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Francis Diebold

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. S. Boragan Aruoba & Francis X. Diebold & Jeremy Nalewaik & Frank Schorfheide & Dongho Song, 2011. "Improving GDP Measurement: A Forecast Combination Perspective," NBER Working Papers 17421, National Bureau of Economic Research, Inc.

    Mentioned in:

    1. Better GDP estimates
      by Economic Logician in Economic Logic on 2011-10-12 19:28:00
  2. S. Boragan Aruoba & Francis X. Diebold, 2010. "Real-Time Macroeconomic Monitoring: Real Activity, Inflation, and Interactions," PIER Working Paper Archive 10-002, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.

    Mentioned in:

    1. Nowcasting: recession ended in July 2009
      by Economic Logician in Economic Logic on 2010-02-10 21:19:00
  3. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Clara Vega, 2002. "Micro Effects of Macro Announcements: Real-Time Price Discovery in Foreign Exchange?," Center for Financial Institutions Working Papers 02-23, Wharton School Center for Financial Institutions, University of Pennsylvania.

    Mentioned in:

    1. Trading on Leaked Macroeconomic Data
      by noreply@blogger.com (Carola) in Quantitative Ease on 2015-07-08 22:14:00
    2. 'Trading on Leaked Macroeconomic Data'
      by Mark Thoma in Economist's View on 2015-07-08 15:39:09
  4. Aruoba, S. Borağan & Diebold, Francis X. & Nalewaik, Jeremy & Schorfheide, Frank & Song, Dongho, 2016. "Improving GDP measurement: A measurement-error perspective," Journal of Econometrics, Elsevier, vol. 191(2), pages 384-397.

    Mentioned in:

    1. Is the economy growing? Depends on how you measure it : GDP vs. GDI
      by ? in FRED blog on 2022-09-01 13:00:00
  5. Francis X. Diebold, 2012. "Comparing Predictive Accuracy, Twenty Years Later: A Personal Perspective on the Use and Abuse of Diebold-Mariano Tests," PIER Working Paper Archive 12-035, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.

    Mentioned in:

    1. My "Must Read" List
      by Dave Giles in Econometrics Beat: Dave Giles' Blog on 2012-09-27 06:33:00
  6. Author Profile
    1. Where did the Phrase “Big Data” Come From?
      by Clive Jones in Business Forecasting on 2013-09-04 21:52:38
    2. The REPEC Fantasy League and My Initial Endowment of Economists
      by Matthew Kahn in Environmental and Urban Economics on 2015-07-26 23:22:00

RePEc Biblio mentions

As found on the RePEc Biblio, the curated bibliography of Economics:
  1. Christoffersen, Peter F. & Diebold, Francis X., 1997. "Optimal Prediction Under Asymmetric Loss," Econometric Theory, Cambridge University Press, vol. 13(6), pages 808-817, December.

    Mentioned in:

    1. > Econometrics > Forecasting
  2. Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-263, July.

    Mentioned in:

    1. > Econometrics > Forecasting
  3. Francis X. Diebold, 2012. "A Personal Perspective on the Origin(s) and Development of “Big Data": The Phenomenon, the Term, and the Discipline, Second Version," PIER Working Paper Archive 13-003, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 26 Nov 2012.

    Mentioned in:

    1. > Econometrics > Big Data

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. Christoffersen, Peter F & Diebold, Francis X, 1996. "Further Results on Forecasting and Model Selection under Asymmetric Loss," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(5), pages 561-571, Sept.-Oct.

    Mentioned in:

    1. Further results on forecasting and model selection under asymmetric loss (Journal of Applied Econometrics 1996) in ReplicationWiki ()
  2. Francis X. Diebold & Lutz Kilian, 2001. "Measuring predictability: theory and macroeconomic applications," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(6), pages 657-669.

    Mentioned in:

    1. Measuring predictability: theory and macroeconomic applications (Journal of Applied Econometrics 2001) in ReplicationWiki ()
  3. FrancisX. Diebold & Kamil Yilmaz, 2009. "Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets," Economic Journal, Royal Economic Society, vol. 119(534), pages 158-171, January.

    Mentioned in:

    1. Measuring financial asset return and volatility spillovers, with application to global equity markets (EJ 2009) in ReplicationWiki ()
  4. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Clara Vega, 2003. "Micro Effects of Macro Announcements: Real-Time Price Discovery in Foreign Exchange," American Economic Review, American Economic Association, vol. 93(1), pages 38-62, March.

    Mentioned in:

    1. Micro Effects of Macro Announcements: Real-Time Price Discovery in Foreign Exchange (AER 2003) in ReplicationWiki ()
  5. Diebold, Francis X & Nerlove, Marc, 1989. "The Dynamics of Exchange Rate Volatility: A Multivariate Latent Factor Arch Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 4(1), pages 1-21, Jan.-Mar..

    Mentioned in:

    1. The dynamics of exchange rate volatility: A multivariate latent factor ARCH model (Journal of Applied Econometrics 1989) in ReplicationWiki ()
  6. Diebold, Francis X, 1989. "Structural Time Series Analysis and Modelling Package: A Review," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 4(2), pages 195-204, April-Jun.

    Mentioned in:

    1. Structural time series analysis and modelling package: A review (Journal of Applied Econometrics 1989) in ReplicationWiki ()

Working papers

  1. Richard T. Baillie & Francis X. Diebold & George Kapetanios & Kun Ho Kim, 2022. "On Robust Inference in Time Series Regression," Papers 2203.04080, arXiv.org, revised Oct 2023.

    Cited by:

    1. Richard T. Baillie & Francis X. Diebold & George Kapetanios & Kun Ho Kim, 2022. "A New Test forMarket Efficiency and Uncovered Interest Parity," PIER Working Paper Archive 22-029, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.

  2. Francis X. Diebold & Glenn D. Rudebusch & Maximilian Goebel & Philippe Goulet Coulombe & Boyuan Zhang, 2022. "When Will Arctic Sea Ice Disappear? Projections of Area, Extent, Thickness, and Volume," Papers 2203.04040, arXiv.org, revised May 2023.

    Cited by:

    1. B. Cooper Boniece & Lajos Horv'ath & Lorenzo Trapani, 2023. "On changepoint detection in functional data using empirical energy distance," Papers 2310.04853, arXiv.org.

  3. Francis X. Diebold & Kamil Yilmaz, 2022. "On the Past, Present, and Future of the Diebold-Yilmaz Approach to Dynamic Network Connectedness," Papers 2211.04184, arXiv.org, revised Jan 2023.

    Cited by:

    1. Bastianin, Andrea & Casoli, Chiara & Galeotti, Marzio, 2023. "The connectedness of Energy Transition Metals," FEEM Working Papers 336984, Fondazione Eni Enrico Mattei (FEEM).

  4. Francis X. Diebold & Maximilian Gobel, 2021. "A Benchmark Model for Fixed-Target Arctic Sea Ice Forecasting," Papers 2101.10359, arXiv.org, revised Jan 2022.

    Cited by:

    1. Diebold, Francis X. & Göbel, Maximilian & Goulet Coulombe, Philippe, 2023. "Assessing and comparing fixed-target forecasts of Arctic sea ice: Glide charts for feature-engineered linear regression and machine learning models," Energy Economics, Elsevier, vol. 124(C).
    2. Francis X. Diebold & Maximilian Gobel & Philippe Goulet Coulombe, 2022. "Assessing and Comparing Fixed-Target Forecasts of Arctic Sea Ice: Glide Charts for Feature-Engineered Linear Regression and Machine Learning Models," Working Papers 22-04, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
    3. Francis X. Diebold & Maximilian Gobel & Philippe Goulet Coulombe, 2022. "Assessing and Comparing Fixed-Target Forecasts of Arctic Sea Ice:Glide Charts for Feature-Engineered Linear Regression and Machine Learning Models," PIER Working Paper Archive 22-028, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.

  5. Francis X. Diebold, 2020. "Real-Time Real Economic Activity: Exiting the Great Recession and Entering the Pandemic Recession," NBER Working Papers 27482, National Bureau of Economic Research, Inc.

    Cited by:

    1. Christiane Baumeister & Pierre Guérin, 2020. "A Comparison of Monthly Global Indicators for Forecasting Growth," CESifo Working Paper Series 8656, CESifo.
    2. Flávio Menezes & Vivian Figer & Fernanda Jardim & Pedro Medeiros, 2021. "Using electricity consumption to predict economic activity during COVID-19 in Brazil," Discussion Papers Series 641, School of Economics, University of Queensland, Australia.
    3. Tesi Aliaj & Milos Ciganovic & Massimiliano Tancioni, 2023. "Nowcasting inflation with Lasso‐regularized vector autoregressions and mixed frequency data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(3), pages 464-480, April.
    4. Christiane Baumeister & Danilo Leiva-León & Eric R. Sims, 2021. "Tracking Weekly State-Level Economic Conditions," CESifo Working Paper Series 9165, CESifo.
    5. Menezes, Flavio & Figer, Vivian & Jardim, Fernanda & Medeiros, Pedro, 2022. "A near real-time economic activity tracker for the Brazilian economy during the COVID-19 pandemic," Economic Modelling, Elsevier, vol. 112(C).
    6. Frank Schorfheide & Dongho Song, 2020. "Real-Time Forecasting with a (Standard) Mixed-Frequency VAR During a Pandemic," PIER Working Paper Archive 20-039, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    7. Poncela, Pilar & Ruiz, Esther & Miranda, Karen, 2021. "Factor extraction using Kalman filter and smoothing: This is not just another survey," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1399-1425.
    8. Jad Beyhum & Jonas Striaukas, 2023. "Sparse plus dense MIDAS regressions and nowcasting during the COVID pandemic," Papers 2306.13362, arXiv.org, revised Dec 2023.
    9. Julien Chevallier, 2021. "Covid-19 Outbreak and CO2 Emissions: Macro-Financial Linkages," Working Papers 2021-004, Department of Research, Ipag Business School.
    10. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino & Elmar Mertens, 2021. "Addressing COVID-19 Outliers in BVARs with Stochastic Volatility," Working Papers 21-02R, Federal Reserve Bank of Cleveland, revised 09 Aug 2021.
    11. Alejandra Bellatin & Gabriela Galassi, 2022. "What COVID-19 May Leave Behind: Technology-Related Job Postings in Canada," Staff Working Papers 22-17, Bank of Canada.
    12. Aktham Maghyereh & Hussein Abdoh, 2022. "Global financial crisis versus COVID‐19: Evidence from sentiment analysis," International Finance, Wiley Blackwell, vol. 25(2), pages 218-248, August.
    13. Aaronson, Daniel & Brave, Scott A. & Butters, R. Andrew & Fogarty, Michael & Sacks, Daniel W. & Seo, Boyoung, 2022. "Forecasting unemployment insurance claims in realtime with Google Trends," International Journal of Forecasting, Elsevier, vol. 38(2), pages 567-581.
    14. Qiu, Yue & Zheng, Yuchen, 2023. "Improving box office projections through sentiment analysis: Insights from regularization-based forecast combinations," Economic Modelling, Elsevier, vol. 125(C).
    15. Marcellino, Massimiliano & Foroni, Claudia & Stevanovic, Dalibor, 2020. "Forecasting the Covid-19 recession and recovery: Lessons from the financial crisis," CEPR Discussion Papers 15114, C.E.P.R. Discussion Papers.
    16. Bellatin, Alejandra & Galassi, Gabriela, 2022. "What COVID-19 May Leave Behind: Technology-Related Job Postings in Canada," IZA Discussion Papers 15209, Institute of Labor Economics (IZA).
    17. Daniel J. Lewis & Karel Mertens & James H. Stock & Mihir Trivedi, 2020. "Measuring Real Activity Using a Weekly Economic Index," Staff Reports 920, Federal Reserve Bank of New York.
    18. Stavros Degiannakis, 2023. "The D-model for GDP nowcasting," Working Papers 317, Bank of Greece.

  6. Francis X. Diebold, 2020. ""Big Data" and its Origins," Papers 2008.05835, arXiv.org, revised Jan 2021.

    Cited by:

    1. Francis X. Diebold & Kamil Yilmaz, 2022. "On the Past, Present, and Future of the Diebold-Yilmaz Approach to Dynamic Network Connectedness," Koç University-TUSIAD Economic Research Forum Working Papers 2207, Koc University-TUSIAD Economic Research Forum.

  7. Francis X. Diebold & Maximilian Gobel & Philippe Goulet Coulombe & Glenn D. Rudebusch & Boyuan Zhang, 2020. "Optimal Combination of Arctic Sea Ice Extent Measures: A Dynamic Factor Modeling Approach," Papers 2003.14276, arXiv.org, revised Aug 2020.

    Cited by:

    1. Diebold, Francis X. & Rudebusch, Glenn D., 2022. "Probability assessments of an ice-free Arctic: Comparing statistical and climate model projections," Journal of Econometrics, Elsevier, vol. 231(2), pages 520-534.
    2. Ar'anzazu de Juan & Pilar Poncela & Vladimir Rodr'iguez-Caballero & Esther Ruiz, 2022. "Economic activity and climate change," Papers 2206.03187, arXiv.org, revised Jun 2022.
    3. Hee Soo (test record) Kim & Christian Matthes & Toan Phan, 2011. "Extreme Weather and the Macroeconomy," Working Paper 21-14, Federal Reserve Bank of Richmond.
    4. Poncela, Pilar & Ruiz, Esther & Miranda, Karen, 2021. "Factor extraction using Kalman filter and smoothing: This is not just another survey," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1399-1425.
    5. Diebold, Francis X. & Göbel, Maximilian & Goulet Coulombe, Philippe, 2023. "Assessing and comparing fixed-target forecasts of Arctic sea ice: Glide charts for feature-engineered linear regression and machine learning models," Energy Economics, Elsevier, vol. 124(C).
    6. Escribano, Alvaro & Peña, Daniel & Ruiz, Esther, 2021. "30 years of cointegration and dynamic factor models forecasting and its future with big data: Editorial," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1333-1337.
    7. Francis X. Diebold & Glenn D. Rudebusch, 2023. "Climate Models Underestimate the Sensitivity of Arctic Sea Ice to Carbon Emissions," Papers 2307.03552, arXiv.org.
    8. Marina Friedrich & Luca Margaritella & Stephan Smeekes, 2023. "High-Dimensional Causality for Climatic Attribution," Papers 2302.03996, arXiv.org.
    9. Robert Amano & Marc-André Gosselin & Julien McDonald-Guimond, 2021. "Evolving Temperature Dynamics in Canada: Preliminary Evidence Based on 60 Years of Data," Staff Working Papers 21-22, Bank of Canada.

  8. Francis X. Diebold & Minchul Shin & Boyuan Zhang, 2020. "On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone Inflation and Real Interest Rates," Papers 2012.11649, arXiv.org, revised Jun 2022.

    Cited by:

    1. Ricardo P. Masini & Marcelo C. Medeiros & Eduardo F. Mendes, 2020. "Machine Learning Advances for Time Series Forecasting," Papers 2012.12802, arXiv.org, revised Apr 2021.
    2. Wang, Xiaoqian & Hyndman, Rob J. & Li, Feng & Kang, Yanfei, 2023. "Forecast combinations: An over 50-year review," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1518-1547.
    3. Anthony Garratt & Timo Henckel & Shaun P. Vahey, 2019. "Empirically-transformed linear opinion pools," CAMA Working Papers 2019-47, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    4. Todd E. Clark & Gergely Ganics & Elmar Mertens, 2022. "What is the Predictive Value of SPF Point and Density Forecasts?," Working Papers 22-37, Federal Reserve Bank of Cleveland.
    5. Tony Chernis, 2023. "Combining Large Numbers of Density Predictions with Bayesian Predictive Synthesis," Staff Working Papers 23-45, Bank of Canada.
    6. Bańbura, Marta & Brenna, Federica & Paredes, Joan & Ravazzolo, Francesco, 2021. "Combining Bayesian VARs with survey density forecasts: does it pay off?," Working Paper Series 2543, European Central Bank.

  9. Francis X. Diebold, 2020. "Real-Time Real Economic Activity: Entering and Exiting the Pandemic Recession of 2020," Papers 2006.15183, arXiv.org, revised Jan 2022.

    Cited by:

    1. Frank Schorfheide & Dongho Song, 2020. "Real-Time Forecasting with a (Standard) Mixed-Frequency VAR During a Pandemic," PIER Working Paper Archive 20-039, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    2. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino & Elmar Mertens, 2021. "Addressing COVID-19 Outliers in BVARs with Stochastic Volatility," Working Papers 21-02R, Federal Reserve Bank of Cleveland, revised 09 Aug 2021.
    3. Aktham Maghyereh & Hussein Abdoh, 2022. "Global financial crisis versus COVID‐19: Evidence from sentiment analysis," International Finance, Wiley Blackwell, vol. 25(2), pages 218-248, August.
    4. Marcellino, Massimiliano & Foroni, Claudia & Stevanovic, Dalibor, 2020. "Forecasting the Covid-19 recession and recovery: Lessons from the financial crisis," CEPR Discussion Papers 15114, C.E.P.R. Discussion Papers.

  10. Francis X. Diebold & Glenn D. Rudebusch, 2019. "Probability Assessments of an Ice-Free Arctic: Comparing Statistical and Climate Model Projections," Papers 1912.10774, arXiv.org, revised Jul 2021.

    Cited by:

    1. Francis X. Diebold & Maximilian Gobel & Philippe Goulet Coulombe & Glenn D. Rudebusch & Boyuan Zhang, 2020. "Optimal Combination of Arctic Sea Ice Extent Measures: A Dynamic Factor Modeling Approach," Papers 2003.14276, arXiv.org, revised Aug 2020.
    2. Francis X. Diebold & Maximilian Gobel, 2022. "A Benchmark Model for Fixed-Target Arctic Sea Ice Forecasting," PIER Working Paper Archive 22-002, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    3. Diebold, Francis X. & Göbel, Maximilian & Goulet Coulombe, Philippe, 2023. "Assessing and comparing fixed-target forecasts of Arctic sea ice: Glide charts for feature-engineered linear regression and machine learning models," Energy Economics, Elsevier, vol. 124(C).
    4. Marc Gronwald, 2023. "Explosive Temperatures," CESifo Working Paper Series 10680, CESifo.
    5. Francis X. Diebold & Glenn D. Rudebusch & Maximilian Goebel & Philippe Goulet Coulombe & Boyuan Zhang, 2022. "When Will Arctic Sea Ice Disappear? Projections of Area, Extent, Thickness, and Volume," Papers 2203.04040, arXiv.org, revised May 2023.
    6. Jennifer Castle & David Hendry, 2020. "Identifying the Causal Role of CO2 during the Ice Ages," Economics Series Working Papers 898, University of Oxford, Department of Economics.
    7. Philippe Goulet Coulombe & Maximilian Gobel, 2020. "Arctic Amplification of Anthropogenic Forcing: A Vector Autoregressive Analysis," Papers 2005.02535, arXiv.org, revised Mar 2021.
    8. Francis X. Diebold & Glenn D. Rudebusch, 2023. "Climate Models Underestimate the Sensitivity of Arctic Sea Ice to Carbon Emissions," Papers 2307.03552, arXiv.org.
    9. Francis X. Diebold & Maximilian Gobel & Philippe Goulet Coulombe, 2022. "Assessing and Comparing Fixed-Target Forecasts of Arctic Sea Ice: Glide Charts for Feature-Engineered Linear Regression and Machine Learning Models," Working Papers 22-04, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
    10. B. Cooper Boniece & Lajos Horv'ath & Lorenzo Trapani, 2023. "On changepoint detection in functional data using empirical energy distance," Papers 2310.04853, arXiv.org.
    11. Francis X. Diebold & Maximilian Gobel & Philippe Goulet Coulombe, 2022. "Assessing and Comparing Fixed-Target Forecasts of Arctic Sea Ice:Glide Charts for Feature-Engineered Linear Regression and Machine Learning Models," PIER Working Paper Archive 22-028, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    12. Philippe Goulet Coulombe & Maximilian Gobel, 2021. "Arctic Amplification of Anthropogenic Forcing: A Vector Autoregressive Analysis," Working Papers 21-04, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.

  11. Francis X. Diebold & Glenn D. Rudebusch, 2019. "On the Evolution of U.S. Temperature Dynamics," PIER Working Paper Archive 19-012, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.

    Cited by:

    1. Gadea Rivas, María Dolores & Gonzalo, Jesús, 2021. "A tale of three cities: climate heterogeneity (special issue of SERIES in homage to Juan J. Dolado)," UC3M Working papers. Economics 32200, Universidad Carlos III de Madrid. Departamento de Economía.
    2. María Dolores Gadea Rivas & Jesús Gonzalo, 2022. "A tale of three cities: climate heterogeneity," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 13(1), pages 475-511, May.

  12. Ross Askanazi & Francis X. Diebold & Frank Schorfheide & Minchul Shin, 2018. "On the Comparison of Interval Forecasts," PIER Working Paper Archive 18-013, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 02 Aug 2018.

    Cited by:

    1. Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2019. "Forecasting with a Panel Tobit Model," CAEPR Working Papers 2019-005, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    2. Hyndman, Rob J., 2020. "A brief history of forecasting competitions," International Journal of Forecasting, Elsevier, vol. 36(1), pages 7-14.
    3. Francis X. Diebold & Minchul Shin & Boyuan Zhang, 2021. "On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone Inflation and Real Interest Rates," Working Papers 21-06, Federal Reserve Bank of Philadelphia.
    4. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    5. Arias, Jonas E. & Rubio-Ramírez, Juan F. & Shin, Minchul, 2023. "Macroeconomic forecasting and variable ordering in multivariate stochastic volatility models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1054-1086.
    6. Nico Keilman, 2020. "Evaluating Probabilistic Population Forecasts," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Etudes Economiques (INSEE), issue 520-521, pages 49-64.
    7. Liu, Laura & Moon, Hyungsik Roger & Schorfheide, Frank, 2021. "Panel forecasts of country-level Covid-19 infections," Journal of Econometrics, Elsevier, vol. 220(1), pages 2-22.
    8. Sayar Karmakar & Marek Chudý & Wei Biao Wu, 2022. "Long‐term prediction intervals with many covariates," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(4), pages 587-609, July.
    9. James Mitchell & Martin Weale, 2021. "Censored Density Forecasts: Production and Evaluation," Working Papers 21-12R, Federal Reserve Bank of Cleveland, revised 16 Aug 2022.
    10. Makridakis, Spyros & Hyndman, Rob J. & Petropoulos, Fotios, 2020. "Forecasting in social settings: The state of the art," International Journal of Forecasting, Elsevier, vol. 36(1), pages 15-28.
    11. Francisca Corpas-Burgos & Miguel A. Martinez-Beneito, 2021. "An Autoregressive Disease Mapping Model for Spatio-Temporal Forecasting," Mathematics, MDPI, vol. 9(4), pages 1-17, February.
    12. Spyros Makridakis & Chris Fry & Fotios Petropoulos & Evangelos Spiliotis, 2022. "The Future of Forecasting Competitions: Design Attributes and Principles," INFORMS Joural on Data Science, INFORMS, vol. 1(1), pages 96-113, April.

  13. Francis X. Diebold & Minchul Shin, 2018. "Machine Learning for Regularized Survey Forecast Combination: Partially-Egalitarian Lasso and its Derivatives," NBER Working Papers 24967, National Bureau of Economic Research, Inc.

    Cited by:

    1. Wang, Yudong & Hao, Xianfeng, 2023. "Forecasting the real prices of crude oil: What is the role of parameter instability?," Energy Economics, Elsevier, vol. 117(C).
    2. Granziera, Eleonora & Sekhposyan, Tatevik, 2019. "Predicting relative forecasting performance: An empirical investigation," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1636-1657.
    3. Diebold, Francis X. & Rudebusch, Glenn D., 2022. "Probability assessments of an ice-free Arctic: Comparing statistical and climate model projections," Journal of Econometrics, Elsevier, vol. 231(2), pages 520-534.
    4. Luiz Renato Lima & Lucas Lúcio Godeiro & Mohammed Mohsin, 2021. "Time-Varying Dictionary and the Predictive Power of FED Minutes," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 149-181, January.
    5. Roccazzella, Francesco & Gambetti, Paolo & Vrins, Frédéric, 2021. "Optimal and robust combination of forecasts via constrained optimization and shrinkage," LIDAM Reprints LFIN 2021014, Université catholique de Louvain, Louvain Finance (LFIN).
    6. Li Li & Yanfei Kang & Fotios Petropoulos & Feng Li, 2022. "Feature-based intermittent demand forecast combinations: bias, accuracy and inventory implications," Papers 2204.08283, arXiv.org, revised Aug 2022.
    7. Bartosz Uniejewski & Katarzyna Maciejowska, 2022. "LASSO Principal Component Averaging -- a fully automated approach for point forecast pooling," Papers 2207.04794, arXiv.org.
    8. Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stephane Surprenant, 2020. "How is Machine Learning Useful for Macroeconomic Forecasting?," Working Papers 20-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Aug 2020.
    9. Francis X. Diebold & Minchul Shin & Boyuan Zhang, 2021. "On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone Inflation and Real Interest Rates," Working Papers 21-06, Federal Reserve Bank of Philadelphia.
    10. Wen, Danyan & Liu, Li & Wang, Yudong & Zhang, Yaojie, 2022. "Forecasting crude oil market returns: Enhanced moving average technical indicators," Resources Policy, Elsevier, vol. 76(C).
    11. Zhang, Yaojie & Wahab, M.I.M. & Wang, Yudong, 2023. "Forecasting crude oil market volatility using variable selection and common factor," International Journal of Forecasting, Elsevier, vol. 39(1), pages 486-502.
    12. Guo, Xiaozhu & Huang, Dengshi & Li, Xiafei & Liang, Chao, 2023. "Are categorical EPU indices predictable for carbon futures volatility? Evidence from the machine learning method," International Review of Economics & Finance, Elsevier, vol. 83(C), pages 672-693.
    13. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    14. Marta Poncela-Blanco & Pilar Poncela, 2021. "Improving Wind Power Forecasts: Combination through Multivariate Dimension Reduction Techniques," Energies, MDPI, vol. 14(5), pages 1-16, March.
    15. Jeronymo Marcondes Pinto & Emerson Fernandes Marçal, 2023. "An artificial intelligence approach to forecasting when there are structural breaks: a reinforcement learning-based framework for fast switching," Empirical Economics, Springer, vol. 65(4), pages 1729-1759, October.
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    17. James Younker, 2022. "Calculating Effective Degrees of Freedom for Forecast Combinations and Ensemble Models," Discussion Papers 2022-19, Bank of Canada.
    18. Yusupova, Alisa & Pavlidis, Nicos G. & Pavlidis, Efthymios G., 2023. "Dynamic linear models with adaptive discounting," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1925-1944.
    19. Yoonseok Lee & Donggyu Sul, 2023. "Depth-weighted Forecast Combination: Application to COVID-19 Cases," Advances in Econometrics, in: Essays in Honor of Joon Y. Park: Econometric Methodology in Empirical Applications, volume 45, pages 235-260, Emerald Group Publishing Limited.
    20. Constantin Rudolf Salomo Bürgi, 2023. "How to deal with missing observations in surveys of professional forecasters," Journal of Applied Economics, Taylor & Francis Journals, vol. 26(1), pages 2185975-218, December.
    21. Roccazzella, Francesco & Candelon, Bertrand, 2022. "Should we care about ECB inflation expectations?," LIDAM Discussion Papers LFIN 2022004, Université catholique de Louvain, Louvain Finance (LFIN).
    22. Ryan Cumings-Menon & Minchul Shin, 2020. "Probability Forecast Combination via Entropy Regularized Wasserstein Distance," Working Papers 20-31/R, Federal Reserve Bank of Philadelphia.
    23. Meira, Erick & Cyrino Oliveira, Fernando Luiz & Jeon, Jooyoung, 2021. "Treating and Pruning: New approaches to forecasting model selection and combination using prediction intervals," International Journal of Forecasting, Elsevier, vol. 37(2), pages 547-568.
    24. Katarzyna Maciejowska & Bartosz Uniejewski & Tomasz Serafin, 2020. "PCA forecast averaging - predicting day-ahead and intraday electricity prices," WORking papers in Management Science (WORMS) WORMS/20/02, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
    25. Michael T. Kiley, 2020. "Financial Conditions and Economic Activity: Insights from Machine Learning," Finance and Economics Discussion Series 2020-095, Board of Governors of the Federal Reserve System (U.S.).
    26. Uniejewski, Bartosz & Maciejowska, Katarzyna, 2023. "LASSO principal component averaging: A fully automated approach for point forecast pooling," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1839-1852.
    27. Lu, Fei & Ma, Feng & Li, Pan & Huang, Dengshi, 2022. "Natural gas volatility predictability in a data-rich world," International Review of Financial Analysis, Elsevier, vol. 83(C).
    28. Jiun-Hua Su, 2021. "No-Regret Forecasting with Egalitarian Committees," Papers 2109.13801, arXiv.org.
    29. Wang, Xiaoqian & Hyndman, Rob J. & Li, Feng & Kang, Yanfei, 2023. "Forecast combinations: An over 50-year review," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1518-1547.
    30. Godahewa, Rakshitha & Bergmeir, Christoph & Webb, Geoffrey I. & Montero-Manso, Pablo, 2023. "An accurate and fully-automated ensemble model for weekly time series forecasting," International Journal of Forecasting, Elsevier, vol. 39(2), pages 641-658.
    31. Yumin Li & Ruiqi Yang & Xiaoman Wang & Jiaming Zhu & Nan Song, 2023. "Carbon Price Combination Forecasting Model Based on Lasso Regression and Optimal Integration," Sustainability, MDPI, vol. 15(12), pages 1-26, June.
    32. Rachidi Kotchoni & Maxime Leroux & Dalibor Stevanovic, 2019. "Macroeconomic forecast accuracy in a data‐rich environment," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(7), pages 1050-1072, November.
    33. Saidjon Shiralievich Tavarov & Alexander Sidorov & Zsolt Čonka & Murodbek Safaraliev & Pavel Matrenin & Mihail Senyuk & Svetlana Beryozkina & Inga Zicmane, 2023. "Control of Operational Modes of an Urban Distribution Grid under Conditions of Uncertainty," Energies, MDPI, vol. 16(8), pages 1-18, April.
    34. Grzegorz Marcjasz & Bartosz Uniejewski & Rafał Weron, 2020. "Beating the Naïve—Combining LASSO with Naïve Intraday Electricity Price Forecasts," Energies, MDPI, vol. 13(7), pages 1-16, April.
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    36. Maehashi, Kohei & Shintani, Mototsugu, 2020. "Macroeconomic forecasting using factor models and machine learning: an application to Japan," Journal of the Japanese and International Economies, Elsevier, vol. 58(C).
    37. Tae-Hwy Lee & Ekaterina Seregina, 2020. "Learning from Forecast Errors: A New Approach to Forecast Combinations," Papers 2011.02077, arXiv.org, revised May 2021.
    38. Qian, Yilin & Thompson, Ryan & Vasnev, Andrey L, 2022. "Global combinations of expert forecasts," Working Papers BAWP-2022-02, University of Sydney Business School, Discipline of Business Analytics.
    39. Kohei Maehashi & Mototsugu Shintani, 2020. "Macroeconomic Forecasting Using Factor Models and Machine Learning: An Application to Japan," CIRJE F-Series CIRJE-F-1146, CIRJE, Faculty of Economics, University of Tokyo.
    40. Petropoulos, Fotios & Spiliotis, Evangelos & Panagiotelis, Anastasios, 2023. "Model combinations through revised base rates," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1477-1492.
    41. Anthony Garratt & Timo Henckel & Shaun P. Vahey, 2019. "Empirically-transformed linear opinion pools," CAMA Working Papers 2019-47, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    42. Andrii Babii & Eric Ghysels & Jonas Striaukas, 2023. "Econometrics of Machine Learning Methods in Economic Forecasting," Papers 2308.10993, arXiv.org.
    43. Ryan Thompson & Yilin Qian & Andrey L. Vasnev, 2022. "Flexible global forecast combinations," Papers 2207.07318, arXiv.org, revised Mar 2024.
    44. Daniel Borup & David E. Rapach & Erik Christian Montes Schütte, 2021. "Now- and Backcasting Initial Claims with High-Dimensional Daily Internet Search-Volume Data," CREATES Research Papers 2021-02, Department of Economics and Business Economics, Aarhus University.
    45. Bin Chen & Kenwin Maung, 2020. "Time-varying Forecast Combination for High-Dimensional Data," Papers 2010.10435, arXiv.org.
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  14. Francis X. Diebold & Minchul Shin, 2017. "Beating the Simple Average: Egalitarian LASSO for Combining Economic Forecasts," PIER Working Paper Archive 17-017, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 20 Aug 2017.

    Cited by:

    1. Daniele Bianchi & Kenichiro McAlinn, 2018. "Large-Scale Dynamic Predictive Regressions," Papers 1803.06738, arXiv.org.
    2. Warwick Smith & Anca M. Hanea & Mark A. Burgman, 2022. "Can Groups Improve Expert Economic and Financial Forecasts?," Forecasting, MDPI, vol. 4(3), pages 1-18, August.
    3. Nir Billfeld & Moshe Kim, 2019. "Semiparametric correction for endogenous truncation bias with Vox Populi based participation decision," Papers 1902.06286, arXiv.org.
    4. Nikodinoska, Dragana & Käso, Mathias & Müsgens, Felix, 2022. "Solar and wind power generation forecasts using elastic net in time-varying forecast combinations," Applied Energy, Elsevier, vol. 306(PA).
    5. Camila Figueroa S. & Michael Pedersen, 2019. "A system for forecasting Chilean cash demand – the role of forecast combinations," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 22(2), pages 040-068, August.

  15. Francis X. Diebold & Laura Liu & Kamil Yilmaz, 2017. "Commodity Connectedness," NBER Working Papers 23685, National Bureau of Economic Research, Inc.

    Cited by:

    1. Juncal Cunado & David Gabauer & Rangan Gupta, 2021. "Realized Volatility Spillovers between Energy and Metal Markets: A Time-Varying Connectedness Approach," Working Papers 202180, University of Pretoria, Department of Economics.
    2. Thiem, Christopher, 2018. "Cross-category spillovers of economic policy uncertainty," Ruhr Economic Papers 744, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    3. Lucey, Brian M. & Vigne, Samuel A. & Ballester, Laura & Barbopoulos, Leonidas & Brzeszczynski, Janusz & Carchano, Oscar & Dimic, Nebojsa & Fernandez, Viviana & Gogolin, Fabian & González-Urteaga, Ana , 2018. "Future directions in international financial integration research - A crowdsourced perspective," International Review of Financial Analysis, Elsevier, vol. 55(C), pages 35-49.
    4. Scarcioffolo, Alexandre Ribeiro & Etienne, Xiaoli L., 2019. "How connected are the U.S. regional natural gas markets in the post-deregulation era? Evidence from time-varying connectedness analysis," Journal of Commodity Markets, Elsevier, vol. 15(C), pages 1-1.
    5. Escribano, Ana & Koczar, Monika W. & Jareño, Francisco & Esparcia, Carlos, 2023. "Shock transmission between crude oil prices and stock markets," Resources Policy, Elsevier, vol. 83(C).
    6. Shah, Adil Ahmad & Dar, Arif Billah, 2021. "Exploring diversification opportunities across commodities and financial markets: Evidence from time-frequency based spillovers," Resources Policy, Elsevier, vol. 74(C).
    7. Costola, Michele & Lorusso, Marco, 2021. "Spillovers among Energy Commodities and the Russian Stock Market," MPRA Paper 108990, University Library of Munich, Germany.
    8. Evrim Mandacı, Pınar & Cagli, Efe Çaglar & Taşkın, Dilvin, 2020. "Dynamic connectedness and portfolio strategies: Energy and metal markets," Resources Policy, Elsevier, vol. 68(C).
    9. Semeyutin, Artur & Gozgor, Giray & Lau, Chi Keung Marco & Xu, Bing, 2021. "Effects of idiosyncratic jumps and co-jumps on oil, gold, and copper markets," Energy Economics, Elsevier, vol. 104(C).
    10. Gong, Xu & Xu, Jun & Liu, Tangyong & Zhou, Zicheng, 2022. "Dynamic volatility connectedness between industrial metal markets," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    11. Lukas Boeckelmann & Arthur Stalla-Bourdillon, 2021. "Structural Estimation of Time-Varying Spillovers:an Application to International Credit Risk Transmission," Working Papers hal-03338209, HAL.
    12. Dungey, Mardi & Islam, Raisul & Volkov, Vladimir, 2019. "Crisis transmission: visualizing vulnerability," Working Papers 2019-07, University of Tasmania, Tasmanian School of Business and Economics.
    13. Liu, Pan & Power, Gabriel J. & Vedenov, Dmitry, 2021. "Fair-weather Friends? Sector-specific volatility connectedness and transmission," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 712-736.
    14. Liang, Chao & Ma, Feng & Li, Ziyang & Li, Yan, 2020. "Which types of commodity price information are more useful for predicting US stock market volatility?," Economic Modelling, Elsevier, vol. 93(C), pages 642-650.
    15. An, Sufang & Gao, Xiangyun & An, Haizhong & Liu, Siyao & Sun, Qingru & Jia, Nanfei, 2020. "Dynamic volatility spillovers among bulk mineral commodities: A network method," Resources Policy, Elsevier, vol. 66(C).
    16. Yi, Shuyue & Xu, Zishuang & Wang, Gang-Jin, 2018. "Volatility connectedness in the cryptocurrency market: Is Bitcoin a dominant cryptocurrency?," International Review of Financial Analysis, Elsevier, vol. 60(C), pages 98-114.
    17. Shakya, Shishir & Li, Bingxin & Etienne, Xiaoli, 2022. "Shale revolution, oil and gas prices, and drilling activities in the United States," Energy Economics, Elsevier, vol. 108(C).
    18. Morelli, Giacomo, 2023. "Stochastic ordering of systemic risk in commodity markets," Energy Economics, Elsevier, vol. 117(C).
    19. Balcilar, Mehmet & Gabauer, David & Umar, Zaghum, 2021. "Crude Oil futures contracts and commodity markets: New evidence from a TVP-VAR extended joint connectedness approach," Resources Policy, Elsevier, vol. 73(C).
    20. Wang, Gang-Jin & Xie, Chi & Zhao, Longfeng & Jiang, Zhi-Qiang, 2018. "Volatility connectedness in the Chinese banking system: Do state-owned commercial banks contribute more?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 57(C), pages 205-230.
    21. Fan, Zaifeng & Jump, Jeff & Tse, Yiuman & Yu, Linda, 2023. "Volatility in US dairy futures markets," Journal of Commodity Markets, Elsevier, vol. 29(C).
    22. Pagnottoni, Paolo & Spelta, Alessandro, 2023. "The motifs of risk transmission in multivariate time series: Application to commodity prices," Socio-Economic Planning Sciences, Elsevier, vol. 87(PB).
    23. Christopher Thiem, 2020. "Cross-Category, Trans-Pacific Spillovers of Policy Uncertainty and Financial Market Volatility," Open Economies Review, Springer, vol. 31(2), pages 317-342, April.
    24. Najaf Iqbal & Elie Bouri & Guangrui Liu & Ashish Kumar, 2024. "Volatility spillovers during normal and high volatility states and their driving factors: A cross‐country and cross‐asset analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(1), pages 975-995, January.
    25. Apergis, Nicholas, 2023. "Realized higher-order moments spillovers across cryptocurrencies," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 85(C).
    26. Wen, Tiange & Wang, Gang-Jin, 2020. "Volatility connectedness in global foreign exchange markets," Journal of Multinational Financial Management, Elsevier, vol. 54(C).
    27. Pagnottoni, Paolo, 2023. "Superhighways and roads of multivariate time series shock transmission: Application to cryptocurrency, carbon emission and energy prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 615(C).
    28. Wang, Gang-Jin & Chen, Yang-Yang & Si, Hui-Bin & Xie, Chi & Chevallier, Julien, 2021. "Multilayer information spillover networks analysis of China’s financial institutions based on variance decompositions," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 325-347.
    29. Ma, Yan-Ran & Ji, Qiang & Wu, Fei & Pan, Jiaofeng, 2021. "Financialization, idiosyncratic information and commodity co-movements," Energy Economics, Elsevier, vol. 94(C).
    30. Shah, Adil Ahmad & Dar, Arif Billah, 2022. "Asymmetric, time and frequency-based spillover transmission in financial and commodity markets," The Journal of Economic Asymmetries, Elsevier, vol. 25(C).
    31. Jonas Krampe & Luca Margaritella, 2024. "Global bank network connectedness revisited: What is common, idiosyncratic and when?," Papers 2402.02482, arXiv.org.
    32. Cui, Jinxin & Maghyereh, Aktham, 2023. "Higher-order moment risk connectedness and optimal investment strategies between international oil and commodity futures markets: Insights from the COVID-19 pandemic and Russia-Ukraine conflict," International Review of Financial Analysis, Elsevier, vol. 86(C).
    33. Akyildirim, Erdinc & Cepni, Oguzhan & Pham, Linh & Uddin, Gazi Salah, 2022. "How connected is the agricultural commodity market to the news-based investor sentiment?," Energy Economics, Elsevier, vol. 113(C).
    34. Agyei, Samuel Kwaku & Umar, Zaghum & Bossman, Ahmed & Teplova, Tamara, 2023. "Dynamic connectedness between global commodity sectors, news sentiment, and sub-Saharan African equities," Emerging Markets Review, Elsevier, vol. 56(C).
    35. Wang, Xiaoyang, 2022. "Efficient markets are more connected: An entropy-based analysis of the energy, industrial metal and financial markets," Energy Economics, Elsevier, vol. 111(C).
    36. Balli, Faruk & Balli, Hatice Ozer & Dang, Tam Hoang Nhat & Gabauer, David, 2023. "Contemporaneous and lagged R2 decomposed connectedness approach: New evidence from the energy futures market," Finance Research Letters, Elsevier, vol. 57(C).
    37. Ogbuabor, Jonathan E. & Anthony-Orji, Onyinye I. & Manasseh, Charles O. & Orji, Anthony, 2020. "Measuring the dynamics of COMESA output connectedness with the global economy," The Journal of Economic Asymmetries, Elsevier, vol. 21(C).

  16. Francis X. Diebold & Frank Schorfheide & Minchul Shin, 2016. "Real-Time Forecast Evaluation of DSGE Models with Stochastic Volatility," NBER Working Papers 22615, National Bureau of Economic Research, Inc.

    Cited by:

    1. Wang, Yudong & Liu, Li & Wu, Chongfeng, 2020. "Forecasting commodity prices out-of-sample: Can technical indicators help?," International Journal of Forecasting, Elsevier, vol. 36(2), pages 666-683.
    2. Ivashchenko, S., 2020. "Long-term growth sources for sectors of Russian economy," Journal of the New Economic Association, New Economic Association, vol. 48(4), pages 86-112.
    3. Jan Philipp Fritsche & Mathias Klein & Malte Rieth, 2020. "Government Spending Multipliers in (Un)certain Times," Discussion Papers of DIW Berlin 1901, DIW Berlin, German Institute for Economic Research.
    4. Jonathan Benchimol & Sergey Ivashchenko, 2020. "Switching Volatility in a Nonlinear Open Economy," CFDS Discussion Paper Series 2020/8, Center for Financial Development and Stability at Henan University, Kaifeng, Henan, China.
    5. Gary Koop & Dimitris Korobilis, 2018. "Forecasting with High-Dimensional Panel VARs," Working Paper series 18-20, Rimini Centre for Economic Analysis.
    6. Sergey Ivashchenko, 2022. "Dynamic Stochastic General Equilibrium Model with Multiple Trends and Structural Breaks," Russian Journal of Money and Finance, Bank of Russia, vol. 81(1), pages 46-72, March.
    7. Paccagnini, Alessia, 2017. "Dealing with Misspecification in DSGE Models: A Survey," MPRA Paper 82914, University Library of Munich, Germany.
    8. S. Boragan Aruoba & Luigi Bocola & Frank Schorfheide, 2013. "Assessing DSGE model nonlinearities," Working Papers 13-47, Federal Reserve Bank of Philadelphia.
    9. Michael Cai & Marco Del Negro & Edward P. Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2019. "Online Estimation of DSGE Models," Liberty Street Economics 20190821, Federal Reserve Bank of New York.
    10. Todd E. Clark & Michael W. McCracken & Elmar Mertens, 2020. "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," The Review of Economics and Statistics, MIT Press, vol. 102(1), pages 17-33, March.
    11. James Morley & Irina B Panovska, 2016. "Is Business Cycle Asymmetry Intrinsic in Industrialized Economies?," Discussion Papers 2016-12, School of Economics, The University of New South Wales.
    12. Andrea Carriero & Galvao, Ana Beatriz & Kapetanios, George, 2016. "A comprehensive evaluation of macroeconomic forecasting methods," EMF Research Papers 10, Economic Modelling and Forecasting Group.
    13. Ramis Khabibullin & Sergei Seleznev, 2022. "Fast Estimation of Bayesian State Space Models Using Amortized Simulation-Based Inference," Papers 2210.07154, arXiv.org.
    14. Angelini, Giovanni & Gorgi, Paolo, 2018. "DSGE Models with observation-driven time-varying volatility," Economics Letters, Elsevier, vol. 171(C), pages 169-171.
    15. Yantao Gao & Xilong Yao & Wenxi Wang & Xin Liu, 2019. "Dynamic effect of environmental tax on export trade: Based on DSGE mode," Energy & Environment, , vol. 30(7), pages 1275-1290, November.
    16. Diebold, Francis X. & Schorfheide, Frank & Shin, Minchul, 2017. "Real-time forecast evaluation of DSGE models with stochastic volatility," CFS Working Paper Series 577, Center for Financial Studies (CFS).
    17. Siddhartha Chib & Minchul Shin & Fei Tan, 2020. "High-Dimensional DSGE Models: Pointers on Prior, Estimation, Comparison, and Prediction∗," Working Papers 20-35, Federal Reserve Bank of Philadelphia.
    18. Farooq Akram & Andrew Binning & Junior Maih, 2016. "Joint prediction bands for macroeconomic risk management," Working Paper 2016/7, Norges Bank.
    19. Reifschneider, David & Tulip, Peter, 2019. "Gauging the uncertainty of the economic outlook using historical forecasting errors: The Federal Reserve’s approach," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1564-1582.
    20. Li, Chenxing & Maheu, John M & Yang, Qiao, 2022. "An Infinite Hidden Markov Model with Stochastic Volatility," MPRA Paper 115456, University Library of Munich, Germany.
    21. Pooyan Amir-Ahmadi & Christian Matthes & Mu-Chun Wang, 2016. "Choosing Prior Hyperparameters," Working Paper 16-9, Federal Reserve Bank of Richmond.
    22. Poledna, Sebastian & Miess, Michael Gregor & Hommes, Cars & Rabitsch, Katrin, 2023. "Economic forecasting with an agent-based model," European Economic Review, Elsevier, vol. 151(C).
    23. David Alaminos & M. Belén Salas & Manuel A. Fernández-Gámez, 2022. "Quantum Computing and Deep Learning Methods for GDP Growth Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 59(2), pages 803-829, February.
    24. Cars Hommes & Mario He & Sebastian Poledna & Melissa Siqueira & Yang Zhang, 2022. "CANVAS: A Canadian Behavioral Agent-Based Model," Staff Working Papers 22-51, Bank of Canada.
    25. Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano, 2021. "Using time-varying volatility for identification in Vector Autoregressions: An application to endogenous uncertainty," Journal of Econometrics, Elsevier, vol. 225(1), pages 47-73.
    26. Yolanda S. Stander, 2023. "The Governance and Disclosure of IFRS 9 Economic Scenarios," JRFM, MDPI, vol. 16(1), pages 1-27, January.
    27. Sergey Ivashchenko & Semih Emre Cekin & Rangan Gupta & Chien-Chiang Lee, 2022. "Real-Time Forecast of DSGE Models with Time-Varying Volatility in GARCH Form," Working Papers 202204, University of Pretoria, Department of Economics.
    28. Dmitry Kreptsev & Sergei Seleznev, 2018. "Forecasting for the Russian Economy Using Small-Scale DSGE Models," Russian Journal of Money and Finance, Bank of Russia, vol. 77(2), pages 51-67, June.
    29. Siddhartha Chib & Minchul Shin & Fei Tan, 2023. "DSGE-SVt: An Econometric Toolkit for High-Dimensional DSGE Models with SV and t Errors," Computational Economics, Springer;Society for Computational Economics, vol. 61(1), pages 69-111, January.
    30. Bäurle Gregor & Kaufmann Daniel & Kaufmann Sylvia & Strachan Rodney, 2020. "Constrained interest rates and changing dynamics at the zero lower bound," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(2), pages 1-26, April.
    31. Michael P Clements & Ana Beatriz Galvao, 2017. "Data Revisions and Real-time Probabilistic Forecasting of Macroeconomic Variables," ICMA Centre Discussion Papers in Finance icma-dp2017-01, Henley Business School, University of Reading.
    32. Mertens, Elmar, 2023. "Precision-based sampling for state space models that have no measurement error," Journal of Economic Dynamics and Control, Elsevier, vol. 154(C).
    33. Musa Abdu & Adamu Jibir & Salihu Abdullahi & Aisha Adamu Hassan, 2021. "Drivers of manufacturing firms’ productivity: a micro-perspective to industrialization in Nigeria," SN Business & Economics, Springer, vol. 1(2), pages 1-17, February.
    34. David L. Reifschneider & Peter Tulip, 2017. "Gauging the Uncertainty of the Economic Outlook Using Historical Forecasting Errors : The Federal Reserve's Approach," Finance and Economics Discussion Series 2017-020, Board of Governors of the Federal Reserve System (U.S.).
    35. James Morley, 2019. "The business cycle: periodic pandemic or rollercoaster ride?," International Journal of Economic Policy Studies, Springer, vol. 13(2), pages 425-431, August.
    36. Clements, Michael P. & Galvao, Ana Beatriz, 2020. "Density Forecasting with BVAR Models under Macroeconomic Data Uncertainty," EMF Research Papers 36, Economic Modelling and Forecasting Group.
    37. Sun Xiaojin & Tsang Kwok Ping, 2019. "What cycles? Data detrending in DSGE models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 23(3), pages 1-23, June.
    38. Sergey M. Ivashchenko, 2019. "DSGE Models: Problem of Trends," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 2, pages 81-95, April.
    39. Xiao-Li Gong & Jin-Yan Lu & Xiong Xiong & Wei Zhang, 2022. "Higher-order dynamic effects of uncertainty risk under thick-tailed stochastic volatility," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-22, December.

  17. Francis X. Diebold & Minchul Shin, 2016. "Assessing Point Forecast Accuracy by Stochastic Error Distance," NBER Working Papers 22516, National Bureau of Economic Research, Inc.

    Cited by:

    1. Borgonovo, Emanuele & Hazen, Gordon B. & Jose, Victor Richmond R. & Plischke, Elmar, 2021. "Probabilistic sensitivity measures as information value," European Journal of Operational Research, Elsevier, vol. 289(2), pages 595-610.
    2. Francis X. Diebold & Minchul Shin & Boyuan Zhang, 2021. "On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone Inflation and Real Interest Rates," Working Papers 21-06, Federal Reserve Bank of Philadelphia.
    3. Diebold, Francis X. & Shin, Minchul, 2015. "Assessing point forecast accuracy by stochastic loss distance," Economics Letters, Elsevier, vol. 130(C), pages 37-38.
    4. Emilian Dobrescu, 2014. "Attempting to Quantify the Accuracy of Complex Macroeconomic Forecasts," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 5-21, December.
    5. Tomás Marinozzi, 2023. "Forecasting Inflation in Argentina: A Probabilistic Approach," Ensayos Económicos, Central Bank of Argentina, Economic Research Department, vol. 1(81), pages 81-110, May.
    6. Jin, Sainan & Corradi, Valentina & Swanson, Norman R., 2017. "Robust Forecast Comparison," Econometric Theory, Cambridge University Press, vol. 33(6), pages 1306-1351, December.
    7. Valentina Corradi & Sainan Jin & Norman R. Swanson, 2023. "Robust forecast superiority testing with an application to assessing pools of expert forecasters," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(4), pages 596-622, June.
    8. Hiroyuki Kawakatsu, 2020. "Recovering Yield Curves from Dynamic Term Structure Models with Time-Varying Factors," Stats, MDPI, vol. 3(3), pages 1-46, August.

  18. Mert Demirer & Francis X. Diebold & Laura Liu & Kamil Yilmaz, 2015. "Estimating Global Bank Network Connectedness," Koç University-TUSIAD Economic Research Forum Working Papers 1512, Koc University-TUSIAD Economic Research Forum.

    Cited by:

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    1. Magkonis, Georgios & Tsouknidis, Dimitris A., 2017. "Dynamic spillover effects across petroleum spot and futures volatilities, trading volume and open interest," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 104-118.
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    3. Billio, Monica & Casarin, Roberto & Rossini, Luca, 2019. "Bayesian nonparametric sparse VAR models," Journal of Econometrics, Elsevier, vol. 212(1), pages 97-115.
    4. Chen, Pu & Semmler, Willi, 2018. "Financial stress, regime switching and spillover effects: Evidence from a multi-regime global VAR model," Journal of Economic Dynamics and Control, Elsevier, vol. 91(C), pages 318-348.
    5. Hardik A. Marfatia & Rangan Gupta & Esin Cakan, 2017. "The International REIT's Time-Varying Response to the U.S. Monetary Policy and Macroeconomic Surprises," Working Papers 201712, University of Pretoria, Department of Economics.
    6. Mardi Dungey & Moses Kangogo & Vladimir Volkov, 2022. "Dynamic effects of network exposure on equity markets," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 12(4), pages 569-629, December.
    7. Victor Olkhov, 2018. "Econophysics Beyond General Equilibrium: the Business Cycle Model," Papers 1804.04721, arXiv.org.
    8. Barunik, Jozef & Krehlik, Tomas, 2016. "Measuring the frequency dynamics of financial and macroeconomic connectedness," FinMaP-Working Papers 54, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    9. Olkhov, Victor, 2018. "Economic Transactions Govern Business Cycles," MPRA Paper 88531, University Library of Munich, Germany, revised 19 Aug 2018.
    10. Uluceviz, Erhan & Yilmaz, Kamil, 2021. "Measuring real–financial connectedness in the U.S. economy," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    11. Erdenebat Bataa & Denise R.Osborn & Marianne Sensier, 2016. "China's Increasing Global Influence: Changes in International Growth Spillovers," Centre for Growth and Business Cycle Research Discussion Paper Series 221, Economics, The University of Manchester.
    12. Victor Olkhov, 2020. "Business Cycles as Collective Risk Fluctuations," Papers 2012.04506, arXiv.org.
    13. Lai, Jennifer & Chen, Hongyi & McNelis, Paul D., 2020. "Macroeconomic adjustment with managed exchange rates and capital controls: Some lessons from China," Economic Modelling, Elsevier, vol. 91(C), pages 759-768.
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    15. Jonathan E. Ogbuabor & Anthony Orji & Gladys C. Aneke & Oyun Erdene-Urnukh, 2016. "Measuring the Real and Financial Connectedness of Selected African Economies with the Global Economy," South African Journal of Economics, Economic Society of South Africa, vol. 84(3), pages 364-399, September.
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    24. Salzmann, Leonard, 2016. "The G7 business cycle in a globalized world," VfS Annual Conference 2016 (Augsburg): Demographic Change 145633, Verein für Socialpolitik / German Economic Association.
    25. Olkhov, Victor, 2018. "Economic and Financial Transactions Govern Business Cycles," MPRA Paper 93269, University Library of Munich, Germany.
    26. Sanderson Abel & Pierre Le Roux, 2016. "Determinants of Banking Sector Profitability in Zimbabwe," International Journal of Economics and Financial Issues, Econjournals, vol. 6(3), pages 845-854.
    27. Monica Billio & Roberto Casarin & Luca Rossini, 2016. "Bayesian nonparametric sparse seemingly unrelated regression model (SUR)," Working Papers 2016:20, Department of Economics, University of Venice "Ca' Foscari".
    28. John Cotter & Mark Hallam & Kamil Yilmaz, 2017. "Mixed-frequency macro-financial spillovers," Working Papers 201704, Geary Institute, University College Dublin.
    29. Tihana ŠKRINJARIĆ & Lidija DEDI & Boško ŠEGO, 2021. "Return and Volatility Spillover between Stock Prices and Exchange Rates in Croatia: A Spillover Methodology Approach," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 93-108, December.
    30. Zhang, Yulian & Hamori, Shigeyuki, 2022. "A connectedness analysis among BRICS’s geopolitical risks and the US macroeconomy," Economic Analysis and Policy, Elsevier, vol. 76(C), pages 182-203.
    31. James Graham, 2014. "'N Sync: how do countries' economies move together?," Reserve Bank of New Zealand Analytical Notes series AN2014/04, Reserve Bank of New Zealand.
    32. Paolo Giudici & Paolo Pagnottoni, 2019. "High Frequency Price Change Spillovers in Bitcoin Markets," Risks, MDPI, vol. 7(4), pages 1-18, November.

  20. Boragan Aruoba & Francis X. Diebold & Jeremy Nalewaik & Frank Schorfheide & Dongho Song, 2013. "Improving GDP Measurement: A Measurement-Error Perspective," PIER Working Paper Archive 13-016, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.

    Cited by:

    1. Jeremy J. Nalewaik, 2014. "Missing Variation in the Great Moderation: Lack of Signal Error and OLS Regression," Finance and Economics Discussion Series 2014-27, Board of Governors of the Federal Reserve System (U.S.).
    2. Reinelt, Timo & Meier, Matthias, 2020. "Monetary policy, markup dispersion, and aggregate TFP," Working Paper Series 2427, European Central Bank.
    3. Francis X. Diebold & Maximilian Gobel & Philippe Goulet Coulombe & Glenn D. Rudebusch & Boyuan Zhang, 2020. "Optimal Combination of Arctic Sea Ice Extent Measures: A Dynamic Factor Modeling Approach," Papers 2003.14276, arXiv.org, revised Aug 2020.
    4. Arabinda Basistha, 2023. "Estimation of short‐run predictive factor for US growth using state employment data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(1), pages 34-50, January.
    5. Daniel Aaronson & Scott A. Brave & Michael Fogarty & Ezra Karger & Spencer D. Krane, 2021. "Tracking U.S. Consumers in Real Time with a New Weekly Index of Retail Trade," Working Paper Series WP-2021-05, Federal Reserve Bank of Chicago, revised 18 Jun 2021.
    6. Michael Cai & Marco Del Negro & Marc Giannoni & Abhi Gupta & Pearl Li & Erica Moszkowski, 2018. "DSGE forecasts of the lost recovery," Staff Reports 844, Federal Reserve Bank of New York.
    7. Anesti, Nikoleta & Galvao, Ana Beatriz & Miranda-Agrippino, Silvia, 2018. "Uncertain kingdom: nowcasting GDP and its revisions," LSE Research Online Documents on Economics 90382, London School of Economics and Political Science, LSE Library.
    8. Ana Beatriz Galvão & James Mitchell, 2023. "Real‐Time Perceptions of Historical GDP Data Uncertainty," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(3), pages 457-481, June.
    9. Nalewaik, Jeremy & Pinto, Eugénio, 2015. "The response of capital goods shipments to demand over the business cycle," Journal of Macroeconomics, Elsevier, vol. 43(C), pages 62-80.
    10. Sekine, Toshitaka, 2022. "Looking from Gross Domestic Income: Alternative view of Japan’s economy," Japan and the World Economy, Elsevier, vol. 64(C).
    11. John C. Williams, 2015. "The recovery’s final frontier?," Speech 150, Federal Reserve Bank of San Francisco.
    12. Petrella, Ivan & Venditti, Fabrizio & Delle Monache, Davide, 2016. "Adaptive state space models with applications to the business cycle and financial stress," CEPR Discussion Papers 11599, C.E.P.R. Discussion Papers.
    13. Matteo Barigozzi & Matteo Luciani, 2017. "Common Factors, Trends, and Cycles in Large Datasets," Finance and Economics Discussion Series 2017-111, Board of Governors of the Federal Reserve System (U.S.).
    14. Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2022. "Reconciled Estimates of Monthly GDP in the US," Working Papers 22-01, Federal Reserve Bank of Cleveland.
    15. Tomaz Cajner & Leland D. Crane & Ryan A. Decker & Adrian Hamins-Puertolas & Christopher Kurz, 2019. "Improving the Accuracy of Economic Measurement with Multiple Data Sources: The Case of Payroll Employment Data," NBER Chapters, in: Big Data for Twenty-First-Century Economic Statistics, pages 147-170, National Bureau of Economic Research, Inc.
    16. Eduardo Rossi & Paolo Santucci de Magistris, 2018. "Indirect inference with time series observed with error," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(6), pages 874-897, September.
    17. Peter A.G. van Bergeijk, 2017. "Making Data Measurement Errors Transparent: The Case of the IMF," World Economics, World Economics, 1 Ivory Square, Plantation Wharf, London, United Kingdom, SW11 3UE, vol. 18(3), pages 133-154, July.
    18. Loria, Francesca & Matthes, Christian & Wang, Mu-Chun, 2022. "Economic theories and macroeconomic reality," Journal of Monetary Economics, Elsevier, vol. 126(C), pages 105-117.
    19. Daniel Rees & David Lancaster & Richard Finlay, 2014. "A State-space Approach to Australian GDP Measurement," RBA Research Discussion Papers rdp2014-12, Reserve Bank of Australia.
    20. Tom Stark, 2014. "Real-time performance of GDPplus and alternative model-based measures of GDP: 2005—2014," Research Rap Special Report, Federal Reserve Bank of Philadelphia, issue Nov.
    21. Sentana, Enrique & Almuzara, Martin & Amengual, Dante & Fiorentini, Gabriele, 2022. "GDP Solera: The Ideal Vintage Mix," CEPR Discussion Papers 17196, C.E.P.R. Discussion Papers.
    22. Boragan Aruoba & Francis X. Diebold & Jeremy Nalewaik & Frank Schorfheide & Dongho Song, 2011. "Improving GDP Measurement: A Forecast Combination Perspective," PIER Working Paper Archive 11-028, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    23. Jan-Benedict E. M. Steenkamp & Alberto Maydeu-Olivares, 2023. "Unrestricted factor analysis: A powerful alternative to confirmatory factor analysis," Journal of the Academy of Marketing Science, Springer, vol. 51(1), pages 86-113, January.
    24. Garciga, Christian & Knotek II, Edward S., 2019. "Forecasting GDP growth with NIPA aggregates: In search of core GDP," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1814-1828.
    25. Matei Demetrescu & Robinson Kruse-Becher, 2021. "Is U.S. real output growth really non-normal? Testing distributional assumptions in time-varying location-scale models," CREATES Research Papers 2021-07, Department of Economics and Business Economics, Aarhus University.
    26. Prydz, Espen Beer & Jolliffe, Dean & Serajuddin, Umar, 2021. "Mind the Gap," GLO Discussion Paper Series 944, Global Labor Organization (GLO).
    27. Eiji Goto & Jan P.A.M. Jacobs & Tara M. Sinclair & Simon van Norden, 2021. "Employment Reconciliation and Nowcasting," Working Papers 2021-007, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    28. Carriero, Andrea & Clements, Michael P. & Galvão, Ana Beatriz, 2015. "Forecasting with Bayesian multivariate vintage-based VARs," International Journal of Forecasting, Elsevier, vol. 31(3), pages 757-768.
    29. Geng, Pei, 2022. "Estimation of functional-coefficient autoregressive models with measurement error," Journal of Multivariate Analysis, Elsevier, vol. 192(C).
    30. John G. Fernald & J. Christina Wang, 2015. "Why has the cyclicality of productivity changed?: what does it mean?," Current Policy Perspectives 15-6, Federal Reserve Bank of Boston.
    31. Gospodinov, Nikolay & Komunjer, Ivana & Ng, Serena, 2017. "Simulated minimum distance estimation of dynamic models with errors-in-variables," Journal of Econometrics, Elsevier, vol. 200(2), pages 181-193.
    32. Lee, Hangyu & Kim, Tae Bong, 2023. "The effectiveness of labor market indicators for conducting monetary policy: Evidence from the Korean economy," Economic Modelling, Elsevier, vol. 118(C).
    33. Martín Almuzara & Dante Amengual & Enrique Sentana, 2019. "Normality tests for latent variables," Quantitative Economics, Econometric Society, vol. 10(3), pages 981-1017, July.
    34. John C. Williams, 2015. "Looking forward, forward looking: the path for monetary policy," Speech 138, Federal Reserve Bank of San Francisco.
    35. John C. Williams, 2015. "Data is the new black: monetary policy by the numbers," Speech 140, Federal Reserve Bank of San Francisco.
    36. Pinkwart, Nicolas, 2018. "Short-term forecasting economic activity in Germany: A supply and demand side system of bridge equations," Discussion Papers 36/2018, Deutsche Bundesbank.
    37. Ben Zeev, Nadav & Pappa, Evi, 2015. "Multipliers of unexpected increases in defense spending: An empirical investigation," Journal of Economic Dynamics and Control, Elsevier, vol. 57(C), pages 205-226.
    38. John C. Williams, 2015. "Looking forward: the path for monetary policy," FRBSF Economic Letter, Federal Reserve Bank of San Francisco.
    39. Andrew C. Chang & Phillip Li, 2018. "Measurement Error In Macroeconomic Data And Economics Research: Data Revisions, Gross Domestic Product, And Gross Domestic Income," Economic Inquiry, Western Economic Association International, vol. 56(3), pages 1846-1869, July.
    40. Wankeun Oh & Jonghyun Yoo, 2020. "Long-Term Increases and Recent Slowdowns of CO 2 Emissions in Korea," Sustainability, MDPI, vol. 12(17), pages 1-13, August.
    41. Tom Stark, 2015. "First quarters in the national income and product accounts," Research Rap Special Report, Federal Reserve Bank of Philadelphia, issue May.
    42. Dr. Yannic Stucki, 2022. "Measuring Swiss employment growth: a measurement-error approach," Working Papers 2022-11, Swiss National Bank.
    43. Nikoleta Anesti & Ana Beatriz Galvão & Silvia Miranda‐Agrippino, 2022. "Uncertain Kingdom: Nowcasting Gross Domestic Product and its revisions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(1), pages 42-62, January.
    44. Nikolay Gospodinov & Ivana Komunjer & Serena Ng, 2014. "Minimum Distance Estimation of Dynamic Models with Errors-In-Variables," FRB Atlanta Working Paper 2014-11, Federal Reserve Bank of Atlanta.
    45. van Bergeijk, P.A.G., 2017. "Measurement error of global production," ISS Working Papers - General Series 632, International Institute of Social Studies of Erasmus University Rotterdam (ISS), The Hague.
    46. Alessandro Giovannelli & Marco Lippi & Tommaso Proietti, 2023. "Band-Pass Filtering with High-Dimensional Time Series," CEIS Research Paper 559, Tor Vergata University, CEIS, revised 15 Jun 2023.
    47. Kurt Graden Lunsford, 2023. "The Discrepancy Between Expenditure- and Income-Side Estimates of US Output," Economic Commentary, Federal Reserve Bank of Cleveland, vol. 2023(01), pages 1-7, January.
    48. Ammi, Mehdi & Arpin, Emmanuelle & Allin, Sara, 2021. "Interpreting forty-three-year trends of expenditures on public health in Canada: Long-run trends, temporal periods, and data differences," Health Policy, Elsevier, vol. 125(12), pages 1557-1564.
    49. Alifatussaadah, Ardiana & Primariesty, Anindya Diva & Soleh, Agus Mohamad & Andriansyah, Andriansyah, 2019. "Nowcasting Indonesia's GDP Growth: Are Fiscal Data Useful?," MPRA Paper 105252, University Library of Munich, Germany.
    50. Hu, Yingyao & Yao, Jiaxiong, 2022. "Illuminating economic growth," Journal of Econometrics, Elsevier, vol. 228(2), pages 359-378.
    51. Jan P.A.M. Jacobs & Samad Sarferaz & Simon van Norden & Jan-Egbert Sturm, 2013. "Modeling Multivariate Data Revisions," CIRANO Working Papers 2013s-44, CIRANO.
    52. Florian Eckert & Nina Mühlebach, 2023. "Global and local components of output gaps," Empirical Economics, Springer, vol. 65(5), pages 2301-2331, November.
    53. Víctor M. Guerrero & Juan A. Mendoza, 2019. "On measuring economic growth from outer space: a single country approach," Empirical Economics, Springer, vol. 57(3), pages 971-990, September.
    54. Gyurkovics, Éva & Takács, Tibor, 2022. "Robust energy-to-peak filter design for a class of unstable polytopic systems with a macroeconomic application," Applied Mathematics and Computation, Elsevier, vol. 420(C).

  21. Francis X. Diebold, 2012. "Comparing Predictive Accuracy, Twenty Years Later: A Personal Perspective on the Use and Abuse of Diebold-Mariano Tests," PIER Working Paper Archive 12-035, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.

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    1. Adam J. Check & Anna K Nolan & Tyler C. Schipper, 2019. "Forecasting GDP Growth using Disaggregated GDP Revisions," Economics Bulletin, AccessEcon, vol. 39(4), pages 2580-2588.
    2. Claudio, João C. & Heinisch, Katja & Holtemöller, Oliver, 2019. "Nowcasting East German GDP growth: A MIDAS approach," IWH Discussion Papers 24/2019, Halle Institute for Economic Research (IWH).
    3. Florian Ziel & Rick Steinert & Sven Husmann, 2015. "Forecasting day ahead electricity spot prices: The impact of the EXAA to other European electricity markets," Papers 1501.00818, arXiv.org, revised Dec 2015.
    4. Isabel Figuerola‐Ferretti & Alejandro Rodríguez & Eduardo Schwartz, 2021. "Oil price analysts' forecasts," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(9), pages 1351-1374, September.
    5. Dhiman, Harsh S. & Deb, Dipankar & Guerrero, Josep M., 2019. "Hybrid machine intelligent SVR variants for wind forecasting and ramp events," Renewable and Sustainable Energy Reviews, Elsevier, vol. 108(C), pages 369-379.
    6. Luisa Bisaglia & Matteo Grigoletto, 2018. "A new time-varying model for forecasting long-memory series," Papers 1812.07295, arXiv.org.
    7. Giovannelli, Alessandro & Massacci, Daniele & Soccorsi, Stefano, 2021. "Forecasting stock returns with large dimensional factor models," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 252-269.
    8. Nowotarski, Jakub & Weron, Rafał, 2018. "Recent advances in electricity price forecasting: A review of probabilistic forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1548-1568.
    9. Kung, Ko-Lun & MacMinn, Richard D. & Kuo, Weiyu & Tsai, Chenghsien Jason, 2022. "Multi-population mortality modeling: When the data is too much and not enough," Insurance: Mathematics and Economics, Elsevier, vol. 103(C), pages 41-55.
    10. TAKAMIZAWA, Hideyuki & 高見澤, 秀幸, 2017. "A Term Structure Model of Interest Rates with Quadratic Volatility," Working Paper Series G-1-18, Hitotsubashi University Center for Financial Research.
    11. Shapiro, Adam Hale & Sudhof, Moritz & Wilson, Daniel J., 2022. "Measuring news sentiment," Journal of Econometrics, Elsevier, vol. 228(2), pages 221-243.
    12. Magdalena Grothe & Aidan Meyler, 2018. "Inflation Forecasts: Are Market-Based and Survey-Based Measures Informative?," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 9(1), pages 171-188, January.
    13. Seitz, Franz & Albuquerque, Bruno & Baumann, Ursel, 2015. "The Information Content Of Money And Credit For US Activity," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113066, Verein für Socialpolitik / German Economic Association.
    14. Robinson Kruse & Christian Leschinski & Michael Will, 2016. "Comparing Predictive Accuracy under Long Memory - With an Application to Volatility Forecasting," CREATES Research Papers 2016-17, Department of Economics and Business Economics, Aarhus University.
    15. Baris Soybilgen & Ege Yazgan, 2017. "An evaluation of inflation expectations in Turkey," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 17(1), pages 1-31–38.
    16. Jesus Lago & Grzegorz Marcjasz & Bart De Schutter & Rafa{l} Weron, 2020. "Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark," Papers 2008.08004, arXiv.org, revised Dec 2020.
    17. Barbara Rossi, 2013. "Exchange rate predictability," Economics Working Papers 1369, Department of Economics and Business, Universitat Pompeu Fabra.
    18. Christiane Baumeister & Lutz Kilian, 2013. "Forecasting the Real Price of Oil in a Changing World: A Forecast Combination Approach," Staff Working Papers 13-28, Bank of Canada.
    19. Liu, Jing & Ma, Feng & Zhang, Yaojie, 2019. "Forecasting the Chinese stock volatility across global stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 466-477.
    20. Michele Ca' Zorzi & Jakub Muck & Michal Rubaszek, 2015. "Real exchange rate forecasting and ppp: this time the random walk loses," Globalization Institute Working Papers 229, Federal Reserve Bank of Dallas.
    21. Götz, T.B. & Hecq, A.W. & Urbain, J.R.Y.J., 2014. "Combining distributions of real-time forecasts: An application to U.S. growth," Research Memorandum 027, Maastricht University, Graduate School of Business and Economics (GSBE).
    22. Lorenzo Burlon & Simone Emiliozzi & Alessandro Notarpietro & Massimiliano Pisani, 2015. "Medium-term forecasting of euro-area macroeconomic variables with DSGE and BVARX models," Questioni di Economia e Finanza (Occasional Papers) 257, Bank of Italy, Economic Research and International Relations Area.
    23. Davide Pettenuzzo & Zhiyuan Pan & Yudong Wang, 2017. "Forecasting Stock Returns: A Predictor-Constrained Approach," Working Papers 116R, Brandeis University, Department of Economics and International Business School, revised Feb 2018.
    24. Salvatore Carta & Andrea Medda & Alessio Pili & Diego Reforgiato Recupero & Roberto Saia, 2018. "Forecasting E-Commerce Products Prices by Combining an Autoregressive Integrated Moving Average (ARIMA) Model and Google Trends Data," Future Internet, MDPI, vol. 11(1), pages 1-19, December.
    25. Pablo Pincheira & Nicolás Hardy & Felipe Muñoz, 2021. "“Go Wild for a While!”: A New Test for Forecast Evaluation in Nested Models," Mathematics, MDPI, vol. 9(18), pages 1-28, September.
    26. Julien Chevallier & Benoît Sévi, 2013. "A Fear Index to Predict Oil Futures Returns," Working Papers 2013.62, Fondazione Eni Enrico Mattei.
    27. Laura Coroneo & Fabrizio Iacone, 2020. "Comparing predictive accuracy in small samples using fixed‐smoothing asymptotics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(4), pages 391-409, June.
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    29. Cotter, John & Eyiah-Donkor, Emmanuel & Potì, Valerio, 2023. "Commodity futures return predictability and intertemporal asset pricing," Journal of Commodity Markets, Elsevier, vol. 31(C).
    30. Kurov, Alexander & Sancetta, Alessio & Strasser, Georg & Wolfe, Marketa Halova, 2019. "Price Drift Before U.S. Macroeconomic News: Private Information about Public Announcements?," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 54(1), pages 449-479, February.
    31. Tim Bollerslev & Benjamin Hood & John Huss & Lasse Heje Pedersen, 2018. "Risk Everywhere: Modeling and Managing Volatility," The Review of Financial Studies, Society for Financial Studies, vol. 31(7), pages 2729-2773.
    32. Khowaja, Kainat & Saef, Danial & Sizov, Sergej & Härdle, Wolfgang Karl, 2020. "Data Analytics Driven Controlling: bridging statistical modeling and managerial intuition," IRTG 1792 Discussion Papers 2020-026, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    33. Yu‐Sheng Lai, 2018. "Estimation of the optimal futures hedge ratio for equity index portfolios using a realized beta generalized autoregressive conditional heteroskedasticity model," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(11), pages 1370-1390, November.
    34. Diaz, Elena Maria & Perez-Quiros, Gabriel, 2021. "GEA tracker: A daily indicator of global economic activity," Journal of International Money and Finance, Elsevier, vol. 115(C).
    35. De Backer, Bruno & Dewachter, Hans & Iania, Leonardo, 2021. "Macrofinancial information on the post- COVID-19 economic recovery: will it be V, U or L-shaped?," LIDAM Discussion Papers LFIN 2021002, Université catholique de Louvain, Louvain Finance (LFIN).
    36. Luisa Bisaglia & Matteo Grigoletto, 2021. "A new time-varying model for forecasting long-memory series," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(1), pages 139-155, March.
    37. Karsten Müller, 2022. "German forecasters’ narratives: How informative are German business cycle forecast reports?," Empirical Economics, Springer, vol. 62(5), pages 2373-2415, May.
    38. Tschora, Léonard & Pierre, Erwan & Plantevit, Marc & Robardet, Céline, 2022. "Electricity price forecasting on the day-ahead market using machine learning," Applied Energy, Elsevier, vol. 313(C).
    39. Hunt, Ian, 2022. "In-sample tests of predictability are superior to pseudo-out-of-sample tests, even when data mining," International Journal of Forecasting, Elsevier, vol. 38(3), pages 872-877.
    40. Fu, Wenlong & Fang, Ping & Wang, Kai & Li, Zhenxing & Xiong, Dongzhen & Zhang, Kai, 2021. "Multi-step ahead short-term wind speed forecasting approach coupling variational mode decomposition, improved beetle antennae search algorithm-based synchronous optimization and Volterra series model," Renewable Energy, Elsevier, vol. 179(C), pages 1122-1139.
    41. Jiani Heng & Chen Wang & Xuejing Zhao & Liye Xiao, 2016. "Research and Application Based on Adaptive Boosting Strategy and Modified CGFPA Algorithm: A Case Study for Wind Speed Forecasting," Sustainability, MDPI, vol. 8(3), pages 1-25, March.
    42. Markus Hertrich, 2022. "Foreign exchange interventions under a minimum exchange rate regime and the Swiss franc," Review of International Economics, Wiley Blackwell, vol. 30(2), pages 450-489, May.
    43. Tuhkuri, Joonas, 2016. "Forecasting Unemployment with Google Searches," ETLA Working Papers 35, The Research Institute of the Finnish Economy.
    44. Danilo Leiva-Leon, 2017. "Measuring business cycles intra-synchronization in us: a regime-switching interdependence framework," Working Papers 1726, Banco de España.
    45. Shihao Gu & Bryan Kelly & Dacheng Xiu, 2018. "Empirical Asset Pricing via Machine Learning," NBER Working Papers 25398, National Bureau of Economic Research, Inc.
    46. Matei Demetrescu & Christoph Hanck & Robinson Kruse, 2016. "Fixed-b Inference in the Presence of Time-Varying Volatility," CREATES Research Papers 2016-01, Department of Economics and Business Economics, Aarhus University.
    47. Guilherme Lindenmeyer & Pedro Pablo Skorin & Hudson da Silva Torrent, 2021. "Using boosting for forecasting electric energy consumption during a recession: a case study for the Brazilian State Rio Grande do Sul," Letters in Spatial and Resource Sciences, Springer, vol. 14(2), pages 111-128, August.
    48. José Renato Haas Ornelas, 2017. "Expected Currency Returns and Volatility Risk Premia," Working Papers Series 454, Central Bank of Brazil, Research Department.
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    Cited by:

    1. Wen Cao & Clifford Hurvich & Philippe Soulier, 2012. "Drift in Transaction-Level Asset Price Models," Working Papers hal-00756372, HAL.
    2. Segnon, Mawuli & Lux, Thomas, 2013. "Multifractal models in finance: Their origin, properties, and applications," Kiel Working Papers 1860, Kiel Institute for the World Economy (IfW Kiel).
    3. Peter Akioyamen & Yi Zhou Tang & Hussien Hussien, 2021. "A Hybrid Learning Approach to Detecting Regime Switches in Financial Markets," Papers 2108.05801, arXiv.org.
    4. Jorge Pérez-Rodríguez & Emilio Gómez-Déniza & Simón Sosvilla-Rivero, 2019. "“Testing for private information using trade duration models with unobserved market heterogeneity: The case of Banco Popular”," IREA Working Papers 201907, University of Barcelona, Research Institute of Applied Economics, revised Apr 2019.
    5. Bjoern Schulte-Tillmann & Mawuli Segnon & Timo Wiedemann, 2023. "A comparison of high-frequency realized variance measures: Duration- vs. return-based approaches," CQE Working Papers 10523, Center for Quantitative Economics (CQE), University of Muenster.
    6. Xin-Lan Fu & Xing-Lu Gao & Zheng Shan & Zhi-Qiang Jiang & Wei-Xing Zhou, 2018. "Multifractal characteristics and return predictability in the Chinese stock markets," Papers 1806.07604, arXiv.org.
    7. Zikes, Filip & Barunik, Jozef & Shenai, Nikhil, 2015. "Modeling and forecasting persistent financial durations," FinMaP-Working Papers 36, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    8. Abdelhakim Aknouche & Christian Francq, 2022. "Stationarity and ergodicity of Markov switching positive conditional mean models," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(3), pages 436-459, May.
    9. Jeffrey R. Black & Pankaj K. Jain & Wei Sun, 2023. "Trade-time clustering," Review of Quantitative Finance and Accounting, Springer, vol. 60(3), pages 1209-1242, April.
    10. Eric M. Aldrich & Indra Heckenbach & Gregory Laughlin, 2014. "A Compound Multifractal Model for High-Frequency Asset Returns," BYU Macroeconomics and Computational Laboratory Working Paper Series 2014-05, Brigham Young University, Department of Economics, BYU Macroeconomics and Computational Laboratory.
    11. Zhicheng Li & Haipeng Xing, 2022. "High-Frequency Quote Volatility Measurement Using a Change-Point Intensity Model," Mathematics, MDPI, vol. 10(4), pages 1-24, February.
    12. Li, Zhicheng & Chen, Xinyun & Xing, Haipeng, 2023. "A multifactor regime-switching model for inter-trade durations in the high-frequency limit order market," Economic Modelling, Elsevier, vol. 118(C).
    13. Yogo Purwono & Irwan Adi Ekaputra & Zaäfri Ananto Husodo, 2018. "Estimation of Dynamic Mixed Hitting Time Model Using Characteristic Function Based Moments," Computational Economics, Springer;Society for Computational Economics, vol. 51(2), pages 295-321, February.
    14. Aldrich, Eric M. & Heckenbach, Indra & Laughlin, Gregory, 2016. "A compound duration model for high-frequency asset returns," Journal of Empirical Finance, Elsevier, vol. 39(PA), pages 105-128.
    15. Czellar, Veronika & Frazier, David T. & Renault, Eric, 2022. "Approximate maximum likelihood for complex structural models," Journal of Econometrics, Elsevier, vol. 231(2), pages 432-456.
    16. Herrera, Rodrigo & Rodriguez, Alejandro & Pino, Gabriel, 2017. "Modeling and forecasting extreme commodity prices: A Markov-Switching based extreme value model," Energy Economics, Elsevier, vol. 63(C), pages 129-143.
    17. Pérez-Rodríguez, Jorge V. & Gómez-Déniz, Emilio & Sosvilla-Rivero, Simón, 2021. "Testing unobserved market heterogeneity in financial markets: The case of Banco Popular," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 151-160.
    18. Kuosmanen, Petri & Nabulsi, Nasib & Vataja, Juuso, 2015. "Financial variables and economic activity in the Nordic countries," International Review of Economics & Finance, Elsevier, vol. 37(C), pages 368-379.
    19. Zhicheng Li & Haipeng Xing & Xinyun Chen, 2019. "A multifactor regime-switching model for inter-trade durations in the limit order market," Papers 1912.00764, arXiv.org.
    20. Chiranjit Dutta & Kara Karpman & Sumanta Basu & Nalini Ravishanker, 2023. "Review of Statistical Approaches for Modeling High-Frequency Trading Data," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 1-48, May.
    21. Augustyniak, Maciej & Dufays, Arnaud, 2018. "Modeling macroeconomic series with regime-switching models characterized by a high-dimensional state space," Economics Letters, Elsevier, vol. 170(C), pages 122-126.
    22. de Bruijn, L.P. & Franses, Ph.H.B.F., 2015. "Stochastic levels and duration dependence in US unemployment," Econometric Institute Research Papers EI2015-20, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    23. Marcin Wątorek & Jarosław Kwapień & Stanisław Drożdż, 2022. "Multifractal Cross-Correlations of Bitcoin and Ether Trading Characteristics in the Post-COVID-19 Time," Future Internet, MDPI, vol. 14(7), pages 1-15, July.
    24. Veronika Czellar & David T. Frazier & Eric Renault, 2020. "Approximate Maximum Likelihood for Complex Structural Models," Papers 2006.10245, arXiv.org.
    25. Lux, Thomas, 2013. "Exact solutions for the transient densities of continuous-time Markov switching models: With an application to the poisson multifractal model," Kiel Working Papers 1871, Kiel Institute for the World Economy (IfW Kiel).
    26. Suh, Jong Hwan, 2015. "Forecasting the daily outbreak of topic-level political risk from social media using hidden Markov model-based techniques," Technological Forecasting and Social Change, Elsevier, vol. 94(C), pages 115-132.
    27. Brownlees Christian T. & Vannucci Marina, 2013. "A Bayesian approach for capturing daily heterogeneity in intra-daily durations time series," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(1), pages 21-46, February.
    28. Farzad Alavi Fard, 2014. "Optimal Bid-Ask Spread in Limit-Order Books under Regime Switching Framework," Review of Economics & Finance, Better Advances Press, Canada, vol. 4, pages 33-48, November.
    29. Czellar, Veronika & Frazier, David T. & Renault, Eric, 2021. "Approximate Maximum Likelihood for Complex Structural Models," The Warwick Economics Research Paper Series (TWERPS) 1337, University of Warwick, Department of Economics.
    30. Marcin Wk{a}torek & Jaros{l}aw Kwapie'n & Stanis{l}aw Dro.zd.z, 2022. "Multifractal cross-correlations of bitcoin and ether trading characteristics in the post-COVID-19 time," Papers 2208.01445, arXiv.org.
    31. Renault, Eric & van der Heijden, Thijs & Werker, Bas J.M., 2014. "The dynamic mixed hitting-time model for multiple transaction prices and times," Journal of Econometrics, Elsevier, vol. 180(2), pages 233-250.
    32. Kang, Bo Soo & Ryu, Doojin & Ryu, Doowon, 2014. "Phase-shifting behaviour revisited: An alternative measure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 401(C), pages 167-173.

  23. Francis X. Diebold, 2012. "On the Origin(s) and Development of the Term “Big Data"," PIER Working Paper Archive 12-037, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.

    Cited by:

    1. Philip ME Garboden, 2019. "Sources and Types of Big Data for Macroeconomic Forecasting," Working Papers 2019-3, University of Hawaii Economic Research Organization, University of Hawaii at Manoa.
    2. Cara Stitzlein & Simon Fielke & François Waldner & Todd Sanderson, 2021. "Reputational Risk Associated with Big Data Research and Development: An Interdisciplinary Perspective," Sustainability, MDPI, vol. 13(16), pages 1-13, August.

  24. Francis X. Diebold, 2012. "A Personal Perspective on the Origin(s) and Development of “Big Data": The Phenomenon, the Term, and the Discipline, Second Version," PIER Working Paper Archive 13-003, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 26 Nov 2012.

    Cited by:

    1. Götz, Thomas B. & Knetsch, Thomas A., 2019. "Google data in bridge equation models for German GDP," International Journal of Forecasting, Elsevier, vol. 35(1), pages 45-66.
    2. Harvey C Turner & David Atkinson, 2021. "Strategic Decision Making: The Effects of Big Data," International Journal of Operations Management, Inovatus Services Ltd., vol. 1(2), pages 38-45, January.

  25. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2011. "Financial Risk Measurement for Financial Risk Management," PIER Working Paper Archive 11-037, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.

    Cited by:

    1. Belloni, Alexandre & Chen, Mingli & Chernozhukov, Victor, 2016. "Quantile Graphical Models : Prediction and Conditional Independence with Applications to Financial Risk Management," Economic Research Papers 269321, University of Warwick - Department of Economics.
    2. Mert Demirer & Francis X. Diebold & Laura Liu & Kamil Yilmaz, 2015. "Estimating Global Bank Network Connectedness," PIER Working Paper Archive 15-025, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 25 Jul 2015.
    3. Makoto Takahashi & Toshiaki Watanabe & Yasuhiro Omori, 2014. "Volatility and Quantile Forecasts by Realized Stochastic Volatility Models with Generalized Hyperbolic Distribution," CIRJE F-Series CIRJE-F-949, CIRJE, Faculty of Economics, University of Tokyo.
    4. Kyle Jurado & Sydney C. Ludvigson & Serena Ng, 2015. "Measuring Uncertainty," American Economic Review, American Economic Association, vol. 105(3), pages 1177-1216, March.
    5. Tim Bollerslev & Andrew J. Patton & Rogier Quaedvlieg, 2016. "Modeling and Forecasting (Un)Reliable Realized Covariances for More Reliable Financial Decisions," CREATES Research Papers 2016-10, Department of Economics and Business Economics, Aarhus University.
    6. Alexandre Belloni & Mingli Chen & Victor Chernozhukov, 2016. "Quantile Graphical Models: Prediction and Conditional Independence with Applications to Systemic Risk," Papers 1607.00286, arXiv.org, revised Oct 2019.
    7. Diebold, Francis X. & Yilmaz, Kamil, 2015. "Financial and Macroeconomic Connectedness: A Network Approach to Measurement and Monitoring," OUP Catalogue, Oxford University Press, number 9780199338306.
    8. Fengler, Matthias R. & Okhrin, Ostap, 2016. "Managing risk with a realized copula parameter," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 131-152.
    9. Daniele Massacci, 2017. "Tail Risk Dynamics in Stock Returns: Links to the Macroeconomy and Global Markets Connectedness," Management Science, INFORMS, vol. 63(9), pages 3072-3089, September.
    10. Bent Jesper Christensen & Rasmus Tangsgaard Varneskov, 2021. "Dynamic Global Currency Hedging [Arbitrage in the Foreign Exchange Market: Turning on the Microscope]," Journal of Financial Econometrics, Oxford University Press, vol. 19(1), pages 97-127.
    11. F. Lilla, 2017. "High Frequency vs. Daily Resolution: the Economic Value of Forecasting Volatility Models - 2nd ed," Working Papers wp1099, Dipartimento Scienze Economiche, Universita' di Bologna.
    12. Massacci, Daniele, 2014. "A two-regime threshold model with conditional skewed Student t distributions for stock returns," Economic Modelling, Elsevier, vol. 43(C), pages 9-20.
    13. Peter Christoffersen & Asger Lunde & Kasper V. Olesen, 2014. "Factor Structure in Commodity Futures Return and Volatility," CREATES Research Papers 2014-31, Department of Economics and Business Economics, Aarhus University.
    14. Yu Chen & Jie Hu & Weiping Zhang, 2020. "Too Connected to Fail? Evidence from a Chinese Financial Risk Spillover Network," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 28(6), pages 78-100, November.
    15. Isao Ishida & Virmantas Kvedaras, 2015. "Modeling Autoregressive Processes with Moving-Quantiles-Implied Nonlinearity," Econometrics, MDPI, vol. 3(1), pages 1-53, January.
    16. Dias, Alexandra, 2013. "Market capitalization and Value-at-Risk," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 5248-5260.
    17. Francis X. Diebold, 2020. ""Big Data" and its Origins," Papers 2008.05835, arXiv.org, revised Jan 2021.
    18. Han-Ching Huang & Yong-Chern Su & Jen-Tien Tsui, 2015. "Asymmetric GARCH Value-at-Risk over MSCI in Financial Crisis," International Journal of Economics and Financial Issues, Econjournals, vol. 5(2), pages 390-398.
    19. Duan, Yunlong & Mu, Chang & Yang, Meng & Deng, Zhiqing & Chin, Tachia & Zhou, Li & Fang, Qifeng, 2021. "Study on early warnings of strategic risk during the process of firms’ sustainable innovation based on an optimized genetic BP neural networks model: Evidence from Chinese manufacturing firms," International Journal of Production Economics, Elsevier, vol. 242(C).
    20. BALTES Nicolae & DRAGOE Alexandra-Gabriela-Maria, 2017. "Estimating The Return Of The Financial Titles Of The Companies From The Manufacturing Industry, Listed On The Bucharest Stock Exchange," Revista Economica, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 69(3), pages 19-28, August.
    21. Richard Friberg & Mark Sanctuary, 2020. "Exchange rate risk and the skill composition of labor," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 156(2), pages 287-312, May.
    22. Nolte, Ingmar & Xu, Qi, 2015. "The economic value of volatility timing with realized jumps," Journal of Empirical Finance, Elsevier, vol. 34(C), pages 45-59.
    23. Fabrizio Cipollini & Giampiero M. Gallo, 2018. "Modeling Euro STOXX 50 Volatility with Common and Market–specific Components," Working Paper series 18-26, Rimini Centre for Economic Analysis.
    24. Conrad, Christian & Glas, Alexander, 2018. "‘Déjà vol’ revisited: Survey forecasts of macroeconomic variables predict volatility in the cross-section of industry portfolios," Working Papers 0655, University of Heidelberg, Department of Economics.
    25. Fengler, Matthias R. & Herwartz, Helmut, 2015. "Measuring spot variance spillovers when (co)variances are time-varying – the case of multivariate GARCH models," Economics Working Paper Series 1517, University of St. Gallen, School of Economics and Political Science.
    26. Serena Ng & Jonathan H. Wright, 2013. "Facts and Challenges from the Great Recession for Forecasting and Macroeconomic Modeling," NBER Working Papers 19469, National Bureau of Economic Research, Inc.
    27. Nikolaus Hautsch & Lada M. Kyj & Peter Malec, 2015. "Do High‐Frequency Data Improve High‐Dimensional Portfolio Allocations?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(2), pages 263-290, March.
    28. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    29. Mustafayeva, Konul & Wang, Weining, 2020. "Non-Parametric Estimation of Spot Covariance Matrix with High-Frequency Data," IRTG 1792 Discussion Papers 2020-025, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    30. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2016. "Exploiting the errors: A simple approach for improved volatility forecasting," Journal of Econometrics, Elsevier, vol. 192(1), pages 1-18.
    31. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2020. "Multivariate leverage effects and realized semicovariance GARCH models," Journal of Econometrics, Elsevier, vol. 217(2), pages 411-430.
    32. Hoga, Yannick, 2021. "The uncertainty in extreme risk forecasts from covariate-augmented volatility models," International Journal of Forecasting, Elsevier, vol. 37(2), pages 675-686.
    33. Tim Bollerslev & Viktor Todorov & Lai Xu, 2014. "Tail Risk Premia and Return Predictability," CREATES Research Papers 2014-49, Department of Economics and Business Economics, Aarhus University.
    34. F. Lilla, 2016. "High Frequency vs. Daily Resolution: the Economic Value of Forecasting Volatility Models," Working Papers wp1084, Dipartimento Scienze Economiche, Universita' di Bologna.
    35. Linton, Oliver & Whang, Yoon-Jae & Yen, Yu-Min, 2016. "A nonparametric test of a strong leverage hypothesis," Journal of Econometrics, Elsevier, vol. 194(1), pages 153-186.
    36. Nurulhasanah Abdul Rahman & Rafisah Mat Radzi, 2015. "Determinants of Effective Financial Risk Management in Small Business: A Theoretical Framework," Information Management and Business Review, AMH International, vol. 7(2), pages 87-92.
    37. David Happersberger & Harald Lohre & Ingmar Nolte, 2020. "Estimating portfolio risk for tail risk protection strategies," European Financial Management, European Financial Management Association, vol. 26(4), pages 1107-1146, September.
    38. Alfeus, Mesias & Nikitopoulos, Christina Sklibosios, 2022. "Forecasting volatility in commodity markets with long-memory models," Journal of Commodity Markets, Elsevier, vol. 28(C).
    39. Hsuan‐Ling Chang & Yen‐Cheng Chang & Hung‐Wen Cheng & Po‐Hsiang Peng & Kevin Tseng, 2019. "Jump variance risk: Evidence from option valuation and stock returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(7), pages 890-915, July.
    40. Liu, Zhenya & Lu, Shanglin & Li, Bo & Wang, Shixuan, 2023. "Time series momentum and reversal: Intraday information from realized semivariance," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 54-77.
    41. Victor Olkhov, 2021. "To VaR, or Not to VaR, That is the Question," Papers 2101.08559, arXiv.org, revised Oct 2021.
    42. Diebold, Francis X. & Yılmaz, Kamil, 2023. "Reprint of: On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 234(S), pages 70-90.
    43. Symitsi, Efthymia & Symeonidis, Lazaros & Kourtis, Apostolos & Markellos, Raphael, 2018. "Covariance forecasting in equity markets," Journal of Banking & Finance, Elsevier, vol. 96(C), pages 153-168.
    44. Hammadi Zouari, 2022. "On the Effectiveness of Stock Index Futures for Tail Risk Protection," International Journal of Economics and Financial Issues, Econjournals, vol. 12(3), pages 38-52, May.

  26. Boragan Aruoba & Francis X. Diebold & Jeremy Nalewaik & Frank Schorfheide & Dongho Song, 2011. "Improving GDP Measurement: A Forecast Combination Perspective," PIER Working Paper Archive 11-028, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.

    Cited by:

    1. Jeremy J. Nalewaik, 2014. "Missing Variation in the Great Moderation: Lack of Signal Error and OLS Regression," Finance and Economics Discussion Series 2014-27, Board of Governors of the Federal Reserve System (U.S.).
    2. Tomaz Cajner & Leland D. Crane & Ryan A. Decker & Adrian Hamins-Puertolas & Christopher Kurz, 2019. "Improving the Accuracy of Economic Measurement with Multiple Data Sources: The Case of Payroll Employment Data," NBER Chapters, in: Big Data for Twenty-First-Century Economic Statistics, pages 147-170, National Bureau of Economic Research, Inc.
    3. Aruoba, S. Borağan & Diebold, Francis X. & Nalewaik, Jeremy & Schorfheide, Frank & Song, Dongho, 2016. "Improving GDP measurement: A measurement-error perspective," Journal of Econometrics, Elsevier, vol. 191(2), pages 384-397.
    4. Tom Stark, 2014. "Real-time performance of GDPplus and alternative model-based measures of GDP: 2005—2014," Research Rap Special Report, Federal Reserve Bank of Philadelphia, issue Nov.
    5. Francis X. Diebold & Minchul Shin, 2017. "Beating the Simple Average: Egalitarian LASSO for Combining Economic Forecasts," PIER Working Paper Archive 17-017, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 20 Aug 2017.
    6. Diebold, Francis X. & Shin, Minchul, 2019. "Machine learning for regularized survey forecast combination: Partially-egalitarian LASSO and its derivatives," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1679-1691.
    7. Cobb, Marcus P A, 2018. "Improving Underlying Scenarios for Aggregate Forecasts: A Multi-level Combination Approach," MPRA Paper 88593, University Library of Munich, Germany.
    8. James Bishop & Troy Gill & David Lancaster, 2013. "GDP Revisions: Measurement and Implications," RBA Bulletin (Print copy discontinued), Reserve Bank of Australia, pages 11-22, March.
    9. Mary C. Daly & John G. Fernald & Òscar Jordà & Fernanda Nechio, 2013. "Shocks and Adjustments," Working Paper Series 2013-32, Federal Reserve Bank of San Francisco.
    10. Marius Cristian Acatrinei, 2020. "Financial stability indicator for non-banking markets," Journal of Financial Studies, Institute of Financial Studies, vol. 9(5), pages 3-9, November.
    11. Jan P.A.M. Jacobs & Samad Sarferaz & Simon van Norden & Jan-Egbert Sturm, 2013. "Modeling Multivariate Data Revisions," CIRANO Working Papers 2013s-44, CIRANO.

  27. Francis X. Diebold & Kamil Yilmaz, 2011. "On the Network Topology of Variance Decompositions: Measuring the Connectedness of Financial Firms," Koç University-TUSIAD Economic Research Forum Working Papers 1124, Koc University-TUSIAD Economic Research Forum.

    Cited by:

    1. Qiao, Sen & Guo, Zi Xin & Tao, Zhang & Ren, Zheng Yu, 2023. "Analyzing the network structure of risk transmission among renewable, non-renewable energy and carbon markets," Renewable Energy, Elsevier, vol. 209(C), pages 206-217.
    2. Colin Ellis, 2020. "Are Corporate Bond Defaults Contagious across Sectors?," IJFS, MDPI, vol. 8(1), pages 1-17, January.
    3. Alexander Falter & Dennis Wesselbaum, 2018. "Correlated shocks in estimated DSGE models," Economics Bulletin, AccessEcon, vol. 38(4), pages 2026-2036.
    4. Ioannis Chatziantoniou & David Gabauer, 2019. "EMU-Risk Synchronisation and Financial Fragility Through the Prism of Dynamic Connectedness," Working Papers in Economics & Finance 2019-07, University of Portsmouth, Portsmouth Business School, Economics and Finance Subject Group.
    5. Kamal, Javed Bin & Hassan, M. Kabir, 2022. "Asymmetric connectedness between cryptocurrency environment attention index and green assets," The Journal of Economic Asymmetries, Elsevier, vol. 25(C).
    6. Bouri, Elie & Cepni, Oguzhan & Gabauer, David & Gupta, Rangan, 2021. "Return connectedness across asset classes around the COVID-19 outbreak," International Review of Financial Analysis, Elsevier, vol. 73(C).
    7. Geng, Jiang-Bo & Du, Ya-Juan & Ji, Qiang & Zhang, Dayong, 2021. "Modeling return and volatility spillover networks of global new energy companies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    8. Rogelio V. Mercado Jr. & Shanty Noviantie, 2019. "Financial Flows Centrality: Empirical Evidence using Bilateral Capital Flows," Working Papers wp38, South East Asian Central Banks (SEACEN) Research and Training Centre.
    9. Lo Cascio, Iolanda, 2021. "A wavelet analysis of the ripple effect in UK regional housing markets," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 1093-1105.
    10. Singh, Jitendra & Ahmad, Wasim & Mishra, Anil, 2019. "Coherence, connectedness and dynamic hedging effectiveness between emerging markets equities and commodity index funds," Resources Policy, Elsevier, vol. 61(C), pages 441-460.
    11. Ki-Hong Choi & Ron P. McIver & Salvatore Ferraro & Lei Xu & Sang Hoon Kang, 2021. "Dynamic volatility spillover and network connectedness across ASX sector markets," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 45(4), pages 677-691, October.
    12. Shi, Huai-Long & Zhou, Wei-Xing, 2022. "Factor volatility spillover and its implications on factor premia," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 80(C).
    13. Dai, Zhifeng & Zhu, Haoyang & Zhang, Xinhua, 2022. "Dynamic spillover effects and portfolio strategies between crude oil, gold and Chinese stock markets related to new energy vehicle," Energy Economics, Elsevier, vol. 109(C).
    14. Okorie, David Iheke & Lin, Boqiang, 2022. "Givers never lack: Nigerian oil & gas asymmetric network analyses," Energy Economics, Elsevier, vol. 108(C).
    15. Zhang, Xiaoyuan & Zhang, Tianqi, 2022. "Dynamic credit contagion and aggregate loss in networks," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    16. Nguyen, Linh Hoang & Chevapatrakul, Thanaset & Yao, Kai, 2020. "Investigating tail-risk dependence in the cryptocurrency markets: A LASSO quantile regression approach," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 333-355.
    17. Assaf, Ata & Charif, Husni & Mokni, Khaled, 2021. "Dynamic connectedness between uncertainty and energy markets: Do investor sentiments matter?," Resources Policy, Elsevier, vol. 72(C).
    18. Xu, Xiu & Wang, Weining & Shin, Yongcheol, 2020. "Dynamic Spatial Network Quantile Autoregression," IRTG 1792 Discussion Papers 2020-024, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    19. Das, Debojyoti & Bhatia, Vaneet & Kumar, Surya Bhushan & Basu, Sankarshan, 2022. "Do precious metals hedge crude oil volatility jumps?," International Review of Financial Analysis, Elsevier, vol. 83(C).
    20. Lv, Fei & Yang, Chen & Fang, Libing, 2020. "Do the crude oil futures of the Shanghai International Energy Exchange improve asset allocation of Chinese petrochemical-related stocks?," International Review of Financial Analysis, Elsevier, vol. 71(C).
    21. Nicole Branger & Patrick Konermann & Christoph Meinerding & Christian Schlag, 2021. "Equilibrium Asset Pricing in Directed Networks [Risk premia and term premia in general equilibrium]," Review of Finance, European Finance Association, vol. 25(3), pages 777-818.
    22. Malik, Farooq & Umar, Zaghum, 2019. "Dynamic connectedness of oil price shocks and exchange rates," Energy Economics, Elsevier, vol. 84(C).
    23. Shakya, Shasta, 2022. "Geographic networks and spillovers between banks," Journal of Corporate Finance, Elsevier, vol. 77(C).
    24. Elsayed, Ahmed H. & Gozgor, Giray & Lau, Chi Keung Marco, 2022. "Risk transmissions between bitcoin and traditional financial assets during the COVID-19 era: The role of global uncertainties," International Review of Financial Analysis, Elsevier, vol. 81(C).
    25. Ariana Paola Cortés Ángel & Mustafa Hakan Eratalay, 2022. "Deep diving into the S&P Europe 350 index network and its reaction to COVID-19," Journal of Computational Social Science, Springer, vol. 5(2), pages 1343-1408, November.
    26. Lyócsa, Štefan & Výrost, Tomáš & Baumöhl, Eduard, 2019. "Return spillovers around the globe: A network approach," Economic Modelling, Elsevier, vol. 77(C), pages 133-146.
    27. Wang, Yong & Li, Fang & Dou, Jiali, 2023. "Revisiting resources allocation for slow-moving economies: A way forward for low-income economies," Resources Policy, Elsevier, vol. 82(C).
    28. Lovcha, Yuliya & Pérez Laborda, Àlex & Sikora, Iryna, 2019. "The Determinants of CO2 prices in the EU ETS System," Working Papers 2072/376031, Universitat Rovira i Virgili, Department of Economics.
    29. Mohamed Beraich & Karim Amzile & Jaouad Laamire & Omar Zirari & Mohamed Amine Fadali, 2022. "Volatility Spillover Effects of the US, European and Chinese Financial Markets in the Context of the Russia–Ukraine Conflict," IJFS, MDPI, vol. 10(4), pages 1-18, October.
    30. Paolo Giudici & Laura Parisi, 2016. "Bail in or Bail out? The Atlante example from a systemic risk perspective," DEM Working Papers Series 124, University of Pavia, Department of Economics and Management.
    31. Joshua C. C. Chan & Xuewen Yu, 2022. "Fast and Accurate Variational Inference for Large Bayesian VARs with Stochastic Volatility," Papers 2206.08438, arXiv.org.
    32. Hung Do & Rabindra Nepal & Tooraj Jamasb, 2020. "Electricity market integration, decarbonisation and security of supply: Dynamic volatility connectedness in the Irish and Great Britain markets," CAMA Working Papers 2020-42, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    33. Kathleen Weiss Hanley & Gerard Hoberg, 2019. "Dynamic Interpretation of Emerging Risks in the Financial Sector," The Review of Financial Studies, Society for Financial Studies, vol. 32(12), pages 4543-4603.
    34. Christian Manicaro & Joseph Falzon, 2017. "Hedge funds risk and connectedness," Journal of Asset Management, Palgrave Macmillan, vol. 18(4), pages 295-316, July.
    35. Juncal Cunado & David Gabauer & Rangan Gupta, 2021. "Realized Volatility Spillovers between Energy and Metal Markets: A Time-Varying Connectedness Approach," Working Papers 202180, University of Pretoria, Department of Economics.
    36. Hai-Chuan Xu & Fredj Jawadi & Jie Zhou & Wei-Xing Zhou, 2023. "Quantifying interconnectedness and centrality ranking among financial institutions with TVP-VAR framework," Empirical Economics, Springer, vol. 65(1), pages 93-110, July.
    37. Mensi, Walid & Shafiullah, Muhammad & Vo, Xuan Vinh & Kang, Sang Hoon, 2021. "Volatility spillovers between strategic commodity futures and stock markets and portfolio implications: Evidence from developed and emerging economies," Resources Policy, Elsevier, vol. 71(C).
    38. Dai, Zhifeng & Zhu, Junxin & Zhang, Xinhua, 2022. "Time-frequency connectedness and cross-quantile dependence between crude oil, Chinese commodity market, stock market and investor sentiment," Energy Economics, Elsevier, vol. 114(C).
    39. Eric Jondeau & Michael Rockinger, 2013. "Systemic Risk in Europe," Global Credit Review (GCR), World Scientific Publishing Co. Pte. Ltd., vol. 3(01), pages 1-6.
    40. Bauwens, Luc & Chevillon, Guillaume & Laurent, Sébastien, 2023. "We modeled long memory with just one lag!," Journal of Econometrics, Elsevier, vol. 236(1).
    41. García, Javier Sánchez & Rambaud, Salvador Cruz, 2023. "Macrofinancial determinants of volatility transmission in a network of European sovereign debt markets," Finance Research Letters, Elsevier, vol. 53(C).
    42. Helena Chulià & Jorge M. Uribe, 2018. "“Together forever? Good and bad market volatility shocks and international consumption risk sharing: A tale of a sign”," IREA Working Papers 201809, University of Barcelona, Research Institute of Applied Economics, revised May 2018.
    43. Henry, Jérôme & Zimmermann, Maik & Leber, Miha & Kolb, Markus & Grodzicki, Maciej & Amzallag, Adrien & Vouldis, Angelos & Hałaj, Grzegorz & Pancaro, Cosimo & Gross, Marco & Baudino, Patrizia & Sydow, , 2013. "A macro stress testing framework for assessing systemic risks in the banking sector," Occasional Paper Series 152, European Central Bank.
    44. International Monetary Fund, 2016. "Ireland: Financial Sector Assessment Program: Technical Note-Stress Testing the Banking System," IMF Staff Country Reports 2016/315, International Monetary Fund.
    45. Mert Demirer & Francis X. Diebold & Laura Liu & Kamil Yilmaz, 2015. "Estimating Global Bank Network Connectedness," PIER Working Paper Archive 15-025, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 25 Jul 2015.
    46. Chen, Cathy Yi-Hsuan & Härdle, Wolfgang Karl & Klochkov, Yegor, 2022. "SONIC: SOcial Network analysis with Influencers and Communities," Journal of Econometrics, Elsevier, vol. 228(2), pages 177-220.
    47. Zheng, Jinlin & Wen, Baoyu & Jiang, Yaohui & Wang, Xiaohan & Shen, Yue, 2023. "Risk spillovers across geopolitical risk and global financial markets," Energy Economics, Elsevier, vol. 127(PA).
    48. Yousaf, Imran & Youssef, Manel & Goodell, John W., 2022. "Quantile connectedness between sentiment and financial markets: Evidence from the S&P 500 twitter sentiment index," International Review of Financial Analysis, Elsevier, vol. 83(C).
    49. Atil, Ahmed & Nawaz, Kishwar & Lahiani, Amine & Roubaud, David, 2020. "Are natural resources a blessing or a curse for financial development in Pakistan? The importance of oil prices, economic growth and economic globalization," Resources Policy, Elsevier, vol. 67(C).
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    3. Ioannis Chatziantoniou & David Gabauer, 2019. "EMU-Risk Synchronisation and Financial Fragility Through the Prism of Dynamic Connectedness," Working Papers in Economics & Finance 2019-07, University of Portsmouth, Portsmouth Business School, Economics and Finance Subject Group.
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    7. Hasan, Mudassar & Arif, Muhammad & Naeem, Muhammad Abubakr & Ngo, Quang-Thanh & Taghizadeh–Hesary, Farhad, 2021. "Time-frequency connectedness between Asian electricity sectors," Economic Analysis and Policy, Elsevier, vol. 69(C), pages 208-224.
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    1737. Balli, Faruk & Hasan, Mudassar & Ozer-Balli, Hatice & Gregory-Allen, Russell, 2021. "Why do U.S. uncertainties drive stock market spillovers? International evidence," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 288-301.
    1738. Kang, Sang Hoon & McIver, Ron & Yoon, Seong-Min, 2017. "Dynamic spillover effects among crude oil, precious metal, and agricultural commodity futures markets," Energy Economics, Elsevier, vol. 62(C), pages 19-32.
    1739. Apostolakis, Georgios N. & Giannellis, Nikolaos & Papadopoulos, Athanasios P., 2019. "Financial stress and asymmetric shocks transmission within the Eurozone. How fragile is the common monetary policy?," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    1740. Evrim Mandaci, Pınar & Azimli, Asil & Mandaci, Nazif, 2023. "The impact of geopolitical risks on connectedness among natural resource commodities: A quantile vector autoregressive approach," Resources Policy, Elsevier, vol. 85(PA).
    1741. Barbaglia, Luca & Croux, Christophe & Wilms, Ines, 2020. "Volatility spillovers in commodity markets: A large t-vector autoregressive approach," Energy Economics, Elsevier, vol. 85(C).
    1742. Jouini, Jamel & Harrathi, Nizar, 2014. "Revisiting the shock and volatility transmissions among GCC stock and oil markets: A further investigation," Economic Modelling, Elsevier, vol. 38(C), pages 486-494.
    1743. Mensi, Walid & Hernandez, Jose Arroeola & Yoon, Seong-Min & Vo, Xuan Vinh & Kang, Sang Hoon, 2021. "Spillovers and connectedness between major precious metals and major currency markets: The role of frequency factor," International Review of Financial Analysis, Elsevier, vol. 74(C).
    1744. Lovcha, Yuliya & Pérez Laborda, Àlex, 2018. "Volatility Spillovers in a Long-Memory VAR: an Application to Energy Futures Returns," Working Papers 2072/307362, Universitat Rovira i Virgili, Department of Economics.
    1745. Bajo-Rubio, Oscar & Berke, Burcu & McMillan, David, 2017. "The behaviour of asset return and volatility spillovers in Turkey: A tale of two crises," Research in International Business and Finance, Elsevier, vol. 41(C), pages 577-589.
    1746. Do, A. & Powell, R. & Yong, J. & Singh, A., 2020. "Time-varying asymmetric volatility spillover between global markets and China’s A, B and H-shares using EGARCH and DCC-EGARCH models," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    1747. Qian Wang & Yu Wei & Yifeng Zhang & Yuntong Liu, 2023. "Evaluating the Safe-Haven Abilities of Bitcoin and Gold for Crude Oil Market: Evidence During the COVID-19 Pandemic," Evaluation Review, , vol. 47(3), pages 391-432, June.
    1748. Maria Elena Giuli & Alessandro Spelta, 2023. "Wasserstein barycenter regression for estimating the joint dynamics of renewable and fossil fuel energy indices," Computational Management Science, Springer, vol. 20(1), pages 1-17, December.
    1749. Al-Shboul, Mohammad & Assaf, Ata & Mokni, Khaled, 2022. "When bitcoin lost its position: Cryptocurrency uncertainty and the dynamic spillover among cryptocurrencies before and during the COVID-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 83(C).
    1750. Zhang, Dayong & Lei, Lei & Ji, Qiang & Kutan, Ali M., 2019. "Economic policy uncertainty in the US and China and their impact on the global markets," Economic Modelling, Elsevier, vol. 79(C), pages 47-56.
    1751. Yaming Ma & Ziwei Wang & Feng He, 2022. "How do economic policy uncertainties affect stock market volatility? Evidence from G7 countries," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 2303-2325, April.
    1752. Li, Yanshuang & Zhuang, Xintian & Wang, Jian, 2021. "Analysis of the cross-region risk contagion effect in stock market based on volatility spillover networks: Evidence from China," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    1753. Angelini Giovanni & Costantini Mauro & Easaw Joshy, 2024. "Estimating uncertainty spillover effects across euro area using a regime dependent VAR model," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 28(1), pages 39-59, February.
    1754. Dey, Shubhasis & Sampath, Aravind, 2020. "Returns, volatility and spillover – A paradigm shift in India?," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    1755. Ramiro Losada & Ricardo Laborda, 2020. "La interconexión en las instituciones de inversión colectiva no alternativas y el riesgo sistémico," CNMV Documentos de Trabajo CNMV Documentos de Trabaj, CNMV- Comisión Nacional del Mercado de Valores - Departamento de Estudios y Estadísticas.
    1756. David Cronin, 2022. "Inflation Shocks – Do Monetary Variables Matter?," Economic Papers, The Economic Society of Australia, vol. 41(2), pages 182-188, June.

  29. S. Boragan Aruoba & Francis X. Diebold & M. Ayhan Kose & Marco E. Terrones, 2010. "Globalization, the Business Cycle, and Macroeconomic Monitoring," NBER Working Papers 16264, National Bureau of Economic Research, Inc.

    Cited by:

    1. Mr. Maxym Kryshko, 2011. "Data-Rich DSGE and Dynamic Factor Models," IMF Working Papers 2011/216, International Monetary Fund.
    2. Peter C. B. Phillips & Zhentao Shi, 2021. "Boosting: Why You Can Use The Hp Filter," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 62(2), pages 521-570, May.
    3. Diebold, Francis X. & Yilmaz, Kamil, 2015. "Financial and Macroeconomic Connectedness: A Network Approach to Measurement and Monitoring," OUP Catalogue, Oxford University Press, number 9780199338306.
    4. Gitanjali Kumar, 2013. "High-Frequency Real Economic Activity Indicator for Canada," Staff Working Papers 13-42, Bank of Canada.
    5. Rodriguez, Diego & Gonzalez, Andres & Fernandez, Andres, 2015. "Sharing a Ride on the Commodities Roller Coaster: Common Factors in Business Cycles of Emerging Economies," IDB Publications (Working Papers) 7382, Inter-American Development Bank.
    6. Francis X. Diebold & Kamil Yilmaz, 2013. "Measuring the Dynamics of Global Business Cycle Connectedness," PIER Working Paper Archive 13-070, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    7. Ron Alquist & Olivier Coibion, 2014. "Commodity Price Co-Movement and Global Economic Activity," Staff Working Papers 14-32, Bank of Canada.
    8. David Matesanz Gomez & Guillermo J. Ortega & Benno Torgler, 2012. "Synchronization and Diversity in Business Cycles: A Network Approach Applied to the European Union," CREMA Working Paper Series 2012-01, Center for Research in Economics, Management and the Arts (CREMA).
    9. Peter C.B. Phillips & Zhentao Shi, 2019. "Boosting the Hodrick-Prescott Filter," Cowles Foundation Discussion Papers 2192, Cowles Foundation for Research in Economics, Yale University.
    10. Lahiri, Kajal & Zhao, Yongchen, 2019. "International propagation of shocks: A dynamic factor model using survey forecasts," International Journal of Forecasting, Elsevier, vol. 35(3), pages 929-947.
    11. Camacho, Maximo & Martinez-Martin, Jaime, 2015. "Monitoring the world business cycle," Economic Modelling, Elsevier, vol. 51(C), pages 617-625.
    12. Pablo A. Cuba-Borda & Alexander Mechanick & Andrea Raffo, 2018. "Monitoring the World Economy: A Global Conditions Index," IFDP Notes 2018-06-15, Board of Governors of the Federal Reserve System (U.S.).
    13. Alessandro Borin & Riccardo Cristadoro & Roberto Golinelli & Giuseppe Parigi, 2012. "Forecasting world output: the rising importance of emerging economies," Temi di discussione (Economic working papers) 853, Bank of Italy, Economic Research and International Relations Area.
    14. Choi, Sung Hoon & Kim, Donggyu, 2023. "Large volatility matrix analysis using global and national factor models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1917-1933.
    15. S. Boragan Aruoba & Cagri Sarikaya, 2013. "A Real Economic Activity Indicator for Turkey," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 13(1), pages 15-29.
    16. Roberto Golinelli & Giuseppe Parigi, 2013. "Tracking world trade and GDP in real time," Temi di discussione (Economic working papers) 920, Bank of Italy, Economic Research and International Relations Area.
    17. In Choi & Dukpa Kim & Yun Jung Kim & Noh-Sun Kwark, 2016. "A Multilevel Factor Model: Identification, Asymptotic Theory and Applications," Working Papers 1609, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
    18. Chiu Adrian & Wieladek Tomasz, 2013. "Is the “Great Recession” really so different from the past?," The B.E. Journal of Macroeconomics, De Gruyter, vol. 13(1), pages 1-48, October.
    19. Jason Angelopoulos & Costas I. Chlomoudis, 2017. "A Generalized Dynamic Factor Model for the U.S. Port Sector," SPOUDAI Journal of Economics and Business, SPOUDAI Journal of Economics and Business, University of Piraeus, vol. 67(1), pages 22-37, January-M.
    20. David Matesanz Gomez & Guillermo J. Ortega & Benno Torgler, 2011. "Measuring globalization: A hierarchical network approach," CREMA Working Paper Series 2011-11, Center for Research in Economics, Management and the Arts (CREMA).
    21. Mr. Ron Alquist & Mr. Olivier Coibion, 2013. "The Comovement in Commodity Prices: Sources and Implications," IMF Working Papers 2013/140, International Monetary Fund.
    22. Camacho, Maximo & Perez-Quiros, Gabriel & Pacce, Matías, 2020. "Spillover effects in international business cycles," Working Paper Series 2484, European Central Bank.

  30. S. Boragan Aruoba & Francis X. Diebold, 2010. "Real-Time Macroeconomic Monitoring: Real Activity, Inflation, and Interactions," PIER Working Paper Archive 10-002, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.

    Cited by:

    1. Mr. Maxym Kryshko, 2011. "Data-Rich DSGE and Dynamic Factor Models," IMF Working Papers 2011/216, International Monetary Fund.
    2. Jaime Martínez-Martín & Elena Rusticelli, 2020. "Keeping track of global trade in real time," Working Papers 2019, Banco de España.
    3. Helena Rodríguez, 2014. "Un indicador de la evolución del PIB uruguayo en tiempo real," Documentos de trabajo 2014009, Banco Central del Uruguay.
    4. Peter C. B. Phillips & Zhentao Shi, 2021. "Boosting: Why You Can Use The Hp Filter," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 62(2), pages 521-570, May.
    5. Diebold, Francis X. & Yilmaz, Kamil, 2015. "Financial and Macroeconomic Connectedness: A Network Approach to Measurement and Monitoring," OUP Catalogue, Oxford University Press, number 9780199338306.
    6. Poncela, Pilar & Ruiz, Esther & Miranda, Karen, 2021. "Factor extraction using Kalman filter and smoothing: This is not just another survey," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1399-1425.
    7. Tony Chernis & Calista Cheung & Gabriella Velasco, 2017. "A Three-Frequency Dynamic Factor Model for Nowcasting Canadian Provincial GDP Growth," Discussion Papers 17-8, Bank of Canada.
    8. Andrea Gazzani & Fabrizio Venditti & Giovanni Veronese, 2024. "Oil price shocks in real time," Temi di discussione (Economic working papers) 1448, Bank of Italy, Economic Research and International Relations Area.
    9. Tuhkuri, Joonas, 2016. "Forecasting Unemployment with Google Searches," ETLA Working Papers 35, The Research Institute of the Finnish Economy.
    10. Bhattacharya, Rudrani & Kapoor, Mrigankshi, 2020. "Forecasting Consumer Price Index Inflation in India: Vector Error Correction Mechanism Vs. Dynamic Factor Model Approach for Non-Stationary Time Series," Working Papers 20/323, National Institute of Public Finance and Policy.
    11. Chauvet, Marcelle & Potter, Simon, 2013. "Forecasting Output," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 141-194, Elsevier.
    12. Máximo Camacho & Danilo Leiva-León & Gabriel Pérez-Quiros, 2015. "Country Shocks, Monetary Policy Expectations and ECB Decisions. A Dynamic Non-Linear Approach," Working Papers Central Bank of Chile 764, Central Bank of Chile.
    13. Kihwan Kim & Hyun Hak Kim & Norman R. Swanson, 2023. "Mixing mixed frequency and diffusion indices in good times and in bad: an assessment based on historical data around the great recession of 2008," Empirical Economics, Springer, vol. 64(3), pages 1421-1469, March.
    14. Aruoba, S. Borağan & Diebold, Francis X. & Nalewaik, Jeremy & Schorfheide, Frank & Song, Dongho, 2016. "Improving GDP measurement: A measurement-error perspective," Journal of Econometrics, Elsevier, vol. 191(2), pages 384-397.
    15. Leiva-Leon Danilo, 2014. "Real vs. nominal cycles: a multistate Markov-switching bi-factor approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 18(5), pages 1-24, December.
    16. Stona, Filipe & Morais, Igor A.C. & Triches, Divanildo, 2018. "Economic dynamics during periods of financial stress: Evidences from Brazil," International Review of Economics & Finance, Elsevier, vol. 55(C), pages 130-144.
    17. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2011. "Financial Risk Measurement for Financial Risk Management," CREATES Research Papers 2011-37, Department of Economics and Business Economics, Aarhus University.
    18. Abel Rodríguez Tirado & Marcelo Delajara & Federico Hernández Álvarez, 2016. "Nowcasting Mexico’s Short-Term GDP Growth in Real-Time: A Factor Model versus Professional Forecasters," Economía Journal, The Latin American and Caribbean Economic Association - LACEA, vol. 0(Fall 2016), pages 167-182, October.
    19. Peter C.B. Phillips & Zhentao Shi, 2019. "Boosting the Hodrick-Prescott Filter," Cowles Foundation Discussion Papers 2192, Cowles Foundation for Research in Economics, Yale University.
    20. Evren Erdogan Cosar & Sevim Kosem & Cagri Sarikaya, 2013. "Do We Really Need Filters In Estimating Output Gap? : Evidence From Turkey," Working Papers 1333, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    21. Germán López, 2015. "Forecast Accuracy of Small and Large Scale Dynamic Factor Models in Developing Economies," Working Papers. Serie AD 2015-03, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    22. Maximo Camacho & Gabriel Perez-Quiros & Pilar Poncela, 2012. "Markov-switching dynamic factor models in real time," Working Papers 1205, Banco de España.
    23. Boragan Aruoba & Francis X. Diebold & Jeremy Nalewaik & Frank Schorfheide & Dongho Song, 2011. "Improving GDP Measurement: A Forecast Combination Perspective," PIER Working Paper Archive 11-028, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    24. Camacho, Maximo & Lopez-Buenache, German, 2023. "Factor models for large and incomplete data sets with unknown group structure," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1205-1220.
    25. Camba-Méndez, Gonzalo & Kapetanios, George & Papailias, Fotis & Weale, Martin R., 2015. "An automatic leading indicator, variable reduction and variable selection methods using small and large datasets: Forecasting the industrial production growth for euro area economies," Working Paper Series 1773, European Central Bank.
    26. Chen, Ji & Yang, Xinglin & Liu, Xiliang, 2022. "Learning, disagreement and inflation forecasting," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    27. Zhang, Wei & He, Jie & Ge, Chanyuan & Xue, Rui, 2022. "Real-time macroeconomic monitoring using mixed frequency data: Evidence from China," Economic Modelling, Elsevier, vol. 117(C).
    28. Maximo Camacho & Yuliya Lovcha & Gabriel Perez-Quiros, 2012. "Can we use seasonally adjusted indicators in dynamic factor models?," Working Papers 1235, Banco de España.
    29. Camacho Maximo & Lovcha Yuliya & Quiros Gabriel Perez, 2015. "Can we use seasonally adjusted variables in dynamic factor models?," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(3), pages 377-391, June.
    30. Valentina Raponi & Cecilia Frale, 2014. "Revisions in official data and forecasting," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 23(3), pages 451-472, August.
    31. William Barnett & Marcelle Chauvetz & Danilo Leiva-Leonx, 2014. "Real-Time Nowcasting Nominal GDP Under Structural Break," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201313, University of Kansas, Department of Economics, revised Feb 2014.
    32. Maximo Camacho & Jaime Martíinez-Martin, 2012. "Real-time forecasting US GDP from small-scale factor models," Working Papers 1210, BBVA Bank, Economic Research Department.
    33. Madalina-Gabriela Anghel & Georgeta Lixandru & Marius Popovici & Alina – Georgiana Solomon & Emilia Stanciu, 2017. "Theoretical Elements on the Use of Price Indices for Inflation Measurement," International Journal of Academic Research in Accounting, Finance and Management Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Accounting, Finance and Management Sciences, vol. 7(3), pages 38-47, July.
    34. Francis X. Diebold, 2020. "Real-Time Real Economic Activity: Exiting the Great Recession and Entering the Pandemic Recession," NBER Working Papers 27482, National Bureau of Economic Research, Inc.
    35. Berger, Dave & Pukthuanthong, Kuntara, 2016. "Fragility, stress, and market returns," Journal of Banking & Finance, Elsevier, vol. 62(C), pages 152-163.
    36. Constantin Anghelache & Madalina-Gabriela Anghel & Alina-Georgiana Solomon, 2017. "National Accounts System: Source of Information in Macroeconomic Forecast," International Journal of Academic Research in Accounting, Finance and Management Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Accounting, Finance and Management Sciences, vol. 7(2), pages 76-82, April.
    37. Mr. Troy D Matheson, 2011. "New Indicators for Tracking Growth in Real Time," IMF Working Papers 2011/043, International Monetary Fund.
    38. Florin Paul Costel LILEA & Andreea – Ioana MARINESCU, 2017. "Macroeconomic Forecast Models – Concepts And Theoretical Notions," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 65(6), pages 118-123, June.
    39. Nicholas Taylor, 2014. "Economic forecast quality: information timeliness and data vintage effects," Empirical Economics, Springer, vol. 46(1), pages 145-174, February.
    40. Jonas Krampe & Luca Margaritella, 2021. "Factor Models with Sparse VAR Idiosyncratic Components," Papers 2112.07149, arXiv.org, revised May 2022.
    41. Serena Ng & Jonathan H. Wright, 2013. "Facts and Challenges from the Great Recession for Forecasting and Macroeconomic Modeling," NBER Working Papers 19469, National Bureau of Economic Research, Inc.
    42. Constantin ANGHELACHE & Madalina-Gabriela ANGHEL & Tudor SAMSON & Radu STOICA, 2017. "Methods And Techniques For Preparing Forecasts," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 65(4), pages 26-36, April.
    43. Foroni, Claudia & Marcellino, Massimiliano, 2014. "A comparison of mixed frequency approaches for nowcasting Euro area macroeconomic aggregates," International Journal of Forecasting, Elsevier, vol. 30(3), pages 554-568.
    44. William A. Barnett & Marcelle Chauvet & Danilo Leiva-Leon, 2014. "Real-Time Nowcasting of Nominal GDP Under Structural Breaks," Staff Working Papers 14-39, Bank of Canada.
    45. Cremers, Martijn & Fleckenstein, Matthias & Gandhi, Priyank, 2021. "Treasury yield implied volatility and real activity," Journal of Financial Economics, Elsevier, vol. 140(2), pages 412-435.
    46. Coble, David & Pincheira, Pablo, 2017. "Nowcasting Building Permits with Google Trends," MPRA Paper 76514, University Library of Munich, Germany.
    47. Barnett, William A. & Chauvet, Marcelle & Leiva-Leon, Danilo, 2016. "Real-time nowcasting of nominal GDP with structural breaks," Journal of Econometrics, Elsevier, vol. 191(2), pages 312-324.
    48. David Coble & Pablo Pincheira, 2021. "Forecasting building permits with Google Trends," Empirical Economics, Springer, vol. 61(6), pages 3315-3345, December.
    49. Rocio Alvarez & Maximo Camacho & Gabriel Perez-Quiros, 2012. "Finite sample performance of small versus large scale dynamic factor models," Working Papers 1204, Banco de España.
    50. Monica Defend & Aleksey Min & Lorenzo Portelli & Franz Ramsauer & Francesco Sandrini & Rudi Zagst, 2021. "Quantifying Drivers of Forecasted Returns Using Approximate Dynamic Factor Models for Mixed-Frequency Panel Data," Forecasting, MDPI, vol. 3(1), pages 1-35, February.
    51. Baskot, Bojan & Orsag, Silvije & Mikerevic, Dejan, 2018. "Yield Curve In Bosnia And Herzegovina: Financial And Macroeconomic Framework," UTMS Journal of Economics, University of Tourism and Management, Skopje, Macedonia, vol. 9(1), pages 1-15.
    52. Tuhkuri, Joonas, 2016. "ETLAnow: A Model for Forecasting with Big Data – Forecasting Unemployment with Google Searches in Europe," ETLA Reports 54, The Research Institute of the Finnish Economy.
    53. Camacho, Maximo & Perez-Quiros, Gabriel & Pacce, Matías, 2020. "Spillover effects in international business cycles," Working Paper Series 2484, European Central Bank.
    54. Florin Paul Costel LILEA & Aurelian DIACONU & Radu Titus MARINESCU & Gyorgy BODO, 2017. "Structural Methods Used In Forecasting Studies," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 65(4), pages 66-74, April.
    55. Alvarez, Rocio & Camacho, Maximo & Perez-Quiros, Gabriel, 2016. "Aggregate versus disaggregate information in dynamic factor models," International Journal of Forecasting, Elsevier, vol. 32(3), pages 680-694.
    56. Andrzej Wojtyna, 2013. "Kontrowersje wokół charakteru ożywienia po kryzysie finansowym i recesji," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 11-12, pages 5-21.
    57. Francis X. Diebold, 2020. "Real-Time Real Economic Activity: Entering and Exiting the Pandemic Recession of 2020," Papers 2006.15183, arXiv.org, revised Jan 2022.
    58. Kihwan Kim & Norman Swanson, 2013. "Diffusion Index Model Specification and Estimation Using Mixed Frequency Datasets," Departmental Working Papers 201315, Rutgers University, Department of Economics.
    59. Alexis Flageollet & Hamza Bahaji, 2016. "Monetary Policy and Risk-Based Asset Allocation," Open Economies Review, Springer, vol. 27(5), pages 851-870, November.
    60. Marcella Lucchetta & Mr. Gianni De Nicolo, 2012. "Systemic Real and Financial Risks: Measurement, Forecasting, and Stress Testing," IMF Working Papers 2012/058, International Monetary Fund.

  31. Francis X. Diebold & Georg H. Strasser, 2008. "On the Correlation Structure of Microstructure Noise: A Financial Economic Approach," Boston College Working Papers in Economics 693, Boston College Department of Economics, revised 24 Apr 2012.

    Cited by:

    1. Victor Olkhov, 2022. "Market-Based Price Autocorrelation," Papers 2202.09323, arXiv.org, revised Feb 2024.
    2. Rasmus Tangsgaard Varneskov, 2011. "Flat-Top Realized Kernel Estimation of Quadratic Covariation with Non-Synchronous and Noisy Asset Prices," CREATES Research Papers 2011-35, Department of Economics and Business Economics, Aarhus University.
    3. Bollerslev, Tim & Medeiros, Marcelo C. & Patton, Andrew J. & Quaedvlieg, Rogier, 2022. "From zero to hero: Realized partial (co)variances," Journal of Econometrics, Elsevier, vol. 231(2), pages 348-360.
    4. Shrestha, Keshab & Philip, Sheena & Peranginangin, Yessy, 2020. "Contributions of Crude Oil Exchange Traded Funds in Price Discovery Process," American Business Review, Pompea College of Business, University of New Haven, vol. 23(2), pages 393-407, November.
    5. Clinet, Simon & Potiron, Yoann, 2019. "Testing if the market microstructure noise is fully explained by the informational content of some variables from the limit order book," Journal of Econometrics, Elsevier, vol. 209(2), pages 289-337.
    6. Christensen, Kim & Oomen, Roel C.A. & Podolskij, Mark, 2014. "Fact or friction: Jumps at ultra high frequency," Journal of Financial Economics, Elsevier, vol. 114(3), pages 576-599.
    7. Li, Yifan & Nolte, Ingmar & Vasios, Michalis & Voev, Valeri & Xu, Qi, 2022. "Weighted Least Squares Realized Covariation Estimation," Journal of Banking & Finance, Elsevier, vol. 137(C).
    8. Zheng, Chengli & Su, Kuangxi & Yao, Yinhong, 2021. "Hedging futures performance with denoising and noise-assisted strategies," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    9. Kevin Sheppard & Lily Liu & Andrew J. Patton, 2013. "Does Anything Beat 5-Minute RV? A Comparison of Realized Measures Across Multiple Asset Classes," Economics Series Working Papers 645, University of Oxford, Department of Economics.
    10. Chu, Gang & Zhang, Yongjie & Zhang, Xiaotao, 2021. "An analysis of impact of cancellation activity on market quality: Evidence from China," Economic Modelling, Elsevier, vol. 102(C).
    11. Eric Jondeau & Jérôme Lahaye & Michael Rockinger, 2013. "Estimating the Price Impact of Trades in an High-Frequency Microstructure Model with Jumps," Swiss Finance Institute Research Paper Series 13-47, Swiss Finance Institute, revised Feb 2016.
    12. Simon Clinet & Yoann Potiron, 2017. "Estimation for high-frequency data under parametric market microstructure noise," Papers 1712.01479, arXiv.org, revised Sep 2020.
    13. Sílvia Gonçalves & Ulrich Hounyo & Nour Meddahi, 2013. "Bootstrap inference for pre-averaged realized volatility based on non-overlapping returns," CREATES Research Papers 2013-07, Department of Economics and Business Economics, Aarhus University.
    14. Bian, Siyu & Serra, Teresa & Garcia, Philip & Irwin, Scott, 2022. "New evidence on market response to public announcements in the presence of microstructure noise," European Journal of Operational Research, Elsevier, vol. 298(2), pages 785-800.
    15. Dong, Yingjie & Tse, Yiu-Kuen, 2017. "On estimating market microstructure noise variance," Economics Letters, Elsevier, vol. 150(C), pages 59-62.
    16. Chaker, Selma, 2017. "On high frequency estimation of the frictionless price: The use of observed liquidity variables," Journal of Econometrics, Elsevier, vol. 201(1), pages 127-143.
    17. Kim Christensen & Mark Podolskij & Nopporn Thamrongrat & Bezirgen Veliyev, 2015. "Inference from high-frequency data: A subsampling approach," CREATES Research Papers 2015-45, Department of Economics and Business Economics, Aarhus University.
    18. Bollerslev, Tim & Meddahi, Nour & Nyawa, Serge, 2019. "High-dimensional multivariate realized volatility estimation," Journal of Econometrics, Elsevier, vol. 212(1), pages 116-136.
    19. Victor Bello Accioly & Beatriz Vaz de Melo Mendes, 2016. "Assessing the Impact of the Realized Range on the (E)GARCH Volatility: Evidence from Brazil," Brazilian Business Review, Fucape Business School, vol. 13(2), pages 1-26, March.
    20. Kim Christensen & Martin Thyrsgaard & Bezirgen Veliyev, 2018. "The realized empirical distribution function of stochastic variance with application to goodness-of-fit testing," CREATES Research Papers 2018-19, Department of Economics and Business Economics, Aarhus University.
    21. Andersen, Torben G. & Archakov, Ilya & Cebiroglu, Gökhan & Hautsch, Nikolaus, 2022. "Local mispricing and microstructural noise: A parametric perspective," Journal of Econometrics, Elsevier, vol. 230(2), pages 510-534.
    22. Boudt, Kris & Raza, Muhammad Wajid & Wauters, Marjan, 2019. "Evaluating the Shariah-compliance of equity portfolios: The weighting method matters," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 406-417.
    23. Yafeng Shi & Tingting Ying & Yanlong Shi & Chunrong Ai, 2020. "A comparison of conditional predictive ability of implied volatility and realized measures in forecasting volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(7), pages 1025-1034, November.
    24. Hounyo, Ulrich, 2017. "Bootstrapping integrated covariance matrix estimators in noisy jump–diffusion models with non-synchronous trading," Journal of Econometrics, Elsevier, vol. 197(1), pages 130-152.
    25. Olkhov, Victor, 2022. "Introduction of the Market-Based Price Autocorrelation," MPRA Paper 112003, University Library of Munich, Germany.
    26. Pierre Chausse & Dinghai Xu, 2012. "GMM Estimation of a Stochastic Volatility Model with Realized Volatility: A Monte Carlo Study," Working Papers 1203, University of Waterloo, Department of Economics, revised May 2012.
    27. Andersen, Torben G. & Cebiroglu, Gökhan & Hautsch, Nikolaus, 2017. "Volatility, information feedback and market microstructure noise: A tale of two regimes," CFS Working Paper Series 569, Center for Financial Studies (CFS).
    28. Olkhov, Victor, 2022. "Price and Payoff Autocorrelations in the Consumption-Based Asset Pricing Model," MPRA Paper 112255, University Library of Munich, Germany.
    29. Selma Chaker, 2013. "Volatility and Liquidity Costs," Staff Working Papers 13-29, Bank of Canada.
    30. Kim Christensen & Roel Oomen & Roberto Renò, 2016. "The Drift Burst Hypothesis," CREATES Research Papers 2016-28, Department of Economics and Business Economics, Aarhus University.
    31. Ulrich Hounyo, 2014. "Bootstrapping integrated covariance matrix estimators in noisy jump-diffusion models with non-synchronous trading," CREATES Research Papers 2014-35, Department of Economics and Business Economics, Aarhus University.
    32. P. Simmons & N. Tantisantiwong, 2014. "Equilibrium moment restrictions on asset returns: normal and crisis periods," The European Journal of Finance, Taylor & Francis Journals, vol. 20(11), pages 1064-1089, November.

  32. Jens H. E. Christensen & Francis X. Diebold & Glenn D. Rudebusch, 2008. "An arbitrage-free generalized Nelson-Siegel term structure model," Working Paper Series 2008-07, Federal Reserve Bank of San Francisco.

    Cited by:

    1. Rafael Barros de Rezende, 2011. "Giving Flexibility to the Nelson-Siegel Class of Term Structure Models," Brazilian Review of Finance, Brazilian Society of Finance, vol. 9(1), pages 27-49.
    2. Martins, Manuel M.F. & Afonso, António, 2010. "Level, slope, curvature of the sovereign yield curve, and fiscal behaviour," Working Paper Series 1276, European Central Bank.
    3. Caldeira, João F. & Moura, Guilherme V. & Santos, André A.P., 2016. "Bond portfolio optimization using dynamic factor models," Journal of Empirical Finance, Elsevier, vol. 37(C), pages 128-158.
    4. Eric Hillebrand & Huiyu Huang & Tae-Hwy Lee & Canlin Li, 2018. "Using the Entire Yield Curve in Forecasting Output and Inflation," Econometrics, MDPI, vol. 6(3), pages 1-27, August.
    5. Mr. Ales Bulir & Mr. Jan Vlcek, 2020. "Monetary Policy Is Not Always Systematic and Data-Driven: Evidence from the Yield Curve," IMF Working Papers 2020/004, International Monetary Fund.
    6. Molenaars, Tomas K. & Reinerink, Nick H. & Hemminga, Marcus A., 2013. "Forecasting the yield curve - Forecast performance of the dynamic Nelson-Siegel model from 1971 to 2008," MPRA Paper 61862, University Library of Munich, Germany.
    7. Dauwe, Alexander & Moura, Marcelo L., 2011. "Forecasting the term structure of the Euro Market using Principal Component Analysis," Insper Working Papers wpe_233, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    8. Alessia Paccagnini, 2016. "The Macroeconomic Determinants of the US Term-Structure During The Great Moderation," Open Access publications 10197/7324, School of Economics, University College Dublin.
    9. Márcio Laurini, 2011. "Bayesian Factor Selection in Dynamic Term Structure Models," IBMEC RJ Economics Discussion Papers 2011-02, Economics Research Group, IBMEC Business School - Rio de Janeiro.
    10. Jens H. E. Christensen & Jose A. Lopez & Glenn D. Rudebusch, 2009. "Inflation expectations and risk premiums in an arbitrage-free model of nominal and real bond yields," Proceedings, Federal Reserve Bank of San Francisco, issue Jan.
    11. Takamizawa, Hideyuki, 2022. "How arbitrage-free is the Nelson–Siegel model under stochastic volatility?," International Review of Economics & Finance, Elsevier, vol. 79(C), pages 205-223.
    12. Balter, Anne G. & Pelsser, Antoon & Schotman, Peter C., 2021. "What does a term structure model imply about very long-term interest rates?," Journal of Empirical Finance, Elsevier, vol. 62(C), pages 202-219.
    13. Leo Krippner, 2013. "A tractable framework for zero lower bound Gaussian term structure models," Reserve Bank of New Zealand Discussion Paper Series DP2013/02, Reserve Bank of New Zealand.
    14. Leo Krippner, 2012. "A theoretical foundation for the Nelson and Siegel class of yield curve models," CAMA Working Papers 2012-11, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    15. Sébastien Fries & Jean‐Stéphane Mésonnier & Sarah Mouabbi & Jean‐Paul Renne, 2018. "National natural rates of interest and the single monetary policy in the euro area," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(6), pages 763-779, September.
    16. Molenaars, Tomas K. & Reinerink, Nick H. & Hemminga, Marcus A., 2015. "Forecasting the yield curve: art or science?," MPRA Paper 61917, University Library of Munich, Germany.
    17. Leo Krippner, 2012. "Modifying Gaussian term structure models when interest rates are near the zero lower bound (this is a revised version of CAMA working paper 36/2011)," CAMA Working Papers 2012-05, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    18. Gzyl, Henryk & Mayoral, Silvia, 2016. "Determination of zero-coupon and spot rates from treasury data by maximum entropy methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 38-50.
    19. Laurini, Márcio P. & Hotta, Luiz K., 2008. "Bayesian extensions to diebold-li term structure model," Insper Working Papers wpe_122, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    20. Glenn D. Rudebusch, 2010. "Macro-finance models of interest rates and the economy," Working Paper Series 2010-01, Federal Reserve Bank of San Francisco.
    21. Wali Ullah & Yasumasa Matsuda, 2014. "Generalized Nelson-Siegel Term Structure Model : Do the second slope and curvature factors improve the in-sample fit and out-of-sample forecast?," TERG Discussion Papers 312, Graduate School of Economics and Management, Tohoku University.
    22. Wali Ullah, 2020. "The arbitrage-free generalized Nelson–Siegel term structure model: Does a good in-sample fit imply better out-of-sample forecasts?," Empirical Economics, Springer, vol. 59(3), pages 1243-1284, September.
    23. Leo Krippner, 2012. "Modifying Gaussian term structure models when interest rates are near the zero lower bound," Reserve Bank of New Zealand Discussion Paper Series DP2012/02, Reserve Bank of New Zealand.
    24. Robert Brooks & Pavel Teterin, 2020. "Samuelson hypothesis, arbitrage activity, and futures term premiums," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(9), pages 1420-1441, September.
    25. Kei Imakubo & Haruki Kojima & Jouchi Nakajima, 2018. "The natural yield curve: its concept and measurement," Empirical Economics, Springer, vol. 55(2), pages 551-572, September.
    26. Andrea Carriero & Sarah Mouabbi & Elisabetta Vangelista, 2018. "UK term structure decompositions at the zero lower bound," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(5), pages 643-661, August.
    27. Daniel Vela, 2013. "Forecasting Latin-American yield curves: An artificial neural network approach," Borradores de Economia 761, Banco de la Republica de Colombia.
    28. Vahidin Jeleskovic & Anastasios Demertzidis, 2018. "Comparing different methods for the estimation of interbank intraday yield curves," MAGKS Papers on Economics 201839, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    29. Levant, Jared & Ma, Jun, 2017. "A dynamic Nelson-Siegel yield curve model with Markov switching," Economic Modelling, Elsevier, vol. 67(C), pages 73-87.
    30. Craig Blackburn & Michael Sherris, 2011. "Consistent Dynamic Affine Mortality Model for Longevity Risk Applications," Working Papers 201107, ARC Centre of Excellence in Population Ageing Research (CEPAR), Australian School of Business, University of New South Wales.
    31. Ranik Raaen Wahlstrøm & Florentina Paraschiv & Michael Schürle, 2022. "A Comparative Analysis of Parsimonious Yield Curve Models with Focus on the Nelson-Siegel, Svensson and Bliss Versions," Computational Economics, Springer;Society for Computational Economics, vol. 59(3), pages 967-1004, March.
    32. Juneja, Januj, 2017. "Invariance, observational equivalence, and identification: Some implications for the empirical performance of affine term structure models," The Quarterly Review of Economics and Finance, Elsevier, vol. 64(C), pages 292-305.
    33. Januj Juneja, 2015. "An evaluation of alternative methods used in the estimation of Gaussian term structure models," Review of Quantitative Finance and Accounting, Springer, vol. 44(1), pages 1-24, January.
    34. Hokuto Ishii, 2018. "Modeling and Predictability of Exchange Rate Changes by the Extended Relative Nelson–Siegel Class of Models," IJFS, MDPI, vol. 6(3), pages 1-15, August.
    35. Renata Tavanielli & Márcio Laurini, 2023. "Yield Curve Models with Regime Changes: An Analysis for the Brazilian Interest Rate Market," Mathematics, MDPI, vol. 11(11), pages 1-28, June.
    36. Andreasen, Martin M. & Christensen, Jens H.E. & Rudebusch, Glenn D., 2019. "Term Structure Analysis with Big Data: One-Step Estimation Using Bond Prices," Journal of Econometrics, Elsevier, vol. 212(1), pages 26-46.
    37. Albert K. Tsui & Junxiang Wu & Zhaoyong Zhang & Zhongxi Zheng, 2023. "Forecasting term structure of the Japanese bond yields in the presence of a liquidity trap," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(5), pages 1205-1227, August.
    38. Jacek Kotłowski & Michał Brzoza-Brzezina, 2012. "Measuring the Natural Yield Curve," EcoMod2012 4197, EcoMod.
    39. Valentin Jouvanceau & Ieva Mikaliunaite, 2020. "Euro Area Monetary Communications: Excess Sensitivity and Perception Shocks," Bank of Lithuania Working Paper Series 79, Bank of Lithuania.
    40. Rihab Bedoui & Islem Kedidi, 2018. "Modeling Longevity Risk using Consistent Dynamics Affine Mortality Models," Working Papers hal-01678050, HAL.
    41. Juneja, Januj, 2014. "Term structure estimation in the presence of autocorrelation," The North American Journal of Economics and Finance, Elsevier, vol. 28(C), pages 119-129.
    42. Luís Francisco Aguiar & Manuel M. F. Martins & Maria Joana Soares, 2010. "The yield curve and the macro-economy across time and frequencies," NIPE Working Papers 21/2010, NIPE - Universidade do Minho.
    43. Takamizawa, Hideyuki & 高見澤, 秀幸, 2015. "Impact of No-arbitrage on Interest Rate Dynamics," Working Paper Series G-1-5, Hitotsubashi University Center for Financial Research.
    44. Blackburn, Craig & Sherris, Michael, 2013. "Consistent dynamic affine mortality models for longevity risk applications," Insurance: Mathematics and Economics, Elsevier, vol. 53(1), pages 64-73.
    45. Caio Almeida & Axel Simonsen & José Valentim Vicente, 2012. "Forecasting Bond Yields with Segmented Term Structure Models," Working Papers Series 288, Central Bank of Brazil, Research Department.
    46. Koeda, Junko & Sekine, Atsushi, 2022. "Nelson–Siegel decay factor and term premia in Japan," Journal of the Japanese and International Economies, Elsevier, vol. 64(C).
    47. Kim, Young Min & Kang, Kyu Ho & Ka, Kook, 2020. "Do bond markets find inflation targets credible? Evidence from five inflation-targeting countries," International Review of Economics & Finance, Elsevier, vol. 67(C), pages 66-84.
    48. Kaminska, Iryna & Mumtaz, Haroon & Šustek, Roman, 2021. "Monetary policy surprises and their transmission through term premia and expected interest rates," Journal of Monetary Economics, Elsevier, vol. 124(C), pages 48-65.
    49. Januj Amar Juneja, 2021. "How do invariant transformations affect the calibration and optimization of the Kalman filtering algorithm used in the estimation of continuous-time affine term structure models?," Computational Management Science, Springer, vol. 18(1), pages 73-97, January.
    50. Laurini, Márcio P. & Caldeira, João F., 2016. "A macro-finance term structure model with multivariate stochastic volatility," International Review of Economics & Finance, Elsevier, vol. 44(C), pages 68-90.
    51. Lajos Horváth & Piotr Kokoszka & Jeremy VanderDoes & Shixuan Wang, 2022. "Inference in functional factor models with applications to yield curves," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(6), pages 872-894, November.
    52. Fabricio Tourrucôo & João F. Caldeira & Guilherme V. Moura & André A. P. Santos, 2016. "Forecasting The Yield Curve With The Arbitrage-Free Dynamic Nelson-Siegel Model: Brazilian Evidence," Anais do XLII Encontro Nacional de Economia [Proceedings of the 42nd Brazilian Economics Meeting] 028, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    53. Joslin, Scott & Le, Anh & Singleton, Kenneth J., 2013. "Why Gaussian macro-finance term structure models are (nearly) unconstrained factor-VARs," Journal of Financial Economics, Elsevier, vol. 109(3), pages 604-622.
    54. Linlin Niu & Gengming Zeng, 2013. "The Discrete-Time Framework of the Arbitrage-Free Nelson-Siegel Class of Term Structure Models," Working Papers 2013-10-14, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    55. Márcio Laurini & João Frois Caldeira, 2012. "Some Comments on a Macro-Finance Model with Stochastic Volatility," IBMEC RJ Economics Discussion Papers 2012-04, Economics Research Group, IBMEC Business School - Rio de Janeiro.
    56. Lorenčič Eva, 2016. "Testing the Performance of Cubic Splines and Nelson-Siegel Model for Estimating the Zero-coupon Yield Curve," Naše gospodarstvo/Our economy, Sciendo, vol. 62(2), pages 42-50, June.
    57. Wolfgang Karl Härdle,Piotr Majer & Melanie Schienle, 2012. "Yield Curve Modeling and Forecasting using Semiparametric Factor Dynamics," SFB 649 Discussion Papers SFB649DP2012-048, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    58. Daniel Vela, 2013. "Forecasting Latin-American yield curves: An artificial neural network approach," Borradores de Economia 10502, Banco de la Republica.
    59. Januj Amar Juneja, 2022. "A Computational Analysis of the Tradeoff in the Estimation of Different State Space Specifications of Continuous Time Affine Term Structure Models," Computational Economics, Springer;Society for Computational Economics, vol. 60(1), pages 173-220, June.
    60. Caldeira, João F. & Laurini, Márcio P. & Portugal, Marcelo S., 2010. "Bayesian Inference Applied to Dynamic Nelson-Siegel Model with Stochastic Volatility," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 30(1), October.
    61. Bekker, Paul A., 2017. "Interpretable Parsimonious Arbitrage-free Modeling of the Yield Curve," Research Report 17009-EEF, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    62. Eran Raviv, 2013. "Prediction Bias Correction for Dynamic Term Structure Models," Tinbergen Institute Discussion Papers 13-041/III, Tinbergen Institute.
    63. Di Maggio, Marco, 2010. "The Political Economy of the Yield Curve," MPRA Paper 20697, University Library of Munich, Germany.
    64. Bredin, Don & O'Sullivan, Conall & Spencer, Simon, 2021. "Forecasting WTI crude oil futures returns: Does the term structure help?," Energy Economics, Elsevier, vol. 100(C).
    65. Eric Fischer, 2020. "Monetary Surprises and Global Financial Flows: A Case Study of Latin America," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 19(2), pages 189-225, August.
    66. Anthony H. Tu & Cathy Yi-Hsuan Chen, 2016. "What Derives the Bond Portfolio Value-at-Risk: Information Roles of Macroeconomic and Financial Stress Factors," SFB 649 Discussion Papers SFB649DP2016-006, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    67. Michael D. Bauer & Glenn D. Rudebusch & Jing Cynthia Wu, 2011. "Unbiased estimate of dynamic term structure models," Working Paper Series 2011-12, Federal Reserve Bank of San Francisco.
    68. Munch Grønlund, Asger & Jørgensen, Kasper & Schupp, Fabian, 2024. "Measuring market-based core inflation expectations," Working Paper Series 2908, European Central Bank.
    69. Wali Ullah & Yasumasa Matsuda & Yoshihiko Tsukuda, 2015. "Generalized Nelson-Siegel term structure model: do the second slope and curvature factors improve the in-sample fit and out-of-sample forecasts?," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(4), pages 876-904, April.
    70. Lutz Kruschwitz, 2018. "Das Problem der Anschlussverzinsung," Schmalenbach Journal of Business Research, Springer, vol. 70(1), pages 9-45, March.
    71. Hiroyuki Kawakatsu, 2020. "Recovering Yield Curves from Dynamic Term Structure Models with Time-Varying Factors," Stats, MDPI, vol. 3(3), pages 1-46, August.
    72. Frank J. Fabozzi & Francesco A. Fabozzi & Diana Tunaru, 2023. "A comparison of multi-factor term structure models for interbank rates," Review of Quantitative Finance and Accounting, Springer, vol. 61(1), pages 323-356, July.
    73. ZHU Xiaoneng & Shahidur RAHMAN, 2009. "A Regime Switching Macro-finance Model of the Term Structure," Economic Growth Centre Working Paper Series 0901, Nanyang Technological University, School of Social Sciences, Economic Growth Centre.

  33. Francis X. Diebold & Georg H. Strasser, 2008. "On the Correlation Structure of Microstructure Noise in Theory and Practice," PIER Working Paper Archive 08-038, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.

    Cited by:

    1. Kim Christensen & Roel Oomen & Mark Podolskij, 2009. "Realised Quantile-Based Estimation of the Integrated Variance," CREATES Research Papers 2009-27, Department of Economics and Business Economics, Aarhus University.
    2. Goettler, Ronald L. & Parlour, Christine A. & Rajan, Uday, 2009. "Informed traders and limit order markets," Journal of Financial Economics, Elsevier, vol. 93(1), pages 67-87, July.
    3. Kim Christensen & Silja Kinnebrock & Mark Podolskij, 2009. "Pre-averaging estimators of the ex-post covariance matrix in noisy diffusion models with non-synchronous data," CREATES Research Papers 2009-45, Department of Economics and Business Economics, Aarhus University.
    4. E. Bacry & S. Delattre & M. Hoffmann & J. F. Muzy, 2011. "Modeling microstructure noise with mutually exciting point processes," Papers 1101.3422, arXiv.org.
    5. O. E. Barndorff-Nielsen & P. Reinhard Hansen & A. Lunde & N. Shephard, 2009. "Realized kernels in practice: trades and quotes," Econometrics Journal, Royal Economic Society, vol. 12(3), pages 1-32, November.
    6. P. Simmons & N. Tantisantiwong, 2014. "Equilibrium moment restrictions on asset returns: normal and crisis periods," The European Journal of Finance, Taylor & Francis Journals, vol. 20(11), pages 1064-1089, November.

  34. Frank Schorfheide & Francis X. Diebold & Marco Del Negro, 2008. "Priors from Frequency-Domain Dummy Observations," 2008 Meeting Papers 310, Society for Economic Dynamics.

    Cited by:

    1. Zhongjun Qu, 2011. "Inference and Speci?cation Testing in DSGE Models with Possible Weak Identification," Boston University - Department of Economics - Working Papers Series WP2011-058, Boston University - Department of Economics.
    2. Zhongjun Qu, 2018. "A Composite Likelihood Framework for Analyzing Singular DSGE Models," The Review of Economics and Statistics, MIT Press, vol. 100(5), pages 916-932, December.

  35. S. Boragan Aruoba & Francis X. Diebold & Chiara Scotti, 2007. "Real-Time Measurement of Business Conditions, Second Version," PIER Working Paper Archive 08-011, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 04 Apr 2008.

    Cited by:

    1. Andres Fernandez & Norman R. Swanson, 2009. "Real-time datasets really do make a difference: definitional change, data release, and forecasting," Working Papers 09-28, Federal Reserve Bank of Philadelphia.
    2. Martina Hengge & Seton Leonard, 2017. "Factor Models for Non-Stationary Series: Estimates of Monthly U.S. GDP," IHEID Working Papers 13-2017, Economics Section, The Graduate Institute of International Studies.
    3. Willem THORBECKE, 2020. "The Impact of the COVID-19 Pandemic on the U.S. Economy: Evidence from the Stock Market," Discussion papers 20068, Research Institute of Economy, Trade and Industry (RIETI).
    4. Franco, Ray John Gabriel & Mapa, Dennis S., 2014. "The Dynamics of Inflation and GDP Growth: A Mixed Frequency Model Approach," MPRA Paper 55858, University Library of Munich, Germany.
    5. Francisco Blasques & Siem Jan Koopman & Max Mallee, 2014. "Low Frequency and Weighted Likelihood Solutions for Mixed Frequency Dynamic Factor Models," Tinbergen Institute Discussion Papers 14-105/III, Tinbergen Institute.

  36. Francis X. Diebold & Canlin Li & Vivian Z. Yue, 2007. "Global Yield Curve Dynamics and Interactions: A Dynamic Nelson-Siegel Approach," PIER Working Paper Archive 07-030, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.

    Cited by:

    1. Moench, Emanuel & Soofi-Siavash, Soroosh, 2022. "What moves treasury yields?," Journal of Financial Economics, Elsevier, vol. 146(3), pages 1016-1043.
    2. Pegoraro, F. & Siegel, A. F. & Tiozzo Pezzoli, L., 2014. "Specification Analysis of International Treasury Yield Curve Factors," Working papers 490, Banque de France.
    3. Shi Yafeng & Ai Chunrong & Yanlong Shi & Ying Tingting & Xu Qunfang, 2023. "Large covariance estimation using a factor model with common and group‐specific factors," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(8), pages 2217-2248, December.
    4. Coroneo, Laura & Nyholm, Ken & Vidova-Koleva, Rositsa, 2008. "How arbitrage-free is the Nelson-Siegel Model?," Working Paper Series 874, European Central Bank.
    5. Zeyyad Mandalinci & Haroon Mumtaz, 2019. "Global Economic Divergence and Portfolio Capital Flows to Emerging Markets," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 51(6), pages 1713-1730, September.
    6. Roy Havemann & Henk Janse van Vuuren & Daan Steenkamp & Rossouw van Jaarsveld, 2022. "The bond market impact of the South African Reserve Bank bond purchase programme," Working Papers 11024, South African Reserve Bank.
    7. Yu-chin Chen & Kwok Ping Tsang & Wen Jen Tsay, 2010. "Home Bias in Currency Forecasts," Working Papers 272010, Hong Kong Institute for Monetary Research.
    8. Dick, Christian D. & Schmeling, Maik & Schrimpf, Andreas, 2010. "Macro expectations, aggregate uncertainty, and expected term premia," ZEW Discussion Papers 10-064, ZEW - Leibniz Centre for European Economic Research.
    9. Minchul Shin & Molin Zhong, 2015. "Does Realized Volatility Help Bond Yield Density Prediction?," Finance and Economics Discussion Series 2015-115, Board of Governors of the Federal Reserve System (U.S.).
    10. Chadha, Jagjit S. & Waters, Alex, 2014. "Applying a macro-finance yield curve to UK quantitative Easing," Journal of Banking & Finance, Elsevier, vol. 39(C), pages 68-86.
    11. Tommaso Tornese, 2023. "A Euro Area Term Structure Model with Time Varying Exposures," BAFFI CAREFIN Working Papers 23199, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    12. Guerello, Chiara & Tronzano, Marco, 2020. "“Global factors, international spillovers, and the term structure of interest rates: New evidence for Asian Countries”," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    13. Schwaab, Bernd & Koopman, Siem Jan & Lucas, André, 2016. "Global credit risk: world country and industry factors," Working Paper Series 1922, European Central Bank.
    14. Liu, Edith X., 2010. "Diversifying Credit Risk with International Corporate Bonds," Working Papers 10-4, University of Pennsylvania, Wharton School, Weiss Center.
    15. Okimoto, Tatsuyoshi & Takaoka, Sumiko, 2017. "The term structure of credit spreads and business cycle in Japan," Journal of the Japanese and International Economies, Elsevier, vol. 45(C), pages 27-36.
    16. Lasse Bork & Hans Dewachter & Romain Houssa, 2009. "Identification of Macroeconomic Factors in Large Panels," CREATES Research Papers 2009-43, Department of Economics and Business Economics, Aarhus University.
    17. Andreea Oprea, 2022. "The Use of Principal Component Analysis (PCA) in Building Yield Curve Scenarios and Identifying Relative-Value Trading Opportunities on the Romanian Government Bond Market," JRFM, MDPI, vol. 15(6), pages 1-37, May.
    18. Takamizawa, Hideyuki, 2022. "How arbitrage-free is the Nelson–Siegel model under stochastic volatility?," International Review of Economics & Finance, Elsevier, vol. 79(C), pages 205-223.
    19. Mirko Abbritti & Mr. Salvatore Dell'Erba & Mr. Antonio Moreno & Mr. Sergio Sola, 2013. "Global Factors in the Term Structure of Interest Rates," IMF Working Papers 2013/223, International Monetary Fund.
    20. Marco Del Negro & Domenico Giannone & Marc Giannoni & Andrea Tambalotti, 2018. "Global trends in interest rates," Staff Reports 866, Federal Reserve Bank of New York.
    21. Byrne, Joseph P. & Fazio, Giorgio & Fiess, Norbert, 2012. "Interest rate co-movements, global factors and the long end of the term spread," Journal of Banking & Finance, Elsevier, vol. 36(1), pages 183-192.
    22. Leo Krippner, 2012. "A theoretical foundation for the Nelson and Siegel class of yield curve models," CAMA Working Papers 2012-11, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    23. Awaludin, Fadhlee & Masih, Mansur, 2015. "Sukuk pricing dynamics - factors influencing yield curve of the Malaysian Sukuk," MPRA Paper 66355, University Library of Munich, Germany.
    24. Gzyl, Henryk & Mayoral, Silvia, 2016. "Determination of zero-coupon and spot rates from treasury data by maximum entropy methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 38-50.
    25. Laurini, Márcio P. & Hotta, Luiz K., 2008. "Bayesian extensions to diebold-li term structure model," Insper Working Papers wpe_122, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    26. Glenn D. Rudebusch, 2010. "Macro-finance models of interest rates and the economy," Working Paper Series 2010-01, Federal Reserve Bank of San Francisco.
    27. Ergemen, Yunus Emre & Rodríguez-Caballero, C. Vladimir, 2023. "Estimation of a dynamic multi-level factor model with possible long-range dependence," International Journal of Forecasting, Elsevier, vol. 39(1), pages 405-430.
    28. Burak Saltoglu & M. Ege Yazgan, 2012. "The Role of Regime Shifts in the Term Structure of Interest Rates: Further Evidence from an Emerging Market," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 48(S5), pages 48-63, November.
    29. Yifeng Yan & Ju'e Guo, 2015. "The Sovereign Yield Curve and the Macroeconomy in China," Pacific Economic Review, Wiley Blackwell, vol. 20(3), pages 415-441, August.
    30. Chen, Rong & Xiao, Han & Yang, Dan, 2021. "Autoregressive models for matrix-valued time series," Journal of Econometrics, Elsevier, vol. 222(1), pages 539-560.
    31. Bai, Jushan & Ando, Tomohiro, 2013. "Multifactor asset pricing with a large number of observable risk factors and unobservable common and group-specific factors," MPRA Paper 52785, University Library of Munich, Germany, revised Dec 2013.
    32. Adam Traczyk, 2013. "Financial integration and the term structure of interest rates," Empirical Economics, Springer, vol. 45(3), pages 1267-1305, December.
    33. Nathan Sussman & Osnat Zohar, 2018. "Has inflation targeting become less credible?," BIS Working Papers 729, Bank for International Settlements.
    34. Piero C. Kauffmann & Hellinton H. Takada & Ana T. Terada & Julio M. Stern, 2022. "Learning Forecast-Efficient Yield Curve Factor Decompositions with Neural Networks," Econometrics, MDPI, vol. 10(2), pages 1-15, March.
    35. Mario Figueiredo & Yuri F. Saporito, 2023. "Forecasting the term structure of commodities future prices using machine learning," Digital Finance, Springer, vol. 5(1), pages 57-90, March.
    36. Hubrich, Kirstin & Marcellino, Massimiliano & Beck, Günter, 2011. "On the importance of sectoral and regional shocks for price-setting," CEPR Discussion Papers 8357, C.E.P.R. Discussion Papers.
    37. Robert Brooks & Pavel Teterin, 2020. "Samuelson hypothesis, arbitrage activity, and futures term premiums," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(9), pages 1420-1441, September.
    38. Siem Jan Koopman & Max I.P. Mallee & Michel van der Wel, 2007. "Analyzing the Term Structure of Interest Rates using the Dynamic Nelson-Siegel Model with Time-Varying Parameters," Tinbergen Institute Discussion Papers 07-095/4, Tinbergen Institute.
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    4. Geng, Jiang-Bo & Du, Ya-Juan & Ji, Qiang & Zhang, Dayong, 2021. "Modeling return and volatility spillover networks of global new energy companies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    5. Imran Yousaf & Shoaib Ali, 2020. "Discovering interlinkages between major cryptocurrencies using high-frequency data: new evidence from COVID-19 pandemic," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-18, December.
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    21. Tihana Škrinjarić, 2019. "Time Varying Spillovers between the Online Search Volume and Stock Returns: Case of CESEE Markets," IJFS, MDPI, vol. 7(4), pages 1-30, October.
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    26. Lovcha, Yuliya & Pérez Laborda, Àlex & Sikora, Iryna, 2019. "The Determinants of CO2 prices in the EU ETS System," Working Papers 2072/376031, Universitat Rovira i Virgili, Department of Economics.
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    1. Zhou, Siwen, 2019. "Assessing the Macroeconomic Impact of the ECB’s Asset Purchase Programme in a Dynamic Nelson–Siegel Modelling Framework," MPRA Paper 92530, University Library of Munich, Germany.
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    4. Borus Jungbacker & Siem Jan Koopman & Michel van der Wel, 2009. "Smooth Dynamic Factor Analysis with an Application to the U.S. Term Structure of Interest Rates," CREATES Research Papers 2009-39, Department of Economics and Business Economics, Aarhus University.
    5. Coroneo, Laura & Nyholm, Ken & Vidova-Koleva, Rositsa, 2008. "How arbitrage-free is the Nelson-Siegel Model?," Working Paper Series 874, European Central Bank.
    6. Minchul Shin & Molin Zhong, 2015. "Does Realized Volatility Help Bond Yield Density Prediction?," Finance and Economics Discussion Series 2015-115, Board of Governors of the Federal Reserve System (U.S.).
    7. Wali Ullah & Yoshihiko Tsukuda & Yasumasa Matsuda, 2012. "Term Structure Forecasting of Government Bond Yields with Latent and Macroeconomic Factors: Does Macroeconomic Factors Imply Better Out-of-Sample Forecasts?," TERG Discussion Papers 287, Graduate School of Economics and Management, Tohoku University.
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    34. Burak Saltoglu & M. Ege Yazgan, 2012. "The Role of Regime Shifts in the Term Structure of Interest Rates: Further Evidence from an Emerging Market," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 48(S5), pages 48-63, November.
    35. Wali Ullah & Yasumasa Matsuda, 2014. "Generalized Nelson-Siegel Term Structure Model : Do the second slope and curvature factors improve the in-sample fit and out-of-sample forecast?," TERG Discussion Papers 312, Graduate School of Economics and Management, Tohoku University.
    36. Jens H. E. Christensen & Mark M. Spiegel, 2021. "Central Bank Credibility During COVID-19: Evidence from Japan," Working Paper Series 2021-24, Federal Reserve Bank of San Francisco.
    37. Wali Ullah, 2020. "The arbitrage-free generalized Nelson–Siegel term structure model: Does a good in-sample fit imply better out-of-sample forecasts?," Empirical Economics, Springer, vol. 59(3), pages 1243-1284, September.
    38. Castro-Iragorri, C & Ramírez, J, 2021. "Forecasting Dynamic Term Structure Models with Autoencoders," Documentos de Trabajo 19431, Universidad del Rosario.
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    40. Massimo Guidolin & Manuela Pedio, 2019. "Forecasting and Trading Monetary Policy Effects on the Riskless Yield Curve with Regime Switching Nelson†Siegel Models," Working Papers 639, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    41. Hans Dewachter & Leonardo Iania & Jean-Charles Wijnandts, 2016. "The response of euro area sovereign spreads to the ECB unconventional monetary policies," Working Paper Research 309, National Bank of Belgium.
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    2. Mishra, Abinash & Srivastava, Pranjal & Chakrabarti, Anindya S., 2020. "'Too central to fail' firms in bi-layered financial networks: Evidence of linkages from the US corporate bond and stock markets," IIMA Working Papers WP 2020-06-02, Indian Institute of Management Ahmedabad, Research and Publication Department.
    3. Azad, A.S.M. Sohel & Fang, Victor & Hung, Chi-Hsiou, 2012. "Linking the interest rate swap markets to the macroeconomic risk: The UK and us evidence," International Review of Financial Analysis, Elsevier, vol. 22(C), pages 38-47.
    4. Charlotte Christiansen & Maik Schmeling & Andreas Schrimpf, 2012. "A Comprehensive Look at Financial Volatility Prediction by Economic Variables," BIS Working Papers 374, Bank for International Settlements.
    5. Bevilacqua, Mattia & Morelli, David & Tunaru, Radu, 2019. "The determinants of the model-free positive and negative volatilities," Journal of International Money and Finance, Elsevier, vol. 92(C), pages 1-24.
    6. Elie Bouri & Riza Demirer & Rangan Gupta & Xiaojin Sun, 2019. "The Predictability of Stock Market Volatility in Emerging Economies: Relative Roles of Local, Regional and Global Business Cycles," Working Papers 201938, University of Pretoria, Department of Economics.
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    2. Marc-Gregor Czaja & Hendrik Scholz & Marco Wilkens, 2009. "Interest rate risk of German financial institutions: the impact of level, slope, and curvature of the term structure," Review of Quantitative Finance and Accounting, Springer, vol. 33(1), pages 1-26, July.
    3. Leo Krippner, 2012. "A theoretical foundation for the Nelson and Siegel class of yield curve models," CAMA Working Papers 2012-11, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    4. Leo Krippner, 2008. "A Macroeconomic Foundation for the Nelson and Siegel Class of Yield Curve Models," Research Paper Series 226, Quantitative Finance Research Centre, University of Technology, Sydney.
    5. Ibanez, Francisco, 2015. "Calibrating the Dynamic Nelson-Siegel Model: A Practitioner Approach," MPRA Paper 68377, University Library of Munich, Germany.
    6. Md Akhtaruzzaman & Paul Docherty & Abul Shamsuddin, 2014. "Interest rate, size and book-to-market effects in Australian financial firms," Applied Economics, Taylor & Francis Journals, vol. 46(25), pages 3005-3020, September.
    7. Boril Šopov & Jakub Seidler, 2010. "Yield Curve Dynamics: Regional Common Factor Model," Working Papers IES 2010/17, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Aug 2010.
    8. Md. Akhtaruzzaman & Abul Shamsuddin, 2017. "Australian financial firms’ exposures to the level, slope, and curvature of the interest rate term structure," Applied Economics, Taylor & Francis Journals, vol. 49(19), pages 1855-1874, April.
    9. Cláudia Simões & Luís Oliveira & Jorge M. Bravo, 2021. "Immunization Strategies for Funding Multiple Inflation-Linked Retirement Income Benefits," Risks, MDPI, vol. 9(4), pages 1-28, March.
    10. Baek, Seungho & Bilson, John F.O., 2015. "Size and value risk in financial firms," Journal of Banking & Finance, Elsevier, vol. 55(C), pages 295-326.
    11. Gimeno, Ricardo & Nave, Juan M., 2009. "A genetic algorithm estimation of the term structure of interest rates," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2236-2250, April.
    12. Francisco Ibáñez, 2016. "Calibrating the Dynamic Nelson-Siegel Model: A Practitioner Approach," Working Papers Central Bank of Chile 774, Central Bank of Chile.
    13. Sanjay Singh & Neeraj Hatekar, 2018. "Macroeconomic shocks and evolution of term structure of interest rate: A dynamic latent factor approach," Indian Economic Review, Springer, vol. 53(1), pages 245-262, December.
    14. Scott Mixon & Tugkan Tuzun, 2018. "Price Pressure and Price Discovery in the Term Structure of Interest Rates," Finance and Economics Discussion Series 2018-065, Board of Governors of the Federal Reserve System (U.S.).

  42. Francis X. Diebold & Lutz Kilian & Marc Nerlove, 2006. "Time Series Analysis," PIER Working Paper Archive 06-019, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    • Diebold, F.X. & Kilian, L. & Nerlove, Marc, 2006. "Time Series Analysis," Working Papers 28556, University of Maryland, Department of Agricultural and Resource Economics.

    Cited by:

    1. Jeremy Berkowitz & Ionel Birgean & Lutz Kilian, 1999. "On the finite-sample accuracy of nonparametric resampling algorithms for economic time series," Finance and Economics Discussion Series 1999-04, Board of Governors of the Federal Reserve System (U.S.).
    2. Andersson, Fredrik N.G. & Edgerton, David L. & Opper, Sonja, 2013. "A Matter of Time: Revisiting Growth Convergence in China," World Development, Elsevier, vol. 45(C), pages 239-251.
    3. Hannes Leeb & Benedikt M. Potscher, 2003. "Can One Estimate the Conditional Distribution of Post-Model-Selection Estimators?," Cowles Foundation Discussion Papers 1444, Cowles Foundation for Research in Economics, Yale University.
    4. Grabowski, Daniel & Staszewska-Bystrova, Anna, 2018. "Skewness-Adjusted Bootstrap Confidence Intervals and Confidence Bands for Impulse Response Functions," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181590, Verein für Socialpolitik / German Economic Association.
    5. Hacker, Scott & Kim, Hyunjoo & Månsson, Kristofer, 2010. "The Relationship between Exchange Rates and Interest Rate Differentials: a Wavelet Approach," Working Paper Series in Economics and Institutions of Innovation 217, Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies.
    6. Nyankori, James Cyprian Okuk & Wabukawo, Veronica & Sakyi-Dawson, Esther & Sefa-Dedeh, Sam, 2002. "Product Life Cycle Model Of Cowpea Based Products In Ghana," Working Papers 18803, Clemson University, Department of Agricultural and Applied Economics.
    7. Kilian, Lutz & Kim, Yun Jung, 2009. "Do Local Projections Solve the Bias Problem in Impulse Response Inference?," CEPR Discussion Papers 7266, C.E.P.R. Discussion Papers.
    8. Francis X. Diebold & Lutz Kilian, 1997. "Measuring Predictability: Theory and Macroeconomic Applications," NBER Technical Working Papers 0213, National Bureau of Economic Research, Inc.
    9. Ralf Brüggemann, 2006. "Finite Sample Properties of Impulse Response Intervals in SVECMs with Long-Run Identifying Restrictions," SFB 649 Discussion Papers SFB649DP2006-021, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    10. Atsushi Inoue & Lutz Kilian, 2002. "Bootstrapping Autoregressive Processes with Possible Unit Roots," Econometrica, Econometric Society, vol. 70(1), pages 377-391, January.
    11. Quinton Morris & Gary Van Vuuren & Paul Styger, 2009. "Further Evidence Of Long Memory In The South African Stock Market," South African Journal of Economics, Economic Society of South Africa, vol. 77(1), pages 81-101, March.
    12. Madalina-Gabriela ANGHEL & Luminita Madalina CALOTA, 2016. "Statistical-econometric model used in performance analysis of the company," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 64(10), pages 33-40, October.
    13. Helmut Luetkepohl, 2007. "Econometric Analysis with Vector Autoregressive Models," Economics Working Papers ECO2007/11, European University Institute.
    14. Diana COCONOIU & Elena BUGUDUI, 2012. "Using Dynamic Series of Moments for Economic Analysis," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 60(4), pages 94-97, November.
    15. Thabo M. Mokoena & Gupta, R. & Van Eyden, R., 2009. "Half-Life Deviations from PPP in the South African Development Community (SADC)," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 9(1).
    16. Monika Blaszkiewicz-Schwartzman, 2007. "Explaining Exchange Rate Movements in New Member States of the European Union: Nominal and Real Convergence," Money Macro and Finance (MMF) Research Group Conference 2006 144, Money Macro and Finance Research Group.

  43. Peter F. Christoffersen & Francis X. Diebold & Roberto S. Mariano & Anthony S. Tay & Yiu Kuen Tse, 2006. "Direction-of-Change Forecasts Based on Conditional Variance, Skewness and Kurtosis Dynamics: International Evidence," PIER Working Paper Archive 06-016, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.

    Cited by:

    1. Stanislav Anatolyev & Nikolay Gospodinov, 2007. "Modeling Financial Return Dynamics by Decomposition," Working Papers w0095, New Economic School (NES).
    2. Papailias, Fotis & Liu, Jiadong & Thomakos, Dimitrios D., 2019. "Return Signal Momentum," QBS Working Paper Series 2019/04, Queen's University Belfast, Queen's Business School.
    3. Stelios Bekiros & Dimitris Georgoutsos, 2008. "Non-linear dynamics in financial asset returns: the predictive power of the CBOE volatility index," The European Journal of Finance, Taylor & Francis Journals, vol. 14(5), pages 397-408.
    4. Papailias, Fotis & Liu, Jiadong & Thomakos, Dimitrios D., 2021. "Return signal momentum," Journal of Banking & Finance, Elsevier, vol. 124(C).
    5. M. Bigeco & E. Grosso & E. Otranto, 2008. "Recognizing and Forecasting the Sign of Financial Local Trends using Hidden Markov Models," Working Paper CRENoS 200803, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    6. Stanislav Anatolyev & Natalia Kryzhanovskaya, 2009. "Directional Prediction of Returns under Asymmetric Loss: Direct and Indirect Approaches," Working Papers w0136, Center for Economic and Financial Research (CEFIR).
    7. Luis H. R. Alvarez E. & Paavo Salminen, 2017. "Timing in the presence of directional predictability: optimal stopping of skew Brownian motion," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 86(2), pages 377-400, October.

  44. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Clara Vega, 2006. "Real-time price discovery in global stock, bond and foreign exchange markets," International Finance Discussion Papers 871, Board of Governors of the Federal Reserve System (U.S.).

    Cited by:

    1. Wu, Zhen-Xing & Gau, Yin-Feng, 2022. "Informativeness of trades around macroeconomic announcements in the foreign exchange market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 78(C).
    2. Imane El Ouadghiri & Remzi Uctum, 2016. "Jumps in equilibrium prices and asymmetric news in foreign exchange markets," Post-Print hal-01386027, HAL.
    3. Giuliana Passamani & Roberto Tamborini & Matteo Tomaselli, 2016. "Taxing financial transactions in fundamentally heterogeneous markets," DEM Working Papers 2016/10, Department of Economics and Management.
    4. Michael D. Bauer & Eric T. Swanson, 2022. "A Reassessment of Monetary Policy Surprises and High-Frequency Identification," NBER Chapters, in: NBER Macroeconomics Annual 2022, volume 37, pages 87-155, National Bureau of Economic Research, Inc.
    5. Roman Frydman & Michael Goldberg & Nicholas Mangee, 2015. "New Evidence for the Present-Value Model of Stock Prices: Why the REH Version Failed Empirically," Working Papers Series 2, Institute for New Economic Thinking.
    6. Mihaela NICOLAU, 2010. "Financial Markets Interactions between Economic Theory and Practice," Economics and Applied Informatics, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, issue 2, pages 27-36.
    7. Lian, Yu-Min & Chen, Jun-Home & Liao, Szu-Lang, 2021. "Cojump risks and their impacts on option pricing," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 399-410.
    8. Beirne, John & Gieck, Jana, 2012. "Interdependence and contagion in global asset markets," Working Paper Series 1480, European Central Bank.
    9. Gagan Deep Sharma & Mandeep Mahendru & Mrinalini Srivastava, 2019. "Can Central Banking Policies Make a Difference in Financial Market Performance in Emerging Economies? The Case of India," Economies, MDPI, vol. 7(2), pages 1-19, May.
    10. Wang, Wenhao & Lin, Zhitao & Hu, Bing, 2023. "Macro news effects on exchange rates: Difference between carry trade target and safe-haven currencies," Finance Research Letters, Elsevier, vol. 53(C).
    11. Tzuo Hann Law & Dongho Song & Amir Yaron, 2017. "Fearing the Fed: How Wall Street Reads Main Street," 2017 Meeting Papers 1632, Society for Economic Dynamics.
    12. Dunbar, Kwamie & Amin, Abu S., 2012. "Credit risk dynamics in response to changes in the federal funds target: The implication for firm short-term debt," Review of Financial Economics, Elsevier, vol. 21(3), pages 141-152.
    13. Kathryn M.E. Dominguez & Rasmus Fatum & Pavel Vacek, 2010. "Does Foreign Exchange Reserve Decumulation Lead to Currency Appreciation?," EPRU Working Paper Series 2010-06, Economic Policy Research Unit (EPRU), University of Copenhagen. Department of Economics.
    14. Claudio Raddatz & Sergio L. Schmukler, 2011. "On the International Transmission of Shocks: Micro-Evidence from Mutual Fund Portfolios," NBER Chapters, in: Global Financial Crisis, National Bureau of Economic Research, Inc.
    15. Paiardini, Paola, 2014. "The impact of economic news on bond prices: Evidence from the MTS platform," Journal of Banking & Finance, Elsevier, vol. 49(C), pages 302-322.
    16. Angelo Ranaldo & Dr. Enzo Rossi, 2007. "The reaction of asset markets to Swiss National Bank communication," Working Papers 2007-11, Swiss National Bank.
    17. ÅžimÅŸek, Alp & Caballero, Ricardo, 2022. "Monetary Policy and Asset Price Overshooting: A Rationale for the Wall/Main Street Disconnect," CEPR Discussion Papers 15163, C.E.P.R. Discussion Papers.
    18. Sensoy, Ahmet & Sobaci, Cihat, 2014. "Effects of volatility shocks on the dynamic linkages between exchange rate, interest rate and the stock market: The case of Turkey," Economic Modelling, Elsevier, vol. 43(C), pages 448-457.
    19. Paul Wohlfarth, 2018. "Measuring the Impact of Monetary Policy Attention on Global Asset Volatility Using Search Data," Birkbeck Working Papers in Economics and Finance 1803, Birkbeck, Department of Economics, Mathematics & Statistics.
    20. Maximo Camacho & Marcos Dal Bianco & Gabriel Perez Quiros, 2012. "Short-run forecasting of the euro-dollar exchange rate with economic fundamentals," Working Papers 1201, BBVA Bank, Economic Research Department.
    21. Giovannelli, Alessandro & Massacci, Daniele & Soccorsi, Stefano, 2021. "Forecasting stock returns with large dimensional factor models," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 252-269.
    22. Czech, Robert & Huang, Shiyang & Lou, Dong & Wang, Tianyu, 2021. "Informed trading in government bond markets," LSE Research Online Documents on Economics 118857, London School of Economics and Political Science, LSE Library.
    23. Zolotoy, Leon & Frederickson, James R. & Lyon, John D., 2017. "Aggregate earnings and stock market returns: The good, the bad, and the state-dependent," Journal of Banking & Finance, Elsevier, vol. 77(C), pages 157-175.
    24. Andrew Phiri, 2018. "Has the South African Reserve Bank responded to equity returns since the sub-prime crisis? An asymmetric convergence approach," International Journal of Sustainable Economy, Inderscience Enterprises Ltd, vol. 10(3), pages 205-225.
    25. Christos Floros & Konstantinos Gkillas & Christoforos Konstantatos & Athanasios Tsagkanos, 2020. "Realized Measures to Explain Volatility Changes over Time," JRFM, MDPI, vol. 13(6), pages 1-19, June.
    26. Daniel Jubinski & Marc Tomljanovich, 2013. "Do FOMC minutes matter to markets? An intraday analysis of FOMC minutes releases on individual equity volatility and returns," Review of Financial Economics, John Wiley & Sons, vol. 22(3), pages 86-97, September.
    27. Skintzi, Vasiliki D., 2019. "Determinants of stock-bond market comovement in the Eurozone under model uncertainty," International Review of Financial Analysis, Elsevier, vol. 61(C), pages 20-28.
    28. Imane El Ouadghiri & Remzi Uctum, 2015. "Jumps in Equilibrium Prices and Asymmetric News in Foreign Exchange Markets," Working Papers hal-04141414, HAL.
    29. Wang, Cindy S.H. & Fan, Rui & Xie, Yiqiang, 2023. "Market systemic risk, predictability and macroeconomics news," Finance Research Letters, Elsevier, vol. 56(C).
    30. Anna Cieslak & Pavol Povala, 2016. "Information in the Term Structure of Yield Curve Volatility," Journal of Finance, American Finance Association, vol. 71(3), pages 1393-1436, June.
    31. Pisun Xu & Jian Yang, 2011. "U.S. Monetary Policy Surprises and International Securitized Real Estate Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 43(4), pages 459-490, November.
    32. Nicolas Boitout & Imane El Ouadghiri & Valérie Mignon, 2016. "On the impact of macroeconomic news surprises on Treasury-bond returns," Post-Print hal-01386014, HAL.
    33. Radu LUPU & Alexandra MATEESCU & Mihai MITRACHE, 2017. "Analysis of Macroeconomic Events Impact Using the Event Study Methodology," Hyperion Economic Journal, Faculty of Economic Sciences, Hyperion University of Bucharest, Romania, vol. 5(2), pages 3-13, June.
    34. Saban Nazlioglu & Shawkat Hammoudeh & Rangan Gupta, 2015. "Volatility transmission between Islamic and conventional equity markets: evidence from causality-in-variance test," Applied Economics, Taylor & Francis Journals, vol. 47(46), pages 4996-5011, October.
    35. Kim, Jae H. & Shamsuddin, Abul & Lim, Kian-Ping, 2011. "Stock return predictability and the adaptive markets hypothesis: Evidence from century-long U.S. data," Journal of Empirical Finance, Elsevier, vol. 18(5), pages 868-879.
    36. Jinjarak, Yothin, 2014. "Equity prices and financial globalization," International Review of Financial Analysis, Elsevier, vol. 33(C), pages 49-57.
    37. Alessio Emanuele Biondo, 2020. "Information versus imitation in a real-time agent-based model of financial markets," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(3), pages 613-631, July.
    38. Dungey, Mardi & Erdemlioglu, Deniz & Matei, Marius & Yang, Xiye, 2018. "Testing for mutually exciting jumps and financial flights in high frequency data," Journal of Econometrics, Elsevier, vol. 202(1), pages 18-44.
    39. Mark Paddrik & Roy Hayes & William Scherer & Peter Beling, 2014. "Effects of Limit Order Book Information Level on Market Stability Metrics," Working Papers 14-09, Office of Financial Research, US Department of the Treasury.
    40. Schneider, Martin & Albuquerque, Rui & ,, 2006. "Global Private Information in International Equity Markets," CEPR Discussion Papers 5819, C.E.P.R. Discussion Papers.
    41. Liao, Yin, 2013. "The benefit of modeling jumps in realized volatility for risk prediction: Evidence from Chinese mainland stocks," Pacific-Basin Finance Journal, Elsevier, vol. 23(C), pages 25-48.
    42. Charles Engel, 2013. "Exchange Rates and Interest Parity," NBER Working Papers 19336, National Bureau of Economic Research, Inc.
    43. Smimou, K. & Khallouli, W., 2015. "Does the Euro affect the dynamic relation between stock market liquidity and the business cycle?," Emerging Markets Review, Elsevier, vol. 25(C), pages 125-153.
    44. Joshua Hausman & Jon Wongswan, 2006. "Global asset prices and FOMC announcements," International Finance Discussion Papers 886, Board of Governors of the Federal Reserve System (U.S.).
    45. Meher Manzur, 2018. "Exchange rate economics is always and everywhere controversial," Applied Economics, Taylor & Francis Journals, vol. 50(3), pages 216-232, January.
    46. Marcel Fratzscher, 2011. "Capital Flows, Push versus Pull Factors and the Global Financial Crisis," NBER Working Papers 17357, National Bureau of Economic Research, Inc.
    47. Ben Omrane, Walid & Savaşer, Tanseli, 2016. "The sign switch effect of macroeconomic news in foreign exchange markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 45(C), pages 96-114.
    48. Indriawan, Ivan, 2020. "Market quality around macroeconomic news announcements: Evidence from the Australian stock market," Pacific-Basin Finance Journal, Elsevier, vol. 61(C).
    49. Badye Essid & Tolga Cenesizoglu, 2010. "The Effect of Monetary Policy on Credit Spreads," 2010 Meeting Papers 1139, Society for Economic Dynamics.
    50. Dungey, Mardi & Luciani, Matteo & Veredas, David, 2012. "Ranking systemically important financial institutions," Working Papers 15473, University of Tasmania, Tasmanian School of Business and Economics, revised 21 Nov 2012.
    51. Yin-Wong Cheung & Rasmus Fatum & Yohei Yamamoto, 2017. "The Exchange Rate Effects of Macro News after the Global Financial Crisis," GRU Working Paper Series GRU_2017_007, City University of Hong Kong, Department of Economics and Finance, Global Research Unit.
    52. Thomas Gilbert & Shimon Kogan & Lars Lochstoer & Ataman Ozyildirim, 2007. "Investor Inattention and the Market Impact of Summary Statistics," GSIA Working Papers 2006-E24, Carnegie Mellon University, Tepper School of Business.
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    54. Sirimon Treepongkaruna & Robert Brooks & Stephen Gray, 2012. "Do trading hours affect volatility links in the foreign exchange market?," Australian Journal of Management, Australian School of Business, vol. 37(1), pages 7-27, April.
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    58. Li, Guangzhong & Zhu, Jiaqing & Li, Jie, 2016. "Understanding bilateral exchange rate risks," Journal of International Money and Finance, Elsevier, vol. 68(C), pages 103-129.
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    61. Narayan, Paresh Kumar & Sharma, Susan Sunila, 2018. "An analysis of time-varying commodity market price discovery," International Review of Financial Analysis, Elsevier, vol. 57(C), pages 122-133.
    62. Liang Ding & Hao Zou & Vittorio Addona, 2012. "Semi‐transparency, dealership market, and foreign exchange market quality," Review of Financial Economics, John Wiley & Sons, vol. 21(1), pages 1-13, January.
    63. Du, Wenti, 2018. "Who carried more credibility?: An analysis of the market responses to news from the Japanese government, the Japanese central bank and international credit rating agencies," Journal of Economics and Business, Elsevier, vol. 98(C), pages 32-39.
    64. George Jiang & Ingrid Lo, 2011. "Private Information Flow and Price Discovery in the U.S. Treasury Market," Staff Working Papers 11-5, Bank of Canada.
    65. David Büttner & Bernd Hayo & Matthias Neuenkirch, 2009. "The Impact of Foreign Macroeconomic News on Financial Markets in the Czech Republic, Hungary, and Poland," MAGKS Papers on Economics 200903, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    66. Charles Engel, 2015. "Exchange Rates, Interest Rates, and the Risk Premium," NBER Working Papers 21042, National Bureau of Economic Research, Inc.
    67. Elif Sisli Ciamarra & Tanseli Savaser, 2015. "Managerial Performance Incentives and Firm Risk during Economic Expansions and Recessions," Working Papers 93, Brandeis University, Department of Economics and International Business School.
    68. Lieven Baele, 2010. "The Determinants of Stock and Bond Return Comovements," The Review of Financial Studies, Society for Financial Studies, vol. 23(6), pages 2374-2428, June.
    69. Davide Pettenuzzo & Riccardo Sabbatucci & Allan Timmermann, 2018. "High-frequency Cash Flow Dynamics," Working Papers 120, Brandeis University, Department of Economics and International Business School.
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    71. Kurov, Alexander & Olson, Eric & Zaynutdinova, Gulnara R., 2022. "When does the fed care about stock prices?," Journal of Banking & Finance, Elsevier, vol. 142(C).
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    44. Krainer, Robert E., 2017. "Economic stability under alternative banking systems: Theory and policy," Journal of Financial Stability, Elsevier, vol. 31(C), pages 107-118.
    45. Sousa, João & Sousa, Ricardo M., 2017. "Predicting risk premium under changes in the conditional distribution of stock returns," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 50(C), pages 204-218.
    46. Shamsi Zamenjani, Azam, 2021. "Do financial variables help predict the conditional distribution of the market portfolio?," Journal of Empirical Finance, Elsevier, vol. 62(C), pages 327-345.
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    48. Prabheesh, K.P. & Vidya, C.T., 2018. "Do business cycles, investment-specific technology shocks matter for stock returns?," Economic Modelling, Elsevier, vol. 70(C), pages 511-524.
    49. Safari, Meysam & TahmooresPour, Reza, 2011. "Moderation Effect of Market Condition on the Relationship between Dividend Yield and Stock Return," MPRA Paper 28913, University Library of Munich, Germany.
    50. Lindblad, Annika, 2017. "Sentiment indicators and macroeconomic data as drivers for low-frequency stock market volatility," MPRA Paper 80266, University Library of Munich, Germany.
    51. Lustig, Hanno & Verdelhan, Adrien, 2012. "Business cycle variation in the risk-return trade-off," Journal of Monetary Economics, Elsevier, vol. 59(S), pages 35-49.
    52. Reitz, Stefan & Pierdzioch, Christian & Rülke, Jan-Christoph, 2015. "Nonlinear Expectation Formation in the U.S. Stock Market," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113210, Verein für Socialpolitik / German Economic Association.
    53. Abdulilah Ibrahim Alsheikhmubarak & Evangelos Giouvris, 2018. "A Comparative GARCH Analysis of Macroeconomic Variables and Returns on Modelling the Kurtosis of FTSE 100 Implied Volatility Index," Multinational Finance Journal, Multinational Finance Journal, vol. 22(3-4), pages 119-172, September.
    54. Pierdzioch, Christian & Reitz, Stefan & Ruelke, Jan-Christoph, 2015. "Nonlinear expectation formation in the U.S. stock market: Empirical evidence from the Livingston survey," Kiel Working Papers 1947 [rev.], Kiel Institute for the World Economy (IfW Kiel).
    55. Diego Fresoli, 2022. "Bootstrap VAR forecasts: The effect of model uncertainties," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 279-293, March.
    56. Metiu, Norbert & Prieto, Esteban, 2023. "Time-varying stock return correlation, news shocks, and business cycles," Discussion Papers 05/2023, Deutsche Bundesbank.
    57. Marc Joëts, 2012. "Energy price transmissions during extreme movements," Working Papers hal-04141047, HAL.
    58. Eriksen, Jonas N., 2017. "Expected Business Conditions and Bond Risk Premia," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 52(4), pages 1667-1703, August.
    59. Markku Lanne & Henri Nyberg, 2015. "Nonlinear dynamic interrelationships between real activity and stock returns," CREATES Research Papers 2015-36, Department of Economics and Business Economics, Aarhus University.
    60. Philippe Goulet Coulombe & Mikael Frenette & Karin Klieber, 2023. "From Reactive to Proactive Volatility Modeling with Hemisphere Neural Networks," Working Papers 23-04, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Nov 2023.
    61. Liu, Yang, 2023. "Government debt and risk premia," Journal of Monetary Economics, Elsevier, vol. 136(C), pages 18-34.
    62. Le, Trung H., 2021. "International portfolio allocation: The role of conditional higher moments," International Review of Economics & Finance, Elsevier, vol. 74(C), pages 33-57.
    63. Cheng, Hang & Shi, Yongdong, 2020. "Forecasting China's stock market variance," Pacific-Basin Finance Journal, Elsevier, vol. 64(C).
    64. Park, Sung Y. & Ryu, Doojin & Song, Jeongseok, 2017. "The dynamic conditional relationship between stock market returns and implied volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 638-648.
    65. Rapach, David & Zhou, Guofu, 2013. "Forecasting Stock Returns," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 328-383, Elsevier.
    66. Kim Chang-Jin & Kim Yunmi, 2019. "A unified framework jointly explaining business conditions, stock returns, volatility and “volatility feedback news” effects," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 23(2), pages 1-14, April.
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  46. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005. "Volatility Forecasting," PIER Working Paper Archive 05-011, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.

    Cited by:

    1. Courtenay, Roger & Clare, Andrew, 2001. "What can we learn about monetary policy transparency from financial market data?," Discussion Paper Series 1: Economic Studies 2001,06, Deutsche Bundesbank.
    2. Anthony S. Tay & Peter F. Christoffersen & Francis X. Diebold & Roberto S. Mariano & Yiu Kuen Tse, 2006. "Direction-of-Change Forecasts Based on Conditional Variance, Skewness and Kurtosis Dynamics : International Evidence," Finance Working Papers 22481, East Asian Bureau of Economic Research.
    3. Olkhov, Victor, 2021. "Three Remarks On Asset Pricing," MPRA Paper 109238, University Library of Munich, Germany.
    4. Zareipour, Hamidreza & Bhattacharya, Kankar & Canizares, Claudio A., 2007. "Electricity market price volatility: The case of Ontario," Energy Policy, Elsevier, vol. 35(9), pages 4739-4748, September.
    5. Gregory Bauer & Keith Vorkink, 2007. "Multivariate Realized Stock Market Volatility," Staff Working Papers 07-20, Bank of Canada.
    6. Lux, Thomas & Morales-Arias, Leonardo, 2010. "Relative forecasting performance of volatility models: Monte Carlo evidence," Kiel Working Papers 1582, Kiel Institute for the World Economy (IfW Kiel).
    7. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005. "Practical Volatility and Correlation Modeling for Financial Market Risk Management," PIER Working Paper Archive 05-007, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    8. Eric Jacquier & Nicholas G. Polson & Peter E. Rossi, 1999. "Stochastic Volatility: Univariate and Multivariate Extensions," CIRANO Working Papers 99s-26, CIRANO.
    9. Olkhov, Victor, 2022. "The Market-Based Asset Price Probability," MPRA Paper 115382, University Library of Munich, Germany, revised 16 Nov 2022.
    10. Victor Olkhov, 2020. "Price, Volatility and the Second-Order Economic Theory," Papers 2009.14278, arXiv.org, revised Apr 2021.
    11. Torben G. Andersen & Tim Bollerslev & Xin Huang, 2007. "A Reduced Form Framework for Modeling Volatility of Speculative Prices based on Realized Variation Measures," CREATES Research Papers 2007-14, Department of Economics and Business Economics, Aarhus University.
    12. Luisa Bisaglia & Silvano Bordignon & Francesco Lisi, 2003. "k -Factor GARMA models for intraday volatility forecasting," Applied Economics Letters, Taylor & Francis Journals, vol. 10(4), pages 251-254.
    13. Anderson, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Labys, Paul, 2002. "Modeling and Forecasting Realized Volatility," Working Papers 02-12, Duke University, Department of Economics.
    14. Matei, Marius, 2010. "Risk analysis in the evaluation of the international investment opportunities. Advances in modelling and forecasting volatility for risk assessment purposes," Working Papers of Institute for Economic Forecasting 100201, Institute for Economic Forecasting.
    15. Hao Zhou, 2003. "Itô conditional moment generator and the estimation of short rate processes," Finance and Economics Discussion Series 2003-32, Board of Governors of the Federal Reserve System (U.S.).
    16. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Jin Wu, 2005. "A Framework for Exploring the Macroeconomic Determinants of Systematic Risk," American Economic Review, American Economic Association, vol. 95(2), pages 398-404, May.
    17. Yan-Leung Cheung & Yin-Wong Cheung & Alan T.K. Wan, 2008. "A High-Low Model of Daily Stock Price Ranges," CESifo Working Paper Series 2387, CESifo.
    18. Terasvirta, Timo, 2006. "Forecasting economic variables with nonlinear models," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 8, pages 413-457, Elsevier.
    19. ZHU, Dongming & ZINDE-WALSH, Victoria, 2007. "Properties and Estimation of Asymmetric Exponential Power Distribution," Cahiers de recherche 13-2007, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    20. Rime, Dagfinn & Sucarrat, Genaro, 2007. "Exchange rate variability, market activity and heterogeneity," UC3M Working papers. Economics we077039, Universidad Carlos III de Madrid. Departamento de Economía.
    21. Bauer, Gregory H. & Vorkink, Keith, 2011. "Forecasting multivariate realized stock market volatility," Journal of Econometrics, Elsevier, vol. 160(1), pages 93-101, January.
    22. Guidolin, Massimo & Timmermann, Allan, 2006. "Term structure of risk under alternative econometric specifications," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 285-308.
    23. Milan Ficura & Jiri Witzany, 2016. "Estimating Stochastic Volatility and Jumps Using High-Frequency Data and Bayesian Methods," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 66(4), pages 278-301, August.
    24. SUCARRAT, Genaro, 2006. "The first stage in Hendry’s reduction theory revisited," LIDAM Discussion Papers CORE 2006082, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    25. Robert Ślepaczuk & Grzegorz Zakrzewski, 2009. "High-Frequency and Model-Free Volatility Estimators," Working Papers 2009-13, Faculty of Economic Sciences, University of Warsaw.
    26. Olkhov, Victor, 2020. "Volatility Depend on Market Trades and Macro Theory," MPRA Paper 102434, University Library of Munich, Germany.
    27. Ariño, Miguel A. & Canela, Miguel A., 2006. "Study of the dollar-euro exchange rate," IESE Research Papers D/620, IESE Business School, revised 30 Mar 2006.
    28. Tim Bollerslev & Morten Ø. Nielsen & Per Houmann Frederiksen & Torben G. Andersen, 2008. "Continuous-time Models, Realized Volatilities, And Testable Distributional Implications For Daily Stock Returns," Working Paper 1173, Economics Department, Queen's University.
    29. Abramov, Vyacheslav & Klebaner, Fima, 2006. "Forecasting and testing a non-constant volatility," MPRA Paper 207, University Library of Munich, Germany.
    30. Allen, P. Geoffrey & Morzuch, Bernard J., 2006. "Twenty-five years of progress, problems, and conflicting evidence in econometric forecasting. What about the next 25 years?," International Journal of Forecasting, Elsevier, vol. 22(3), pages 475-492.
    31. David McMillan & Alan Speight, 2005. "Long-memory and heterogeneous components in high frequency Pacific-Basin exchange rate volatility," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 12(3), pages 199-226, September.
    32. Lux, Thomas & Morales-Arias, Leonardo, 2009. "Forecasting volatility under fractality, regime-switching, long memory and student-t innovations," Kiel Working Papers 1532, Kiel Institute for the World Economy (IfW Kiel).
    33. Suhejla Hoiti & Esfandiar Maasoumi & Michael McAleer & Daniel Slottje, 2005. "Measuring the Volatility in U.S. Treasury Benchmarks and Debt Instruments," DEA Working Papers 14, Universitat de les Illes Balears, Departament d'Economía Aplicada.
    34. Théoret, Raymond & Racicot, François-Éric, 2010. "Forecasting stochastic Volatility using the Kalman filter: an application to Canadian Interest Rates and Price-Earnings Ratio," MPRA Paper 35911, University Library of Munich, Germany.
    35. Francois-Éric Racicot & Raymond Théoret, 2005. "Quelques applications du filtre de Kalman en finance: estimation et prévision de la volatilité stochastique et du rapport cours-bénéfices," RePAd Working Paper Series UQO-DSA-wp0312005, Département des sciences administratives, UQO.
    36. Valeri Voev, 2009. "On the Economic Evaluation of Volatility Forecasts," CREATES Research Papers 2009-56, Department of Economics and Business Economics, Aarhus University.
    37. Qinkai Chen & Christian-Yann Robert, 2021. "Multivariate Realized Volatility Forecasting with Graph Neural Network," Papers 2112.09015, arXiv.org, revised Dec 2021.
    38. Patton, Andrew J., 2011. "Volatility forecast comparison using imperfect volatility proxies," Journal of Econometrics, Elsevier, vol. 160(1), pages 246-256, January.
    39. Andrew Clare & Roger Courtenay, 2001. "Assessing the impact of macroeconomic news announcements on securities prices under different monetary policy regimes," Bank of England working papers 125, Bank of England.
    40. Victor Olkhov, 2021. "To VaR, or Not to VaR, That is the Question," Papers 2101.08559, arXiv.org, revised Oct 2021.
    41. Bistra Radeva, 2019. "Stock price fluctuations and GARCH modelling of stock market indexes," Economics and computer science, Publishing house "Knowledge and business" Varna, issue 3, pages 6-19.
    42. Sizova, Natalia, 2011. "Integrated variance forecasting: Model based vs. reduced form," Journal of Econometrics, Elsevier, vol. 162(2), pages 294-311, June.
    43. Juliusz Jabłecki & Ryszard Kokoszczyński & Paweł Sakowski & Robert Ślepaczuk & Piotr Wójcik, 2014. "Does historical volatility term structure contain valuable in-formation for predicting volatility index futures?," Working Papers 2014-18, Faculty of Economic Sciences, University of Warsaw.
    44. Veiga, Helena, 2006. "Volatility forecasts: a continuous time model versus discrete time models," DES - Working Papers. Statistics and Econometrics. WS ws062509, Universidad Carlos III de Madrid. Departamento de Estadística.
    45. Vyacheslav Abramov & Fima Klebaner, 2007. "Estimation and Prediction of a Non-Constant Volatility," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 14(1), pages 1-23, March.
    46. Bretó, Carles & Veiga, Helena, 2011. "Forecasting volatility: does continuous time do better than discrete time?," DES - Working Papers. Statistics and Econometrics. WS ws112518, Universidad Carlos III de Madrid. Departamento de Estadística.

  47. Francis X. Diebold & Monika Piazzesi & Glenn Rudebusch, 2005. "Modeling Bond Yields in Finance and Macroeconomics," NBER Working Papers 11089, National Bureau of Economic Research, Inc.

    Cited by:

    1. Rafael Barros de Rezende, 2011. "Giving Flexibility to the Nelson-Siegel Class of Term Structure Models," Brazilian Review of Finance, Brazilian Society of Finance, vol. 9(1), pages 27-49.
    2. Martins, Manuel M.F. & Afonso, António, 2010. "Level, slope, curvature of the sovereign yield curve, and fiscal behaviour," Working Paper Series 1276, European Central Bank.
    3. Olesya Grishchenko & Sarah Mouabbi & Jean‐Paul Renne, 2019. "Measuring Inflation Anchoring and Uncertainty: A U.S. and Euro Area Comparison," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 51(5), pages 1053-1096, August.
    4. Eric Hillebrand & Huiyu Huang & Tae-Hwy Lee & Canlin Li, 2018. "Using the Entire Yield Curve in Forecasting Output and Inflation," Econometrics, MDPI, vol. 6(3), pages 1-27, August.
    5. Matsumura, Marco & Moreira, Ajax & Vicente, José, 2011. "Forecasting the yield curve with linear factor models," International Review of Financial Analysis, Elsevier, vol. 20(5), pages 237-243.
    6. Hautsch, Nikolaus & Ou, Yangguoyi, 2009. "Analyzing interest rate risk: Stochastic volatility in the term structure of government bond yields," CFS Working Paper Series 2009/03, Center for Financial Studies (CFS).
    7. Coroneo, Laura & Nyholm, Ken & Vidova-Koleva, Rositsa, 2008. "How arbitrage-free is the Nelson-Siegel Model?," Working Paper Series 874, European Central Bank.
    8. Dick, Christian D. & Schmeling, Maik & Schrimpf, Andreas, 2010. "Macro expectations, aggregate uncertainty, and expected term premia," ZEW Discussion Papers 10-064, ZEW - Leibniz Centre for European Economic Research.
    9. Diebold, Francis X. & Li, Canlin & Yue, Vivian Z., 2008. "Global yield curve dynamics and interactions: A dynamic Nelson-Siegel approach," Journal of Econometrics, Elsevier, vol. 146(2), pages 351-363, October.
    10. Chadha, Jagjit S. & Waters, Alex, 2014. "Applying a macro-finance yield curve to UK quantitative Easing," Journal of Banking & Finance, Elsevier, vol. 39(C), pages 68-86.
    11. Josué Cortés Espada & Carlos Capistrán & Manuel Ramos-Francia & Alberto Torres, 2009. "An empirical analysis of the mexican term structure of interest rates," Economics Bulletin, AccessEcon, vol. 29(3), pages 2300-2313.
    12. Galvao, Ana Beatriz & Costa, Sonia, 2013. "Does the euro area forward rate provide accurate forecasts of the short rate?," International Journal of Forecasting, Elsevier, vol. 29(1), pages 131-141.
    13. Marco Matsumara & Ajax R.B. Moreira, 2005. "Can Macroeconomic Variables Account for the Term Structure of Sovereign Spreads? Studying the Brazilian Case," Discussion Papers 1106, Instituto de Pesquisa Econômica Aplicada - IPEA.
    14. Taboga, Marco & Pericoli, Marcello, 2008. "Bond risk premia, macroeconomic fundamentals and the exchange rate," MPRA Paper 9523, University Library of Munich, Germany.
    15. Margherita Bottero & Stefano schiaffi, 2022. "Firm liquidity and the transmission of monetary policy," Temi di discussione (Economic working papers) 1378, Bank of Italy, Economic Research and International Relations Area.
    16. Kenneth W. Clements & Renee Fry, 2006. "Commodity Currencies And Currency Commodities," CAMA Working Papers 2006-19, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    17. Guglielmo Maria Caporale & Luis A. Gil-Alana & Carlos Poza, 2021. "The Covid-19 Pandemic and the Degree of Persistence of US Stock Prices and Bond Yields," CESifo Working Paper Series 8976, CESifo.
    18. Alessia Paccagnini, 2016. "The Macroeconomic Determinants of the US Term-Structure During The Great Moderation," Open Access publications 10197/7324, School of Economics, University College Dublin.
    19. Huse, Cristian, 2011. "Term structure modelling with observable state variables," Journal of Banking & Finance, Elsevier, vol. 35(12), pages 3240-3252.
    20. Mr. Rodrigo Cabral & Mr. Richard Munclinger & Mr. Luiz Alves & Mr. Marco Rodriguez Waldo, 2011. "On Brazil’s Term Structure: Stylized Facts and Analysis of Macroeconomic Interactions," IMF Working Papers 2011/113, International Monetary Fund.
    21. Marco S. Matsumura, 2015. "Impact of Macro Shocks on Sovereign Default Probabilities," Discussion Papers 0173, Instituto de Pesquisa Econômica Aplicada - IPEA.
    22. Jens H. E. Christensen & Francis X. Diebold & Glenn D. Rudebusch, 2008. "An Arbitrage-Free Generalized Nelson-Siegel Term Structure Model," PIER Working Paper Archive 08-030, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    23. Dong Heon Kim, 2008. "Another Look at Yield Spreads: The Role of Liquidity," Southern Economic Journal, John Wiley & Sons, vol. 74(4), pages 952-970, April.
    24. Paolo Zagaglia, 2013. "Forecasting Long-Term Interest Rates with a General-Equilibrium Model of the Euro Area: What Role for Liquidity Services of Bonds?," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 20(4), pages 383-430, November.
    25. Paolo Zagaglia, 2011. "Forecasting Long-Term Interest Rates with a Dynamic General Equilibrium Model of the Euro Area: The Role of the Feedback," Working Paper series 19_11, Rimini Centre for Economic Analysis.
    26. Oliver Blaskowitz & Helmut Herwatz, 2008. "Adaptive Forecasting of the EURIBOR Swap Term Structure," SFB 649 Discussion Papers SFB649DP2008-017, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    27. Lee, Shyan Yuan & Chiou, Wan-Jiun Paul & Chung, Yi-Fang, 2017. "Pricing corporate bonds and constructing credit curves in a developing country: The case of the Taiwan bond fund crisis," International Review of Economics & Finance, Elsevier, vol. 50(C), pages 261-274.
    28. René Garcia & Richard Luger, 2005. "The Canadian Macroeconomy and the Yield Curve: An Equilibrium-Based Approach," Staff Working Papers 05-36, Bank of Canada.
    29. Jacopo Panerati & Nicolas Schwind & Stefan Zeltner & Katsumi Inoue & Giovanni Beltrame, 2018. "Assessing the resilience of stochastic dynamic systems under partial observability," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-21, August.
    30. David K. Backus & Jonathan H. Wright, 2007. "Cracking the Conundrum," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 38(1), pages 293-329.
    31. Bhansali, Vineer & Dorsten, Matthew P. & Wise, Mark B., 2009. "Asymmetric monetary policy and the yield curve," Journal of International Money and Finance, Elsevier, vol. 28(8), pages 1408-1425, December.
    32. Gzyl, Henryk & Mayoral, Silvia, 2016. "Determination of zero-coupon and spot rates from treasury data by maximum entropy methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 38-50.
    33. Glenn D. Rudebusch, 2010. "Macro-finance models of interest rates and the economy," Working Paper Series 2010-01, Federal Reserve Bank of San Francisco.
    34. Kwangyong Park, 2020. "The Excess Sensitivity of Long-term Interest rates and Central Bank Credibility," Working Papers 2020-29, Economic Research Institute, Bank of Korea.
    35. Hautsch, Nikolaus & Yang, Fuyu, 2012. "Bayesian inference in a Stochastic Volatility Nelson–Siegel model," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3774-3792.
    36. Carlos Garriga & Finn E. Kydland & Roman Šustek, 2019. "MoNK: Mortgages in a New-Keynesian Model," NBER Working Papers 26427, National Bureau of Economic Research, Inc.
    37. Glenn D. Rudebusch & Eric T. Swanson & Tao Wu, 2006. "The Bond Yield "Conundrum" from a Macro-Finance Perspective," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 24(S1), pages 83-109, December.
    38. Jens H. E. Christensen & Francis X. Diebold & Glenn D. Rudebusch, 2007. "The Affine Arbitrage-Free Class of Nelson-Siegel Term Structure Models," PIER Working Paper Archive 07-029, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    39. Yu-chin Chen & Kwok Ping Tsang, 2013. "What Does the Yield Curve Tell Us about Exchange Rate Predictability?," The Review of Economics and Statistics, MIT Press, vol. 95(1), pages 185-205, March.
    40. Tao Wu & Glenn Rudebusch, 2004. "A Macro-Finance Model of the Term Structure, Monetary Policy, and the Economy," 2004 Meeting Papers 104, Society for Economic Dynamics.
    41. David Bolder, 2006. "Modelling Term-Structure Dynamics for Risk Management: A Practitioner's Perspective," Staff Working Papers 06-48, Bank of Canada.
    42. Massimiliano Serati & Matteo Manera & Michele Plotegher, 2008. "Modelling electricity prices: from the state of the art to a draft of a new proposal," LIUC Papers in Economics 210, Cattaneo University (LIUC).
    43. Peter Hördahl & Eli M Remolona & Giorgio Valente, 2015. "Expectations and risk premia at 8:30am: Macroeconomic announcements and the yield curve," BIS Working Papers 527, Bank for International Settlements.
    44. Löchel, H. & Packham, N. & Walisch, F., 2016. "Determinants of the onshore and offshore Chinese government yield curves," Pacific-Basin Finance Journal, Elsevier, vol. 36(C), pages 77-93.
    45. Matteo Modena, 2008. "An Empirical Analysis of the Curvature Factor of the Term Structure of Interest Rates," Working Papers 2008_35, Business School - Economics, University of Glasgow.
    46. Leo Krippner, 2008. "A Macroeconomic Foundation for the Nelson and Siegel Class of Yield Curve Models," Research Paper Series 226, Quantitative Finance Research Centre, University of Technology, Sydney.
    47. Francis E. Warnock & Veronica Cacdac Warnock, 2006. "International Capital Flows and U.S. Interest Rates," NBER Working Papers 12560, National Bureau of Economic Research, Inc.
    48. Marcello, Pericoli & Marco, Taboga, 2005. "A specification analysis of discrete-time no-arbitrage term structure models with observable and unobservable factors," MPRA Paper 4969, University Library of Munich, Germany, revised Sep 2007.
    49. Torben G. Andersen & Luca Benzoni, 2007. "Do Bonds Span Volatility Risk in the U.S. Treasury Market? A Specification test for Affine Term Structure Models," NBER Working Papers 12962, National Bureau of Economic Research, Inc.
    50. Yu-chin Chen & Kwok Ping Tsang, 2011. "A Macro-Finance Approach to Exchange Rate Determination," Working Papers 012011, Hong Kong Institute for Monetary Research.
    51. Marco S. Matsumura, 2006. "Impact of Macro Shocks on Sovereign Default Probabilities," Discussion Papers 1241, Instituto de Pesquisa Econômica Aplicada - IPEA.
    52. Ranik Raaen Wahlstrøm & Florentina Paraschiv & Michael Schürle, 2022. "A Comparative Analysis of Parsimonious Yield Curve Models with Focus on the Nelson-Siegel, Svensson and Bliss Versions," Computational Economics, Springer;Society for Computational Economics, vol. 59(3), pages 967-1004, March.
    53. Luis Ceballos & Alberto Naudon & Damián Romero, 2016. "Nominal term structure and term premia: evidence from Chile," Applied Economics, Taylor & Francis Journals, vol. 48(29), pages 2721-2735, June.
    54. Zeno Rotondi, 2006. "The Macroeconomy and the Yield Curve: A Review of the Literature with Some New Evidence," Giornale degli Economisti, GDE (Giornale degli Economisti e Annali di Economia), Bocconi University, vol. 65(2), pages 193-224, November.
    55. Timmermann, Allan & Guidolin, Massimo, 2007. "Forecasts of US Short-term Interest Rates: A Flexible Forecast Combination Approach," CEPR Discussion Papers 6188, C.E.P.R. Discussion Papers.
    56. Renne, J-P., 2009. "Frequency-domain analysis of debt service in a macro-finance model for the euro area," Working papers 261, Banque de France.
    57. Charles Leung, 2007. "Equilibrium Correlations of Asset Price and Return," The Journal of Real Estate Finance and Economics, Springer, vol. 34(2), pages 233-256, February.
    58. Rudebusch, Glenn D. & Swanson, Eric T., 2008. "Examining the bond premium puzzle with a DSGE model," Journal of Monetary Economics, Elsevier, vol. 55(Supplemen), pages 111-126, October.
    59. Leite, André Luís & Filho, Romeu Braz Pereira Gomes & Vicente, José Valentim Machado, 2010. "Forecasting the yield curve: A statistical model with market survey data," International Review of Financial Analysis, Elsevier, vol. 19(2), pages 108-112, March.
    60. Bernaschi, Massimo & Tacconi, Elisa & Vergni, Davide, 2008. "A parametric study of the term structure dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(5), pages 1264-1272.
    61. Schrimpf, Paul & Kearns, Jonathan & XIA, Fan Dora, 2020. "Explaining Monetary Spillovers: The Matrix Reloaded," CEPR Discussion Papers 15006, C.E.P.R. Discussion Papers.
    62. Mr. Carlos I. Medeiros & Ying He, 2011. "An Assessment of Estimates of Term Structure Models for the United States," IMF Working Papers 2011/247, International Monetary Fund.
    63. Bennouna, Hicham, 2019. "Interest rate pass-through in Morocco: Evidence from bank-level survey data," Economic Modelling, Elsevier, vol. 80(C), pages 142-157.
    64. Andrea Carriero, 2007. "Forecasting the Yield Curve Using Priors from No Arbitrage Affine Term Structure Models," Working Papers 612, Queen Mary University of London, School of Economics and Finance.
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    4. Viktor Todorov & Yang Zhang, 2022. "Information gains from using short‐dated options for measuring and forecasting volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(2), pages 368-391, March.
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    6. Tim Bollerslev & Michael Gibson & Hao Zhou, 2007. "Dynamic Estimation of Volatility Risk Premia and Investor Risk Aversion from Option-Implied and Realized Volatilities," CREATES Research Papers 2007-16, Department of Economics and Business Economics, Aarhus University.
    7. Adam Clements & Yin Liao, 2014. "The role in index jumps and cojumps in forecasting stock index volatility: Evidence from the Dow Jones index," NCER Working Paper Series 101, National Centre for Econometric Research.
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    Cited by:

    1. Rafael Barros de Rezende, 2011. "Giving Flexibility to the Nelson-Siegel Class of Term Structure Models," Brazilian Review of Finance, Brazilian Society of Finance, vol. 9(1), pages 27-49.
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    3. Olesya Grishchenko & Sarah Mouabbi & Jean‐Paul Renne, 2019. "Measuring Inflation Anchoring and Uncertainty: A U.S. and Euro Area Comparison," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 51(5), pages 1053-1096, August.
    4. Eric Hillebrand & Huiyu Huang & Tae-Hwy Lee & Canlin Li, 2018. "Using the Entire Yield Curve in Forecasting Output and Inflation," Econometrics, MDPI, vol. 6(3), pages 1-27, August.
    5. Matsumura, Marco & Moreira, Ajax & Vicente, José, 2011. "Forecasting the yield curve with linear factor models," International Review of Financial Analysis, Elsevier, vol. 20(5), pages 237-243.
    6. Hautsch, Nikolaus & Ou, Yangguoyi, 2009. "Analyzing interest rate risk: Stochastic volatility in the term structure of government bond yields," CFS Working Paper Series 2009/03, Center for Financial Studies (CFS).
    7. Coroneo, Laura & Nyholm, Ken & Vidova-Koleva, Rositsa, 2008. "How arbitrage-free is the Nelson-Siegel Model?," Working Paper Series 874, European Central Bank.
    8. Dick, Christian D. & Schmeling, Maik & Schrimpf, Andreas, 2010. "Macro expectations, aggregate uncertainty, and expected term premia," ZEW Discussion Papers 10-064, ZEW - Leibniz Centre for European Economic Research.
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    112. Marcos S. Matsumura & Ajax R. B. Moreira, 2006. "Macro Factors and the Brazilian Yield Curve With no Arbitrage Models," Discussion Papers 1210, Instituto de Pesquisa Econômica Aplicada - IPEA.
    113. J.Marcelo Ochoa, 2006. "An interpretation of an affine term structure model of Chile," Estudios de Economia, University of Chile, Department of Economics, vol. 33(2 Year 20), pages 155-184, December.
    114. Wilmar Alexander Cabrera-Rodríguez & Daniela Rodríguez-Novoa & Camilo Eduardo Sánchez-Quinto, 2023. "A robust model for the term structure of interest rates: some applications in Colombia," Borradores de Economia 1255, Banco de la Republica de Colombia.
    115. Ronald Ravinesh Kumar & Peter Josef Stauvermann & Hang Thi Thu Vu, 2021. "The Relationship between Yield Curve and Economic Activity: An Analysis of G7 Countries," JRFM, MDPI, vol. 14(2), pages 1-23, February.
    116. Alexey Akimov & Simon Stevenson & Maxim Zagonov, 2015. "Public Real Estate and the Term Structure of Interest Rates: A Cross-Country Study," The Journal of Real Estate Finance and Economics, Springer, vol. 51(4), pages 503-540, November.
    117. Balázs Romhányi, 2005. "A learning hypothesis of the term structure of interest rates," Macroeconomics 0503001, University Library of Munich, Germany.
    118. Michiel De Pooter, 2007. "Examining the Nelson-Siegel Class of Term Structure Models," Tinbergen Institute Discussion Papers 07-043/4, Tinbergen Institute.
    119. Nagano, Teppei & Baba, Naohiko, 2008. "Extracting market expectations from yield curves augmented by money market interest rates: the case of Japan," Working Paper Series 980, European Central Bank.
    120. Marco S. Matsumura, 2007. "Impact Of Macro Shocks On Sovereign Default Probabilities," Anais do XXXV Encontro Nacional de Economia [Proceedings of the 35th Brazilian Economics Meeting] 060, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].

  50. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2005. "Practical volatility and correlation modeling for financial market risk management," CFS Working Paper Series 2005/02, Center for Financial Studies (CFS).

    Cited by:

    1. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
    2. Sofiane Aboura & Julien Chevallier, 2014. "Cross-Market Spillovers with ‘Volatility Surprise’," EconomiX Working Papers 2014-46, University of Paris Nanterre, EconomiX.
    3. Gregory Bauer & Keith Vorkink, 2007. "Multivariate Realized Stock Market Volatility," Staff Working Papers 07-20, Bank of Canada.
    4. Erie Febrian & Aldrin Herwany, 2010. "Volatility Forecasting Models and Market Co-Integration: A Study on South-East Asian Markets," Working Papers in Business, Management and Finance 201005, Department of Management and Business, Padjadjaran University, revised May 2010.
    5. Christophe Perignon & D. Smith, 2009. "The Level and Quality of Value-at-Risk Disclosure by Commercial Banks," Post-Print hal-00496102, HAL.
    6. Francis X. Diebold & Kamil Yilmaz, 2010. "Better to Give than to Receive: Predictive Directional Measurement of Volatility Spillovers," Koç University-TUSIAD Economic Research Forum Working Papers 1001, Koc University-TUSIAD Economic Research Forum, revised Mar 2010.
    7. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Jin Wu, 2005. "A Framework for Exploring the Macroeconomic Determinants of Systematic Risk," American Economic Review, American Economic Association, vol. 95(2), pages 398-404, May.
    8. David S. Bates, 2009. "U.S. Stock Market Crash Risk, 1926-2006," NBER Working Papers 14913, National Bureau of Economic Research, Inc.
    9. Gaisser, Sandra & Memmel, Christoph & Schmidt, Rafael & Wehn, Carsten, 2009. "Time dynamic and hierarchical dependence modelling of an aggregated portfolio of trading books: a multivariate nonparametric approach," Discussion Paper Series 2: Banking and Financial Studies 2009,07, Deutsche Bundesbank.
    10. Markus Bibinger & Lars Winkelmann, 2014. "Common price and volatility jumps in noisy high-frequency data," SFB 649 Discussion Papers SFB649DP2014-037, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    11. Erie Febrian & Aldrin Herwany, 2009. "Volatility Model for Financial Market Risk Management : An Analysis on JSX Index Return Covariance Matrix," Working Papers in Economics and Development Studies (WoPEDS) 200907, Department of Economics, Padjadjaran University, revised Sep 2009.
    12. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    13. McAleer, Michael & Medeiros, Marcelo C., 2008. "A multiple regime smooth transition Heterogeneous Autoregressive model for long memory and asymmetries," Journal of Econometrics, Elsevier, vol. 147(1), pages 104-119, November.
    14. Marc S. Paolella, 2017. "The Univariate Collapsing Method for Portfolio Optimization," Econometrics, MDPI, vol. 5(2), pages 1-33, May.
    15. Zhou, Xinmiao & Qian, Huanhuan & Pérez-Rodríguez, Jorge. V. & González López-Valcárcel, Beatriz, 2020. "Risk dependence and cointegration between pharmaceutical stock markets: The case of China and the USA," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    16. Ghorbel, Ahmed & Trabelsi, Abdelwahed, 2007. "Predictive Performance of Conditional Extreme Value Theory and Conventional Methods in Value at Risk Estimation," MPRA Paper 3963, University Library of Munich, Germany.
    17. Faheem Aslam & Paulo Ferreira & Khurrum Shahzad Mughal & Beenish Bashir, 2021. "Intraday Volatility Spillovers among European Financial Markets during COVID-19," IJFS, MDPI, vol. 9(1), pages 1-19, January.
    18. Erie Febrian & Aldrin Herwany, 2009. "Forecasting Stocks of Government Owned Companies (GOCS):Volatility Modeling," Working Papers in Economics and Development Studies (WoPEDS) 200908, Department of Economics, Padjadjaran University, revised Sep 2009.
    19. Barbara Bedowska-Sojka, 2017. "Evaluating the Accuracy of Time-varying Beta. The Evidence from Poland," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 17, pages 161-176.
    20. Krahnen, Jan-Pieter & Wilde, Christian, 2006. "Risk Transfer with CDOs and Systemic Risk in Banking," CEPR Discussion Papers 5618, C.E.P.R. Discussion Papers.
    21. Jean-Paul Laurent & Hassan Omidi Firouzi, 2022. "Market Risk and Volatility Weighted Historical Simulation After Basel III," Working Papers hal-03679434, HAL.
    22. Olkhov, Victor, 2022. "Introduction of the Market-Based Price Autocorrelation," MPRA Paper 112003, University Library of Munich, Germany.
    23. Li, Leon, 2017. "Testing and comparing the performance of dynamic variance and correlation models in value-at-risk estimation," The North American Journal of Economics and Finance, Elsevier, vol. 40(C), pages 116-135.
    24. Norman R. Swanson & Valentina Corradi & Walter Distaso, 2011. "Predictive Inference for Integrated Volatility," Departmental Working Papers 201109, Rutgers University, Department of Economics.
    25. Francis X. Diebold & Kamil Yilmaz, 2008. "Macroeconomic Volatility and Stock Market Volatility, World-Wide," PIER Working Paper Archive 08-031, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    26. Othmar M. Lehner, 2013. "Crowdfunding social ventures: a model and research agenda," Venture Capital, Taylor & Francis Journals, vol. 15(4), pages 289-311, October.
    27. O’Brien, James & Szerszeń, Paweł J., 2017. "An evaluation of bank measures for market risk before, during and after the financial crisis," Journal of Banking & Finance, Elsevier, vol. 80(C), pages 215-234.
    28. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2005. "Volatility forecasting," CFS Working Paper Series 2005/08, Center for Financial Studies (CFS).
    29. James M. O'Brien & Pawel J. Szerszen, 2014. "An Evaluation of Bank VaR Measures for Market Risk During and Before the Financial Crisis," Finance and Economics Discussion Series 2014-21, Board of Governors of the Federal Reserve System (U.S.).
    30. Detlef Seese & Christof Weinhardt & Frank Schlottmann (ed.), 2008. "Handbook on Information Technology in Finance," International Handbooks on Information Systems, Springer, number 978-3-540-49487-4, November.
    31. Yoontae Jeon & Thomas H. McCurdy, 2017. "Time-Varying Window Length for Correlation Forecasts," Econometrics, MDPI, vol. 5(4), pages 1-29, December.
    32. Jondeau, Eric, 2015. "The dynamics of squared returns under contemporaneous aggregation of GARCH models," Journal of Empirical Finance, Elsevier, vol. 32(C), pages 80-93.
    33. Bates, David S., 2012. "U.S. stock market crash risk, 1926–2010," Journal of Financial Economics, Elsevier, vol. 105(2), pages 229-259.
    34. Eric Hillebrand & Marcelo Cunha Medeiros, 2010. "Asymmetries, breaks, and long-range dependence: An estimation framework for daily realized volatility," Textos para discussão 578, Department of Economics PUC-Rio (Brazil).
    35. Gao, Jun & Gao, Xiang & Gu, Chen, 2023. "Forecasting European stock volatility: The role of the UK," International Review of Financial Analysis, Elsevier, vol. 89(C).
    36. Eric Jondeau, 2008. "Contemporaneous Aggregation of GARCH Models and Evaluation of the Aggregation Bias," Swiss Finance Institute Research Paper Series 08-06, Swiss Finance Institute.

  51. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2005. "Volatility forecasting," CFS Working Paper Series 2005/08, Center for Financial Studies (CFS).

    Cited by:

    1. Courtenay, Roger & Clare, Andrew, 2001. "What can we learn about monetary policy transparency from financial market data?," Discussion Paper Series 1: Economic Studies 2001,06, Deutsche Bundesbank.
    2. Anthony S. Tay & Peter F. Christoffersen & Francis X. Diebold & Roberto S. Mariano & Yiu Kuen Tse, 2006. "Direction-of-Change Forecasts Based on Conditional Variance, Skewness and Kurtosis Dynamics : International Evidence," Finance Working Papers 22481, East Asian Bureau of Economic Research.
    3. Olkhov, Victor, 2021. "Three Remarks On Asset Pricing," MPRA Paper 109238, University Library of Munich, Germany.
    4. Zareipour, Hamidreza & Bhattacharya, Kankar & Canizares, Claudio A., 2007. "Electricity market price volatility: The case of Ontario," Energy Policy, Elsevier, vol. 35(9), pages 4739-4748, September.
    5. Gregory Bauer & Keith Vorkink, 2007. "Multivariate Realized Stock Market Volatility," Staff Working Papers 07-20, Bank of Canada.
    6. Lux, Thomas & Morales-Arias, Leonardo, 2010. "Relative forecasting performance of volatility models: Monte Carlo evidence," Kiel Working Papers 1582, Kiel Institute for the World Economy (IfW Kiel).
    7. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005. "Practical Volatility and Correlation Modeling for Financial Market Risk Management," PIER Working Paper Archive 05-007, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    8. Eric Jacquier & Nicholas G. Polson & Peter E. Rossi, 1999. "Stochastic Volatility: Univariate and Multivariate Extensions," CIRANO Working Papers 99s-26, CIRANO.
    9. Olkhov, Victor, 2022. "The Market-Based Asset Price Probability," MPRA Paper 115382, University Library of Munich, Germany, revised 16 Nov 2022.
    10. Victor Olkhov, 2020. "Price, Volatility and the Second-Order Economic Theory," Papers 2009.14278, arXiv.org, revised Apr 2021.
    11. Torben G. Andersen & Tim Bollerslev & Xin Huang, 2007. "A Reduced Form Framework for Modeling Volatility of Speculative Prices based on Realized Variation Measures," CREATES Research Papers 2007-14, Department of Economics and Business Economics, Aarhus University.
    12. Luisa Bisaglia & Silvano Bordignon & Francesco Lisi, 2003. "k -Factor GARMA models for intraday volatility forecasting," Applied Economics Letters, Taylor & Francis Journals, vol. 10(4), pages 251-254.
    13. Anderson, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Labys, Paul, 2002. "Modeling and Forecasting Realized Volatility," Working Papers 02-12, Duke University, Department of Economics.
    14. Matei, Marius, 2010. "Risk analysis in the evaluation of the international investment opportunities. Advances in modelling and forecasting volatility for risk assessment purposes," Working Papers of Institute for Economic Forecasting 100201, Institute for Economic Forecasting.
    15. Hao Zhou, 2003. "Itô conditional moment generator and the estimation of short rate processes," Finance and Economics Discussion Series 2003-32, Board of Governors of the Federal Reserve System (U.S.).
    16. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Jin Wu, 2005. "A Framework for Exploring the Macroeconomic Determinants of Systematic Risk," American Economic Review, American Economic Association, vol. 95(2), pages 398-404, May.
    17. Yan-Leung Cheung & Yin-Wong Cheung & Alan T.K. Wan, 2008. "A High-Low Model of Daily Stock Price Ranges," CESifo Working Paper Series 2387, CESifo.
    18. Terasvirta, Timo, 2006. "Forecasting economic variables with nonlinear models," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 8, pages 413-457, Elsevier.
    19. ZHU, Dongming & ZINDE-WALSH, Victoria, 2007. "Properties and Estimation of Asymmetric Exponential Power Distribution," Cahiers de recherche 13-2007, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    20. Rime, Dagfinn & Sucarrat, Genaro, 2007. "Exchange rate variability, market activity and heterogeneity," UC3M Working papers. Economics we077039, Universidad Carlos III de Madrid. Departamento de Economía.
    21. Bauer, Gregory H. & Vorkink, Keith, 2011. "Forecasting multivariate realized stock market volatility," Journal of Econometrics, Elsevier, vol. 160(1), pages 93-101, January.
    22. Guidolin, Massimo & Timmermann, Allan, 2006. "Term structure of risk under alternative econometric specifications," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 285-308.
    23. Milan Ficura & Jiri Witzany, 2016. "Estimating Stochastic Volatility and Jumps Using High-Frequency Data and Bayesian Methods," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 66(4), pages 278-301, August.
    24. SUCARRAT, Genaro, 2006. "The first stage in Hendry’s reduction theory revisited," LIDAM Discussion Papers CORE 2006082, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    25. Robert Ślepaczuk & Grzegorz Zakrzewski, 2009. "High-Frequency and Model-Free Volatility Estimators," Working Papers 2009-13, Faculty of Economic Sciences, University of Warsaw.
    26. Olkhov, Victor, 2020. "Volatility Depend on Market Trades and Macro Theory," MPRA Paper 102434, University Library of Munich, Germany.
    27. Ariño, Miguel A. & Canela, Miguel A., 2006. "Study of the dollar-euro exchange rate," IESE Research Papers D/620, IESE Business School, revised 30 Mar 2006.
    28. Tim Bollerslev & Morten Ø. Nielsen & Per Houmann Frederiksen & Torben G. Andersen, 2008. "Continuous-time Models, Realized Volatilities, And Testable Distributional Implications For Daily Stock Returns," Working Paper 1173, Economics Department, Queen's University.
    29. Abramov, Vyacheslav & Klebaner, Fima, 2006. "Forecasting and testing a non-constant volatility," MPRA Paper 207, University Library of Munich, Germany.
    30. Allen, P. Geoffrey & Morzuch, Bernard J., 2006. "Twenty-five years of progress, problems, and conflicting evidence in econometric forecasting. What about the next 25 years?," International Journal of Forecasting, Elsevier, vol. 22(3), pages 475-492.
    31. David McMillan & Alan Speight, 2005. "Long-memory and heterogeneous components in high frequency Pacific-Basin exchange rate volatility," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 12(3), pages 199-226, September.
    32. Lux, Thomas & Morales-Arias, Leonardo, 2009. "Forecasting volatility under fractality, regime-switching, long memory and student-t innovations," Kiel Working Papers 1532, Kiel Institute for the World Economy (IfW Kiel).
    33. Suhejla Hoiti & Esfandiar Maasoumi & Michael McAleer & Daniel Slottje, 2005. "Measuring the Volatility in U.S. Treasury Benchmarks and Debt Instruments," DEA Working Papers 14, Universitat de les Illes Balears, Departament d'Economía Aplicada.
    34. Théoret, Raymond & Racicot, François-Éric, 2010. "Forecasting stochastic Volatility using the Kalman filter: an application to Canadian Interest Rates and Price-Earnings Ratio," MPRA Paper 35911, University Library of Munich, Germany.
    35. Francois-Éric Racicot & Raymond Théoret, 2005. "Quelques applications du filtre de Kalman en finance: estimation et prévision de la volatilité stochastique et du rapport cours-bénéfices," RePAd Working Paper Series UQO-DSA-wp0312005, Département des sciences administratives, UQO.
    36. Valeri Voev, 2009. "On the Economic Evaluation of Volatility Forecasts," CREATES Research Papers 2009-56, Department of Economics and Business Economics, Aarhus University.
    37. Qinkai Chen & Christian-Yann Robert, 2021. "Multivariate Realized Volatility Forecasting with Graph Neural Network," Papers 2112.09015, arXiv.org, revised Dec 2021.
    38. Patton, Andrew J., 2011. "Volatility forecast comparison using imperfect volatility proxies," Journal of Econometrics, Elsevier, vol. 160(1), pages 246-256, January.
    39. Andrew Clare & Roger Courtenay, 2001. "Assessing the impact of macroeconomic news announcements on securities prices under different monetary policy regimes," Bank of England working papers 125, Bank of England.
    40. Victor Olkhov, 2021. "To VaR, or Not to VaR, That is the Question," Papers 2101.08559, arXiv.org, revised Oct 2021.
    41. Bistra Radeva, 2019. "Stock price fluctuations and GARCH modelling of stock market indexes," Economics and computer science, Publishing house "Knowledge and business" Varna, issue 3, pages 6-19.
    42. Sizova, Natalia, 2011. "Integrated variance forecasting: Model based vs. reduced form," Journal of Econometrics, Elsevier, vol. 162(2), pages 294-311, June.
    43. Juliusz Jabłecki & Ryszard Kokoszczyński & Paweł Sakowski & Robert Ślepaczuk & Piotr Wójcik, 2014. "Does historical volatility term structure contain valuable in-formation for predicting volatility index futures?," Working Papers 2014-18, Faculty of Economic Sciences, University of Warsaw.
    44. Veiga, Helena, 2006. "Volatility forecasts: a continuous time model versus discrete time models," DES - Working Papers. Statistics and Econometrics. WS ws062509, Universidad Carlos III de Madrid. Departamento de Estadística.
    45. Vyacheslav Abramov & Fima Klebaner, 2007. "Estimation and Prediction of a Non-Constant Volatility," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 14(1), pages 1-23, March.
    46. Bretó, Carles & Veiga, Helena, 2011. "Forecasting volatility: does continuous time do better than discrete time?," DES - Working Papers. Statistics and Econometrics. WS ws112518, Universidad Carlos III de Madrid. Departamento de Estadística.

  52. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005. "Practical Volatility and Correlation Modeling for Financial Market Risk Management," NBER Working Papers 11069, National Bureau of Economic Research, Inc.

    Cited by:

    1. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
    2. Sofiane Aboura & Julien Chevallier, 2014. "Cross-Market Spillovers with ‘Volatility Surprise’," EconomiX Working Papers 2014-46, University of Paris Nanterre, EconomiX.
    3. Gregory Bauer & Keith Vorkink, 2007. "Multivariate Realized Stock Market Volatility," Staff Working Papers 07-20, Bank of Canada.
    4. Erie Febrian & Aldrin Herwany, 2010. "Volatility Forecasting Models and Market Co-Integration: A Study on South-East Asian Markets," Working Papers in Business, Management and Finance 201005, Department of Management and Business, Padjadjaran University, revised May 2010.
    5. Christophe Perignon & D. Smith, 2009. "The Level and Quality of Value-at-Risk Disclosure by Commercial Banks," Post-Print hal-00496102, HAL.
    6. Francis X. Diebold & Kamil Yilmaz, 2010. "Better to Give than to Receive: Predictive Directional Measurement of Volatility Spillovers," Koç University-TUSIAD Economic Research Forum Working Papers 1001, Koc University-TUSIAD Economic Research Forum, revised Mar 2010.
    7. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Jin Wu, 2005. "A Framework for Exploring the Macroeconomic Determinants of Systematic Risk," American Economic Review, American Economic Association, vol. 95(2), pages 398-404, May.
    8. David S. Bates, 2009. "U.S. Stock Market Crash Risk, 1926-2006," NBER Working Papers 14913, National Bureau of Economic Research, Inc.
    9. Gaisser, Sandra & Memmel, Christoph & Schmidt, Rafael & Wehn, Carsten, 2009. "Time dynamic and hierarchical dependence modelling of an aggregated portfolio of trading books: a multivariate nonparametric approach," Discussion Paper Series 2: Banking and Financial Studies 2009,07, Deutsche Bundesbank.
    10. Markus Bibinger & Lars Winkelmann, 2014. "Common price and volatility jumps in noisy high-frequency data," SFB 649 Discussion Papers SFB649DP2014-037, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    11. Erie Febrian & Aldrin Herwany, 2009. "Volatility Model for Financial Market Risk Management : An Analysis on JSX Index Return Covariance Matrix," Working Papers in Economics and Development Studies (WoPEDS) 200907, Department of Economics, Padjadjaran University, revised Sep 2009.
    12. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    13. McAleer, Michael & Medeiros, Marcelo C., 2008. "A multiple regime smooth transition Heterogeneous Autoregressive model for long memory and asymmetries," Journal of Econometrics, Elsevier, vol. 147(1), pages 104-119, November.
    14. Marc S. Paolella, 2017. "The Univariate Collapsing Method for Portfolio Optimization," Econometrics, MDPI, vol. 5(2), pages 1-33, May.
    15. Zhou, Xinmiao & Qian, Huanhuan & Pérez-Rodríguez, Jorge. V. & González López-Valcárcel, Beatriz, 2020. "Risk dependence and cointegration between pharmaceutical stock markets: The case of China and the USA," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    16. Ghorbel, Ahmed & Trabelsi, Abdelwahed, 2007. "Predictive Performance of Conditional Extreme Value Theory and Conventional Methods in Value at Risk Estimation," MPRA Paper 3963, University Library of Munich, Germany.
    17. Faheem Aslam & Paulo Ferreira & Khurrum Shahzad Mughal & Beenish Bashir, 2021. "Intraday Volatility Spillovers among European Financial Markets during COVID-19," IJFS, MDPI, vol. 9(1), pages 1-19, January.
    18. Erie Febrian & Aldrin Herwany, 2009. "Forecasting Stocks of Government Owned Companies (GOCS):Volatility Modeling," Working Papers in Economics and Development Studies (WoPEDS) 200908, Department of Economics, Padjadjaran University, revised Sep 2009.
    19. Barbara Bedowska-Sojka, 2017. "Evaluating the Accuracy of Time-varying Beta. The Evidence from Poland," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 17, pages 161-176.
    20. Krahnen, Jan-Pieter & Wilde, Christian, 2006. "Risk Transfer with CDOs and Systemic Risk in Banking," CEPR Discussion Papers 5618, C.E.P.R. Discussion Papers.
    21. Jean-Paul Laurent & Hassan Omidi Firouzi, 2022. "Market Risk and Volatility Weighted Historical Simulation After Basel III," Working Papers hal-03679434, HAL.
    22. Olkhov, Victor, 2022. "Introduction of the Market-Based Price Autocorrelation," MPRA Paper 112003, University Library of Munich, Germany.
    23. Li, Leon, 2017. "Testing and comparing the performance of dynamic variance and correlation models in value-at-risk estimation," The North American Journal of Economics and Finance, Elsevier, vol. 40(C), pages 116-135.
    24. Norman R. Swanson & Valentina Corradi & Walter Distaso, 2011. "Predictive Inference for Integrated Volatility," Departmental Working Papers 201109, Rutgers University, Department of Economics.
    25. Francis X. Diebold & Kamil Yilmaz, 2008. "Macroeconomic Volatility and Stock Market Volatility, World-Wide," PIER Working Paper Archive 08-031, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    26. Othmar M. Lehner, 2013. "Crowdfunding social ventures: a model and research agenda," Venture Capital, Taylor & Francis Journals, vol. 15(4), pages 289-311, October.
    27. O’Brien, James & Szerszeń, Paweł J., 2017. "An evaluation of bank measures for market risk before, during and after the financial crisis," Journal of Banking & Finance, Elsevier, vol. 80(C), pages 215-234.
    28. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2005. "Volatility forecasting," CFS Working Paper Series 2005/08, Center for Financial Studies (CFS).
    29. James M. O'Brien & Pawel J. Szerszen, 2014. "An Evaluation of Bank VaR Measures for Market Risk During and Before the Financial Crisis," Finance and Economics Discussion Series 2014-21, Board of Governors of the Federal Reserve System (U.S.).
    30. Detlef Seese & Christof Weinhardt & Frank Schlottmann (ed.), 2008. "Handbook on Information Technology in Finance," International Handbooks on Information Systems, Springer, number 978-3-540-49487-4, November.
    31. Yoontae Jeon & Thomas H. McCurdy, 2017. "Time-Varying Window Length for Correlation Forecasts," Econometrics, MDPI, vol. 5(4), pages 1-29, December.
    32. Jondeau, Eric, 2015. "The dynamics of squared returns under contemporaneous aggregation of GARCH models," Journal of Empirical Finance, Elsevier, vol. 32(C), pages 80-93.
    33. Bates, David S., 2012. "U.S. stock market crash risk, 1926–2010," Journal of Financial Economics, Elsevier, vol. 105(2), pages 229-259.
    34. Eric Hillebrand & Marcelo Cunha Medeiros, 2010. "Asymmetries, breaks, and long-range dependence: An estimation framework for daily realized volatility," Textos para discussão 578, Department of Economics PUC-Rio (Brazil).
    35. Gao, Jun & Gao, Xiang & Gu, Chen, 2023. "Forecasting European stock volatility: The role of the UK," International Review of Financial Analysis, Elsevier, vol. 89(C).
    36. Eric Jondeau, 2008. "Contemporaneous Aggregation of GARCH Models and Evaluation of the Aggregation Bias," Swiss Finance Institute Research Paper Series 08-06, Swiss Finance Institute.

  53. Campbell, Sean D. & Diebold, Francis X., 2005. "Stock returns and expected business conditions: Half a century of direct evidence," CFS Working Paper Series 2005/22, Center for Financial Studies (CFS).

    Cited by:

    1. Mikael C. Bergbrant & Patrick J. Kelly, 2015. "Macroeconomic Expectations and the Size, Value and Momentum Factors," Working Papers w0214, New Economic School (NES).
    2. Morana, Claudio, 2014. "Insights on the global macro-finance interface: Structural sources of risk factor fluctuations and the cross-section of expected stock returns," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 64-79.
    3. Diebold, Francis X. & Yilmaz, Kamil, 2015. "Financial and Macroeconomic Connectedness: A Network Approach to Measurement and Monitoring," OUP Catalogue, Oxford University Press, number 9780199338306.
    4. Bevilacqua, Mattia & Morelli, David & Tunaru, Radu, 2019. "The determinants of the model-free positive and negative volatilities," Journal of International Money and Finance, Elsevier, vol. 92(C), pages 1-24.
    5. Chava, Sudheer & Gallmeyer, Michael & Park, Heungju, 2015. "Credit conditions and stock return predictability," Journal of Monetary Economics, Elsevier, vol. 74(C), pages 117-132.
    6. Aleksandar M. Velkoski, 2015. "Restaurant Consumption as an Economic Indicator," Tourism Economics, , vol. 21(2), pages 325-339, April.
    7. Kirby, Chris, 2019. "The value premium and expected business conditions," Finance Research Letters, Elsevier, vol. 30(C), pages 360-366.
    8. Serhan Cevik & João Tovar Jalles, 2020. "This Changes Everything: Climate Shocks and Sovereign Bonds," Working Papers REM 2020/0132, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    9. Turan G. Bali & Hao Zhou, 2013. "Risk, Uncertainty, and Expected Returns," Koç University-TUSIAD Economic Research Forum Working Papers 1306, Koc University-TUSIAD Economic Research Forum.
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    1. González, Mariano & Nave, Juan & Rubio, Gonzalo, 2018. "Macroeconomic determinants of stock market betas," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 26-44.
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    3. Roberto Pascual & David Veredas, 2009. "Does the open limit order book matter in explaining informational volatility?," ULB Institutional Repository 2013/183777, ULB -- Universite Libre de Bruxelles.
    4. Hooper, Vincent J. & Ng, Kevin & Reeves, Jonathan J., 2008. "Quarterly beta forecasting: An evaluation," International Journal of Forecasting, Elsevier, vol. 24(3), pages 480-489.
    5. Degiannakis, Stavros & Filis, George & Kizys, Renatas, 2014. "The effects of oil price shocks on stock market volatility: Evidence from European data," MPRA Paper 96296, University Library of Munich, Germany.
    6. Aït-Sahalia, Yacine & Kalnina, Ilze & Xiu, Dacheng, 2020. "High-frequency factor models and regressions," Journal of Econometrics, Elsevier, vol. 216(1), pages 86-105.
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    8. Lillie Lam & Laurence Fung & Ip-wing Yu, 2009. "Forecasting a Large Dimensional Covariance Matrix of a Portfolio of Different Asset Classes," Working Papers 0901, Hong Kong Monetary Authority.
    9. Peter C. B. Phillips & Jun Yu, 2009. "Information Loss in Volatility Measurement with Flat Price Trading," Global COE Hi-Stat Discussion Paper Series gd08-039, Institute of Economic Research, Hitotsubashi University.
    10. Tolga Cenesizoglu & Denada Ibrushi, 2020. "Predicting Systematic Risk With Macroeconomic And Financial Variables," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 43(3), pages 649-673, August.
    11. Andersen, Torben G. & Riva, Raul & Thyrsgaard, Martin & Todorov, Viktor, 2023. "Intraday cross-sectional distributions of systematic risk," Journal of Econometrics, Elsevier, vol. 235(2), pages 1394-1418.
    12. Ilze KALNINA, 2015. "Inference for Nonparametric High-Frequency Estimators with an Application to Time Variation in Betas," Cahiers de recherche 13-2015, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
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    48. Chauvet, Marcelle & Senyuz, Zeynep & Yoldas, Emre, 2010. "What does financial volatility tell us about macroeconomic fluctuations?," MPRA Paper 34104, University Library of Munich, Germany, revised Jun 2011.
    49. Le Dinh Hac & Dinh Tran Ngoc Huy & Nguyen Ngoc Thach & Bui Minh Chuyen & Pham Thi Hong Nhung & Tran Duc Thang & Tran Tuan Anh, 2021. "Enhancing risk management culture for sustainable growth of Asia commercial bank -ACB in Vietnam under mixed effects of macro factors," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 8(3), pages 291-307, March.
    50. Cenesizoglu, Tolga & de Oliveira Ferrazoli Ribeiro, Fabio & Reeves, Jonathan J., 2017. "Beta forecasting at long horizons," International Journal of Forecasting, Elsevier, vol. 33(4), pages 936-957.
    51. Sascha Mergner, 2005. "Time-varying Beta Risk of Pan-European Sectors: A Comparison of Alternative Modeling Techniques," Finance 0509024, University Library of Munich, Germany.
    52. Hassan, Gazi & Hisham, Al refai, 2010. "Can Macroeconomic Factors Explain Equity Returns in the Long Run? The Case of Jordan," MPRA Paper 22713, University Library of Munich, Germany.
    53. Fredj Jawadi & Wael Louhichi & Abdoulkarim Idi Cheffou & Hachmi Ben Ameur, 2019. "Modeling time-varying beta in a sustainable stock market with a three-regime threshold GARCH model," Annals of Operations Research, Springer, vol. 281(1), pages 275-295, October.
    54. Samet Günay, 2017. "Risk Configuration of S&P 500 Industries: Sigma-risk and Alpha-risk Approximation," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 11(2), pages 196-221, May.
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    56. Dungey, Mardi & Henry, Olan T & Hvodzdyk, Lyudmyla, 2013. "The impact of jumps and thin trading on realized hedge ratios," Working Papers 2013-02, University of Tasmania, Tasmanian School of Business and Economics, revised 28 Mar 2013.
    57. Phoebe Koundouri & Nikolaos Kourogenis & Nikitas Pittis & Panagiotis Samartzis, 2015. "Factor Models as 'Explanatory Unifiers' versus 'Explanatory Ideals' of Empirical Regularities of Stock Returns," DEOS Working Papers 1507, Athens University of Economics and Business.
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    65. Richard Mawulawoe Ahadzie & Nagaratnam Jeyasreedharan, 2024. "Higher‐order moments and asset pricing in the Australian stock market," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 64(1), pages 75-128, March.
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    1. Lunina, Veronika, 2016. "Joint Modelling of Power Price, Temperature, and Hydrological Balance with a View towards Scenario Analysis," Working Papers 2016:30, Lund University, Department of Economics.
    2. Campbell, Sean D. & Diebold, Francis X., 2004. "Weather forecasting for weather derivatives," CFS Working Paper Series 2004/10, Center for Financial Studies (CFS).
    3. Bigerna, Simona, 2018. "Estimating temperature effects on the Italian electricity market," Energy Policy, Elsevier, vol. 118(C), pages 257-269.
    4. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
    5. Július Bemš & Caner Aydin, 2022. "Introduction to weather derivatives," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 11(3), May.
    6. Matthias Ritter, 2012. "Can the market forecast the weather better than meteorologists?," SFB 649 Discussion Papers SFB649DP2012-067, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    7. Zhang, Li, 2008. "Three essays on agricultural risk and insurance," ISU General Staff Papers 2008010108000016857, Iowa State University, Department of Economics.
    8. Atak, Alev & Linton, Oliver B. & Xiao, Zhijie, 2010. "A Semiparametric Panel Model for Unbalanced Data with Application to Climate Change in the United Kingdom," MPRA Paper 22079, University Library of Munich, Germany.
    9. Meng, Xiaochun & Taylor, James W., 2022. "Comparing probabilistic forecasts of the daily minimum and maximum temperature," International Journal of Forecasting, Elsevier, vol. 38(1), pages 267-281.
    10. Fred Espen Benth & Jurate Saltyte-Benth, 2005. "Stochastic Modelling of Temperature Variations with a View Towards Weather Derivatives," Applied Mathematical Finance, Taylor & Francis Journals, vol. 12(1), pages 53-85.
    11. Zhang, Yongli & Rolling, Craig & Yang, Yuhong, 2021. "Estimating and forecasting dynamic correlation matrices: A nonlinear common factor approach," Journal of Multivariate Analysis, Elsevier, vol. 183(C).
    12. Rui Zhou & Johnny Siu-Hang Li & Jeffrey Pai, 2019. "Pricing temperature derivatives with a filtered historical simulation approach," The European Journal of Finance, Taylor & Francis Journals, vol. 25(15), pages 1462-1484, October.
    13. Andrea Barth & Fred Espen Benth & Jurgen Potthoff, 2011. "Hedging of Spatial Temperature Risk with Market-Traded Futures," Applied Mathematical Finance, Taylor & Francis Journals, vol. 18(2), pages 93-117.
    14. Sun, Baojing & van Kooten, G. Cornelis, 2014. "Financial Weather Options for Crop Production," Working Papers 164323, University of Victoria, Resource Economics and Policy.
    15. Sun, Baojing, 2017. "Financial Weather Derivatives for Corn Production in Northeastern China: Modelling the Underlying Weather Index," Working Papers 257083, University of Victoria, Resource Economics and Policy.
    16. Fred Benth & Wolfgang Karl Härdle & Brenda López Cabrera, 2009. "Pricing of Asian temperature risk," SFB 649 Discussion Papers SFB649DP2009-046, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    17. Demers, Jean-Guy, 2009. "Multiple zone power forwards: A value at risk framework," Energy Economics, Elsevier, vol. 31(5), pages 714-726, September.
    18. Adam Clements & A S Hurn & K A Lindsay, 2008. "Developing analytical distributions for temperature indices for the purposes of pricing temperature-based weather derivatives," NCER Working Paper Series 34, National Centre for Econometric Research.
    19. Torro, Hipolit, 2007. "Forecasting Weekly Electricity Prices at Nord Pool," International Energy Markets Working Papers 7437, Fondazione Eni Enrico Mattei (FEEM).
    20. Daniel Preve, "undated". "Linear programming-based estimators in nonnegative autoregression," GRU Working Paper Series GRU_2016_001, City University of Hong Kong, Department of Economics and Finance, Global Research Unit.
    21. Cees Diks & Valentyn Panchenko & Dick van Dijk, 2008. "Partial Likelihood-Based Scoring Rules for Evaluating Density Forecasts in Tails," Discussion Papers 2008-10, School of Economics, The University of New South Wales.
    22. Rosella Castellano & Roy Cerqueti & Giulia Rotundo, 2020. "Exploring the financial risk of a temperature index: a fractional integrated approach," Annals of Operations Research, Springer, vol. 284(1), pages 225-242, January.
    23. Ostap Okhrin & Martin Odening & Wei Xu, 2013. "Systemic Weather Risk and Crop Insurance: The Case of China," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 80(2), pages 351-372, June.
    24. Dupuis, Debbie J., 2011. "Forecasting temperature to price CME temperature derivatives," International Journal of Forecasting, Elsevier, vol. 27(2), pages 602-618, April.
    25. Eckhard Platen & Jason West, 2003. "Fair Pricing of Weather Derivatives," Research Paper Series 106, Quantitative Finance Research Centre, University of Technology, Sydney.
    26. Sun, Baojing, 2017. "Financial Weather Derivatives for Corn Production in Northeastern China: Modelling the underlying Weather Index," Working Papers 263197, University of Victoria, Resource Economics and Policy.
    27. Ito, Ryoko, 2013. "Modeling Dynamic Diurnal Patterns in High-Frequency Financial Data," Cambridge Working Papers in Economics 1315, Faculty of Economics, University of Cambridge.
    28. Siamak Javadi & Abdullah‐Al Masum & Mohsen Aram & Ramesh P. Rao, 2023. "Climate change and corporate cash holdings: Global evidence," Financial Management, Financial Management Association International, vol. 52(2), pages 253-295, June.
    29. Huynh, Thanh D. & Nguyen, Thu Ha & Truong, Cameron, 2020. "Climate risk: The price of drought," Journal of Corporate Finance, Elsevier, vol. 65(C).
    30. Zhao, Xiaobing, 2011. "The Economic Cost of CO2 Emission Cuts," 2011 Annual Meeting, July 24-26, 2011, Pittsburgh, Pennsylvania 103413, Agricultural and Applied Economics Association.
    31. Musshoff, Oliver & Odening, Martin & Xu, Wei, 2005. "Zur Bewertung von Wetterderivaten als innovative Risikomanagementinstrumente in der Landwirtschaft," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 54(04), pages 1-13.
    32. Žmuk Berislav & Kovač Matej, 2020. "Ornstein-Uhlenbeck process and GARCH model for temperature forecasting in weather derivatives valuation," Croatian Review of Economic, Business and Social Statistics, Sciendo, vol. 6(1), pages 27-42, May.
    33. Chung-Li & Wei Zhu & Alexandre Dmitriev, 2009. "Variable Capacity Utilization, Ambient Temperature Shocks and Generation Asset Valuation," Discussion Papers 2009-14, School of Economics, The University of New South Wales.
    34. Ngoc Mai Tran & Maria Osipenko & Wolfgang Karl Härdle, 2014. "Principal Component Analysis in an Asymmetric Norm," SFB 649 Discussion Papers SFB649DP2014-001, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    35. Caporin, Massimiliano & Preś, Juliusz, 2012. "Modelling and forecasting wind speed intensity for weather risk management," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3459-3476.
    36. Cui, Hairong & Zhou, Ying & Dzandu, Michael D. & Tang, Yinshan & Lu, Xunfa, 2019. "Is temperature-index derivative suitable for China?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    37. Cees Diks & Valentyn Panchenko & Dick van Dijk, 2011. "Likelihood-based scoring rules for comparing density forecasts in tails," Post-Print hal-00834423, HAL.
    38. Balvers, Ronald & Du, Ding & Zhao, Xiaobing, 2012. "The Adverse Impact of Gradual Temperature Change on Capital Investment," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124676, Agricultural and Applied Economics Association.
    39. Dorfleitner, Gregor & Wimmer, Maximilian, 2010. "The pricing of temperature futures at the Chicago Mercantile Exchange," Journal of Banking & Finance, Elsevier, vol. 34(6), pages 1360-1370, June.
    40. Kyungsik Nam, 2021. "Nonlinear Cointegrating Regression of the Earth’s Surface Mean Temperature Anomalies on Total Radiative Forcing," Econometrics, MDPI, vol. 9(1), pages 1-25, February.
    41. Harrison Hong & Frank Weikai Li & Jiangmin Xu, 2016. "Climate Risks and Market Efficiency," NBER Working Papers 22890, National Bureau of Economic Research, Inc.
    42. Zhao, Jing & Guo, Yanling & Xiao, Xia & Wang, Jianzhou & Chi, Dezhong & Guo, Zhenhai, 2017. "Multi-step wind speed and power forecasts based on a WRF simulation and an optimized association method," Applied Energy, Elsevier, vol. 197(C), pages 183-202.
    43. Ahčan, Aleš, 2012. "Statistical analysis of model risk concerning temperature residuals and its impact on pricing weather derivatives," Insurance: Mathematics and Economics, Elsevier, vol. 50(1), pages 131-138.
    44. Groll, Andreas & López-Cabrera, Brenda & Meyer-Brandis, Thilo, 2016. "A consistent two-factor model for pricing temperature derivatives," Energy Economics, Elsevier, vol. 55(C), pages 112-126.
    45. Fred Espen Benth & Jūratė Šaltytė Benth & Steen Koekebakker, 2007. "Putting a Price on Temperature," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 34(4), pages 746-767, December.
    46. Javadi, Siamak & Masum, Abdullah-Al, 2021. "The impact of climate change on the cost of bank loans," Journal of Corporate Finance, Elsevier, vol. 69(C).
    47. Frank Schiller & Gerold Seidler & Maximilian Wimmer, 2012. "Temperature models for pricing weather derivatives," Quantitative Finance, Taylor & Francis Journals, vol. 12(3), pages 489-500, March.
    48. Wolfgang Karl Härdle & Brenda López Cabrera & Awdesch Melzer, 2021. "Pricing wind power futures," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(4), pages 1083-1102, August.
    49. Baojing Sun, 2017. "Financial Weather Derivatives for Corn Production in Northeastern China: Modelling the underlying Weather Index," Working Papers 2017-05, University of Victoria, Department of Economics, Resource Economics and Policy Analysis Research Group.
    50. Silvio M. Duarte Queiros & Evaldo M. F. Curado & Fernando D. Nobre, 2011. "Minding impacting events in a model of stochastic variance," Papers 1102.4819, arXiv.org, revised Feb 2011.
    51. Zhao, Jing & Guo, Zhen-Hai & Su, Zhong-Yue & Zhao, Zhi-Yuan & Xiao, Xia & Liu, Feng, 2016. "An improved multi-step forecasting model based on WRF ensembles and creative fuzzy systems for wind speed," Applied Energy, Elsevier, vol. 162(C), pages 808-826.
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    53. Martínez, Beatriz & Torró, Hipòlit, 2023. "Theory of storage implications in the European natural gas market," Journal of Commodity Markets, Elsevier, vol. 29(C).
    54. Turvey, Calum G. & Norton, Michael T., 2008. "An Internet-Based Tool for Weather Risk Management," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 37(1), pages 1-16, April.
    55. Turvey, Calum G. & Weersink, Alfons, 2005. "Pricing Weather Insurance with a Random Strike Price: An Application to the Ontario Ice Wine Harvest," 2005 Annual meeting, July 24-27, Providence, RI 19255, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    56. Wolfgang Karl Härdle & Maria Osipenko, 2011. "Spatial Risk Premium on Weather Derivatives and Hedging Weather Exposure in Electricity," SFB 649 Discussion Papers SFB649DP2011-013, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    57. Caiado, Jorge, 2007. "Forecasting water consumption in Spain using univariate time series models," MPRA Paper 6610, University Library of Munich, Germany.
    58. Balvers, Ronald & Du, Ding & Zhao, Xiaobing, 2017. "Temperature shocks and the cost of equity capital: Implications for climate change perceptions," Journal of Banking & Finance, Elsevier, vol. 77(C), pages 18-34.
    59. Nam, Kyungsik, 2021. "Investigating the effect of climate uncertainty on global commodity markets," Energy Economics, Elsevier, vol. 96(C).
    60. Mathias S. Kruttli & Brigitte Roth Tran & Sumudu W. Watugala, 2019. "Pricing Poseidon: Extreme Weather Uncertainty and Firm Return Dynamics," Finance and Economics Discussion Series 2019-054, Board of Governors of the Federal Reserve System (U.S.).
    61. Peng Li, 2021. "The Valuation of Weather Derivatives Using One Sided Crank–Nicolson Schemes," Computational Economics, Springer;Society for Computational Economics, vol. 58(3), pages 825-847, October.
    62. Musshoff, Oliver & Odening, Martin & Xu, Wei, 2006. "Modeling and Hedging Rain Risk," 2006 Annual meeting, July 23-26, Long Beach, CA 21050, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    63. Philipp Hell & Thilo Meyer-Brandis & Thorsten Rheinländer, 2012. "Consistent Factor Models For Temperature Markets," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 15(04), pages 1-24.
    64. Aur'elien Alfonsi & Nerea Vadillo, 2023. "Risk valuation of quanto derivatives on temperature and electricity," Papers 2310.07692, arXiv.org, revised Apr 2024.
    65. Zhao, Xiaobing & Du, Ding & Xiong, Jun & Springer, Abraham & Masek Lopez, Sharon R. & Winkler, Blake & Hubler, Kenedy, 2019. "The impact of forest restoration on agriculture in the Verde River watershed, Arizona, USA," Forest Policy and Economics, Elsevier, vol. 109(C).
    66. Zhao, Xiaobing & Fletcher, Jerald J., 2011. "A spatial–temporal optimization approach to watershed management: Acid mine drainage treatment in the Cheat River watershed, WV, USA," Ecological Modelling, Elsevier, vol. 222(9), pages 1580-1591.
    67. Wolfram Schlenker & Michael J. Roberts, 2008. "Estimating the Impact of Climate Change on Crop Yields: The Importance of Nonlinear Temperature Effects," NBER Working Papers 13799, National Bureau of Economic Research, Inc.
    68. Jr‐Wei Huang & Sharon S. Yang & Chuang‐Chang Chang, 2018. "Modeling temperature behaviors: Application to weather derivative valuation," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(9), pages 1152-1175, September.
    69. Anbarci, Nejat & Boyd III, John & Floehr, Eric & Lee, Jungmin & Song, Joon Jin, 2011. "Population and income sensitivity of private and public weather forecasting," Regional Science and Urban Economics, Elsevier, vol. 41(2), pages 124-133, March.
    70. Nairobi Nairobi & Edwin Russel & Ambya Ambya & Arif Darmawan & Mustofa Usman & Wamiliana Wamiliana, 2020. "Dynamic Modeling Data Export Oil and Gas and Non-Oil and Gas by ARMA(2,1)-GARCH(1,1) Model: Study of Indonesian s Export over the Years 2008-2019," International Journal of Energy Economics and Policy, Econjournals, vol. 10(6), pages 175-184.
    71. Francis X. Diebold & Glenn D. Rudebusch, 2019. "On the Evolution of U.S. Temperature Dynamics," Papers 1907.06303, arXiv.org, revised Jan 2021.
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    74. Fred Espen Benth & Anca Pircalabu, 2018. "A non-Gaussian Ornstein–Uhlenbeck model for pricing wind power futures," Applied Mathematical Finance, Taylor & Francis Journals, vol. 25(1), pages 36-65, January.
    75. Benth, Fred Espen & Taib, Che Mohd Imran Che, 2013. "On the speed towards the mean for continuous time autoregressive moving average processes with applications to energy markets," Energy Economics, Elsevier, vol. 40(C), pages 259-268.
    76. Fred Espen Benth & Jūratė Šaltytė Benth, 2012. "Modeling and Pricing in Financial Markets for Weather Derivatives," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 8457, January.
    77. Jeongin Lee & Jongwoo Choi & Wanki Park & Ilwoo Lee, 2023. "A Dual-Stage Solar Power Prediction Model That Reflects Uncertainties in Weather Forecasts," Energies, MDPI, vol. 16(21), pages 1-19, October.
    78. Yeny E. Rodríguez & Miguel A. Pérez-Uribe & Javier Contreras, 2021. "Wind Put Barrier Options Pricing Based on the Nordix Index," Energies, MDPI, vol. 14(4), pages 1-14, February.
    79. Ollech, Daniel, 2018. "Seasonal adjustment of daily time series," Discussion Papers 41/2018, Deutsche Bundesbank.
    80. Šaltytė Benth, Jūratė & Benth, Fred Espen, 2012. "A critical view on temperature modelling for application in weather derivatives markets," Energy Economics, Elsevier, vol. 34(2), pages 592-602.
    81. Chen, Gang & Roberts, Matthew C. & Thraen, Cameron S., 2006. "Managing Dairy Profit Risk Using Weather Derivatives," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 31(3), pages 1-14, December.
    82. Jorge Caiado, 2009. "Performance of combined double seasonal univariate time series models for forecasting water demand," CEMAPRE Working Papers 0903, Centre for Applied Mathematics and Economics (CEMAPRE), School of Economics and Management (ISEG), Technical University of Lisbon.
    83. Jacob Boudoukh & Matthew Richardson & YuQing Shen & Robert F. Whitelaw, 2003. "Do Asset Prices Reflect Fundamentals? Freshly Squeezed Evidence from the OJ Market," NBER Working Papers 9515, National Bureau of Economic Research, Inc.
    84. Janda, Karel & Vylezik, Tomas, 2011. "Financial Management of Weather Risk with Energy Derivatives," MPRA Paper 35037, University Library of Munich, Germany.
    85. Adam Clements & A S Hurn & K A Lindsay, 2008. "Estimating the Payoffs of Temperature-based Weather Derivatives," NCER Working Paper Series 33, National Centre for Econometric Research.
    86. Thordis L. Thorarinsdottir & Tilmann Gneiting, 2010. "Probabilistic forecasts of wind speed: ensemble model output statistics by using heteroscedastic censored regression," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 173(2), pages 371-388, April.
    87. Pai, Jeffrey & Ravishanker, Nalini, 2009. "A multivariate preconditioned conjugate gradient approach for maximum likelihood estimation in vector long memory processes," Statistics & Probability Letters, Elsevier, vol. 79(9), pages 1282-1289, May.
    88. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2005. "Volatility forecasting," CFS Working Paper Series 2005/08, Center for Financial Studies (CFS).
    89. Larsson, Karl & Green, Rikard & Benth, Fred Espen, 2023. "A stochastic time-series model for solar irradiation," Energy Economics, Elsevier, vol. 117(C).
    90. Sun, Baojing & van Kooten, G. Cornelis, 2015. "Financial weather derivatives for corn production in Northern China: A comparison of pricing methods," Journal of Empirical Finance, Elsevier, vol. 32(C), pages 201-209.
    91. Prabakaran, Sellamuthu & Garcia, Isabel C. & Mora, Jose U., 2020. "A temperature stochastic model for option pricing and its impacts on the electricity market," Economic Analysis and Policy, Elsevier, vol. 68(C), pages 58-77.
    92. Markus Herrmann & Martin Hibbeln, 2021. "Seasonality in catastrophe bonds and market‐implied catastrophe arrival frequencies," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 88(3), pages 785-818, September.
    93. Eirini Konstantinidi & Gkaren Papazian & George Skiadopoulos, 2015. "Modeling the Dynamics of Temperature with a View to Weather Derivatives," World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 17, pages 511-544, World Scientific Publishing Co. Pte. Ltd..
    94. Gneiting, Tilmann, 2011. "Quantiles as optimal point forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 197-207, April.
    95. González-Rivera, Gloria & Rodríguez Caballero, Carlos Vladimir & Ruiz Ortega, Esther, 2023. "Modelling intervals of minimum/maximum temperatures in the Iberian Peninsula," DES - Working Papers. Statistics and Econometrics. WS 37968, Universidad Carlos III de Madrid. Departamento de Estadística.
    96. Roberto Buizza & James W. Taylor, 2004. "A comparison of temperature density forecasts from GARCH and atmospheric models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(5), pages 337-355.
    97. Larsson, Karl, 2023. "Parametric heat wave insurance," Journal of Commodity Markets, Elsevier, vol. 31(C).
    98. Schlenker, Wolfram & Taylor, Charles A., 2021. "Market expectations of a warming climate," Journal of Financial Economics, Elsevier, vol. 142(2), pages 627-640.
    99. Monika Wieczorek-Kosmala, 2020. "Weather Risk Management in Energy Sector: The Polish Case," Energies, MDPI, vol. 13(4), pages 1-21, February.
    100. Alessio Giorgini & Rogemar S. Mamon & Marianito R. Rodrigo, 2021. "A Stochastic Harmonic Oscillator Temperature Model for the Valuation of Weather Derivatives," Mathematics, MDPI, vol. 9(22), pages 1-15, November.
    101. Xiaofeng Cao & Ostap Okhrin & Martin Odening & Matthias Ritter, 2015. "Modelling spatio-temporal variability of temperature," Computational Statistics, Springer, vol. 30(3), pages 745-766, September.
    102. Fred Espen Benth & Jūratė Šaltytė Benth & Steen Koekebakker, 2008. "Stochastic Modeling of Electricity and Related Markets," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 6811, January.
    103. Mu, Xiaoyi, 2007. "Weather, storage, and natural gas price dynamics: Fundamentals and volatility," Energy Economics, Elsevier, vol. 29(1), pages 46-63, January.
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    105. Baltuttis, Dennik & Töppel, Jannick & Tränkler, Timm & Wiethe, Christian, 2020. "Managing the risks of energy efficiency insurances in a portfolio context: An actuarial diversification approach," International Review of Financial Analysis, Elsevier, vol. 68(C).
    106. Dupuis, Debbie J., 2011. "Forecasting temperature to price CME temperature derivatives," International Journal of Forecasting, Elsevier, vol. 27(2), pages 602-618.
    107. Heng Xiong & Rogemar Mamon, 2018. "Putting a price tag on temperature," Computational Management Science, Springer, vol. 15(2), pages 259-296, June.
    108. Ohana, Steve, 2010. "Modeling global and local dependence in a pair of commodity forward curves with an application to the US natural gas and heating oil markets," Energy Economics, Elsevier, vol. 32(2), pages 373-388, March.
    109. Gneiting, Tilmann, 2011. "Quantiles as optimal point forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 197-207.
    110. Hélène Hamisultane, 2008. "Sunshine-Factor Model with Treshold GARCH for Predicting Temperature of Weather Contracts," Working Papers halshs-00355857, HAL.
    111. Cyr, Don & Kusy, Martin, 2007. "Identification of stochastic processes for an estimated icewine temperature hedging variable," Working Papers 37298, American Association of Wine Economists.
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    Cited by:

    1. Andrey Kudryavtsev, 2012. "Short-Term Stock Price Reversals May Be Reversed," International Journal of Business and Economic Sciences Applied Research (IJBESAR), International Hellenic University (IHU), Kavala Campus, Greece (formerly Eastern Macedonia and Thrace Institute of Technology - EMaTTech), vol. 5(3), pages 129-146, December.
    2. Mattiussi, V. & Iori, G., 2006. "Currency futures volatility during the 1997 East Asian crisis: an application of Fourier analysis," Working Papers 06/09, Department of Economics, City University London.
    3. Yoann Potiron & Per Mykland, 2015. "Estimation of integrated quadratic covariation with endogenous sampling times," Papers 1507.01033, arXiv.org, revised Nov 2016.
    4. Eric Jondeau & Michael Rockinger, 2006. "Optimal Portfolio Allocation under Higher Moments," European Financial Management, European Financial Management Association, vol. 12(1), pages 29-55, January.
    5. Aharon, David Y. & Qadan, Mahmoud, 2020. "When do retail investors pay attention to their trading platforms?," The North American Journal of Economics and Finance, Elsevier, vol. 53(C).
    6. Yin-Wong Cheung, 2007. "An empirical model of daily highs and lows," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 12(1), pages 1-20.
    7. Mueller, Philippe & Stathopoulos, Andreas & Vedolin, Andrea, 2017. "International correlation risk," LSE Research Online Documents on Economics 84140, London School of Economics and Political Science, LSE Library.
    8. Redouane Elkamhia & Denitsa Stefanova, 2011. "Dynamic Correlation or Tail Dependence Hedging for Portfolio Selection," Tinbergen Institute Discussion Papers 11-028/2/DSF10, Tinbergen Institute.
    9. Theodoros Diasakos, 2008. "Comparative Statics of Asset Prices," Carlo Alberto Notebooks 72, Collegio Carlo Alberto, revised 2011.
    10. Walid M.A. Ahmed, 2016. "Cross-border equity flows and market volatility: the case of Qatar Exchange," International Journal of Emerging Markets, Emerald Group Publishing Limited, vol. 11(3), pages 395-418, July.
    11. Vetter, Mathias & Podolskij, Mark, 2006. "Estimation of Volatility Functionals in the Simultaneous Presence of Microstructure Noise and Jumps," Technical Reports 2006,51, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    12. Silja Kinnebrock & Mark Podolskij, 2008. "An Econometric Analysis of Modulated Realised Covariance, Regression and Correlation in Noisy Diffusion Models," CREATES Research Papers 2008-23, Department of Economics and Business Economics, Aarhus University.
    13. Mueller, Philippe & Stathopoulos, Andreas & Vedolin, Andrea, 2014. "International correlation risk," LSE Research Online Documents on Economics 60955, London School of Economics and Political Science, LSE Library.
    14. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2002. "Parametric and Nonparametric Volatility Measurement," Center for Financial Institutions Working Papers 02-27, Wharton School Center for Financial Institutions, University of Pennsylvania.
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  57. Francis X. Diebold, 2004. "The Nobel Memorial Prize for Robert F. Engle," PIER Working Paper Archive 04-010, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.

    Cited by:

    1. Tim Bollerslev, 2008. "Glossary to ARCH (GARCH)," CREATES Research Papers 2008-49, Department of Economics and Business Economics, Aarhus University.
    2. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
    3. Joshua Aizenman & Brian Pinto, 2004. "Managing Volatility and Crises: A Practitioner's Guide Overview," NBER Working Papers 10602, National Bureau of Economic Research, Inc.
    4. Michele Vodret & Iacopo Mastromatteo & Bence Tóth & Michael Benzaquen, 2023. "Microfounding GARCH models and beyond: a Kyle-inspired model with adaptive agents," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 18(3), pages 599-625, July.
    5. Vargas, Gregorio A., 2006. "An Asymmetric Block Dynamic Conditional Correlation Multivariate GARCH Model," MPRA Paper 189, University Library of Munich, Germany, revised Aug 2006.
    6. Thomas C. Chiang & Jiandong Li, 2012. "Stock Returns and Risk: Evidence from Quantile," JRFM, MDPI, vol. 5(1), pages 1-39, December.
    7. Degiannakis, Stavros & Livada, Alexandra & Panas, Epaminondas, 2008. "Rolling-sampled parameters of ARCH and Levy-stable models," MPRA Paper 80464, University Library of Munich, Germany.
    8. Eduardo Rossi, 2010. "Univariate GARCH models: a survey (in Russian)," Quantile, Quantile, issue 8, pages 1-67, July.
    9. Mohamed BELHEDI & Ines SLAMA & Amine LAHIANI, 2015. "Tranmission Of International Shocks To An Emerging Small Open-Economy: Evidence From Tunisia," Region et Developpement, Region et Developpement, LEAD, Universite du Sud - Toulon Var, vol. 42, pages 231-258.
    10. Ahmad Muslim, 2014. "Analyzing volatility of rice price in Indonesia using ARCH/GARCH model," Economic Journal of Emerging Markets, Universitas Islam Indonesia, vol. 6(1), pages 1-12, April.
    11. Donna J. Bergenstock & Mary E. Deily & Larry W. Taylor, 2006. "A Cartel's Response to Cheating: An Empirical Investigation of the De Beers Diamond Empire," Southern Economic Journal, John Wiley & Sons, vol. 73(1), pages 173-189, July.
    12. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2005. "Volatility forecasting," CFS Working Paper Series 2005/08, Center for Financial Studies (CFS).
    13. Masih, Mansur & Algahtani, Ibrahim & De Mello, Lurion, 2010. "Price dynamics of crude oil and the regional ethylene markets," Energy Economics, Elsevier, vol. 32(6), pages 1435-1444, November.

  58. Andersen, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Wu, Jin, 2004. "Realized beta: Persistence and predictability," CFS Working Paper Series 2004/16, Center for Financial Studies (CFS).

    Cited by:

    1. Gregory Bauer & Keith Vorkink, 2007. "Multivariate Realized Stock Market Volatility," Staff Working Papers 07-20, Bank of Canada.
    2. Helmut Herwartz, 2006. "Econometric analysis of high frequency data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 90(1), pages 89-104, March.
    3. Alfred Mbairadjim Moussa & Jules Sadefo Kamdem & Arnold F. Shapiro & Michel Terraza, 2012. "Capital asset pricing model with fuzzy returns and hypothesis testing," Working Papers 12-33, LAMETA, Universtiy of Montpellier, revised Sep 2012.
    4. Stoja, Evarist & Polanski, Arnold & Nguyen, Linh H. & Pereverzin, Aleksandr, 2023. "Does systematic tail risk matter?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
    5. Robert Ślepaczuk & Grzegorz Zakrzewski, 2009. "High-Frequency and Model-Free Volatility Estimators," Working Papers 2009-13, Faculty of Economic Sciences, University of Warsaw.
    6. Haselmann, Rainer & Herwartz, Helmut, 2008. "Portfolio performance and the Euro: Prospects for new potential EMU members," Journal of International Money and Finance, Elsevier, vol. 27(2), pages 314-330, March.
    7. José L. B. Fernandes & Augusto Hasman & Juan Ignacio Peña, 2006. "Risk Premium: Insights Over The Threshold," Working Papers Series 126, Central Bank of Brazil, Research Department.
    8. Levich, Richard M. & Potì, Valerio, 2015. "Predictability and ‘good deals’ in currency markets," International Journal of Forecasting, Elsevier, vol. 31(2), pages 454-472.
    9. Nekhili, Ramzi & Bouri, Elie, 2023. "Higher-order moments and co-moments' contribution to spillover analysis and portfolio risk management," Energy Economics, Elsevier, vol. 119(C).
    10. Mbairadjim Moussa, A. & Sadefo Kamdem, J. & Shapiro, A.F. & Terraza, M., 2014. "CAPM with fuzzy returns and hypothesis testing," Insurance: Mathematics and Economics, Elsevier, vol. 55(C), pages 40-57.
    11. Dovern, Jonas, 2006. "Predicting GDP components: do leading indicators increase predictability?," Kiel Advanced Studies Working Papers 436, Kiel Institute for the World Economy (IfW Kiel).
    12. David W. Berger & Alain P. Chaboud & Erik Hjalmarsson & Edward Howorka, 2006. "What drives volatility persistence in the foreign exchange market?," International Finance Discussion Papers 862, Board of Governors of the Federal Reserve System (U.S.).
    13. Papavassiliou, Vassilios G., 2013. "A new method for estimating liquidity risk: Insights from a liquidity-adjusted CAPM framework," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 24(C), pages 184-197.

  59. Francis X. Diebold & Glenn D. Rudebusch & S. Boragan Aruoba, 2004. "The Macroeconomy and the Yield Curve: A Dynamic Latent Factor Approach," NBER Working Papers 10616, National Bureau of Economic Research, Inc.

    Cited by:

    1. Geert Bekaert & Seonghoon Cho & Antonio Moreno, 2005. "New-Keynesian Macroeconomics and the Term Structure," NBER Working Papers 11340, National Bureau of Economic Research, Inc.
    2. Matteo Barigozzi & Lorenzo Trapani, 2018. "Determining the dimension of factor structures in non-stationary large datasets," Papers 1806.03647, arXiv.org.
    3. Martins, Manuel M.F. & Afonso, António, 2010. "Level, slope, curvature of the sovereign yield curve, and fiscal behaviour," Working Paper Series 1276, European Central Bank.
    4. Moench, Emanuel & Soofi-Siavash, Soroosh, 2022. "What moves treasury yields?," Journal of Financial Economics, Elsevier, vol. 146(3), pages 1016-1043.
    5. Zhou, Siwen, 2019. "Assessing the Macroeconomic Impact of the ECB’s Asset Purchase Programme in a Dynamic Nelson–Siegel Modelling Framework," MPRA Paper 92530, University Library of Munich, Germany.
    6. Caldeira, João F. & Moura, Guilherme V. & Santos, André A.P., 2016. "Bond portfolio optimization using dynamic factor models," Journal of Empirical Finance, Elsevier, vol. 37(C), pages 128-158.
    7. Michael Pfarrhofer, 2019. "Measuring international uncertainty using global vector autoregressions with drifting parameters," Papers 1908.06325, arXiv.org, revised Dec 2019.
    8. Eric Hillebrand & Huiyu Huang & Tae-Hwy Lee & Canlin Li, 2018. "Using the Entire Yield Curve in Forecasting Output and Inflation," Econometrics, MDPI, vol. 6(3), pages 1-27, August.
    9. Matsumura, Marco & Moreira, Ajax & Vicente, José, 2011. "Forecasting the yield curve with linear factor models," International Review of Financial Analysis, Elsevier, vol. 20(5), pages 237-243.
    10. Giacomini, Raffaella & Ragusa, Giuseppe & Altavilla, Carlo, 2013. "Anchoring the Yield Curve Using Survey Expectations," CEPR Discussion Papers 9738, C.E.P.R. Discussion Papers.
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    423. J.Marcelo Ochoa, 2006. "An interpretation of an affine term structure model of Chile," Estudios de Economia, University of Chile, Department of Economics, vol. 33(2 Year 20), pages 155-184, December.
    424. M. Falagiarda & M. Marzo, 2012. "A DSGE model with Endogenous Term Structure," Working Papers wp830, Dipartimento Scienze Economiche, Universita' di Bologna.
    425. Haroon Mumtaz & Konstantinos Theodoridis, 2016. "Volatility Co-movement and the Great Moderation. An Empirical Analysis," Working Papers 804, Queen Mary University of London, School of Economics and Finance.
    426. Konstantinos Bisiotis & Stelios Psarakis & Athanasios N. Yannacopoulos, 2022. "Affine Term Structure Models: Applications in Portfolio Optimization and Change Point Detection," Mathematics, MDPI, vol. 10(21), pages 1-33, November.
    427. Almeida, Caio & Faria, Adriano, 2014. "Forecasting the Brazilian Term Structure Using Macroeconomic Factors," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 34(1), March.
    428. Michele Campolieti & Deborah Gefang & Gary Koop, 2013. "A new look at variation in employment growth in Canada," Working Papers 26145565, Lancaster University Management School, Economics Department.
    429. Loechel, Horst & Packham, Natalie & Walisch, Fabian, 2013. "Determinants of the onshore and offshore Chinese Government yield curves," Frankfurt School - Working Paper Series 202, Frankfurt School of Finance and Management.
    430. Martin M. Andreasen, 2019. "Explaining Bond Return Predictability in an Estimated New Keynesian Model," CREATES Research Papers 2019-11, Department of Economics and Business Economics, Aarhus University.
    431. Francesca Biagini & Alessandro Gnoatto & Maximilian Hartel, 2013. "Affine HJM Framework on $S_{d}^{+}$ and Long-Term Yield," Papers 1311.0688, arXiv.org, revised Aug 2015.
    432. Efthymios Argyropoulos & Nikolaos Elias & Dimitris Smyrnakis & Elias Tzavalis, 2021. "Can country-specific interest rate factors explain the forward premium anomaly?," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 45(2), pages 252-269, April.
    433. Shi Chen & Wolfgang Karl Härdle & Weining Wang, "undated". "Inflation Co-movement across Countries in Multi-maturity Term Structure: An Arbitrage-Free Approach," SFB 649 Discussion Papers SFB649DP2015-049, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    434. Cem Çakmakli, 2012. "Bayesian Semiparametric Dynamic Nelson-Siegel Model," Working Paper series 59_12, Rimini Centre for Economic Analysis, revised Sep 2012.
    435. Borus Jungbacker & Siem Jan Koopman, 2015. "Likelihood‐based dynamic factor analysis for measurement and forecasting," Econometrics Journal, Royal Economic Society, vol. 18(2), pages 1-21, June.
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    437. Rhea Choudhary, 2022. "AnalysingthespillovereffectsoftheSouthAfricanReserveBanksbondpurchaseprogramme," Working Papers 11039, South African Reserve Bank.
    438. Wali ULLAH & Khadija Malik BARI, 2018. "The Term Structure of Government Bond Yields in an Emerging Market," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 5-28, September.
    439. Polat, Onur & Ozkan, Ibrahim, 2019. "Transmission mechanisms of financial stress into economic activity in Turkey," Journal of Policy Modeling, Elsevier, vol. 41(2), pages 395-415.
    440. Borus Jungbacker & Siem Jan Koopman, 2008. "Likelihood-based Analysis for Dynamic Factor Models," Tinbergen Institute Discussion Papers 08-007/4, Tinbergen Institute, revised 20 Mar 2014.
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    443. Wali Ullah & Yasumasa Matsuda & Yoshihiko Tsukuda, 2013. "Term Structure Modeling and Forecasting of Government Bond Yields," Economic Papers, The Economic Society of Australia, vol. 32(4), pages 535-560, December.
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    445. Vides, José Carlos & Golpe, Antonio A. & Iglesias, Jesús, 2020. "The EHTS and the persistence in the spread reconsidered. A fractional cointegration approach," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 124-137.
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    447. Fernandes, Marcelo & Vieira, Fausto, 2019. "A dynamic Nelson–Siegel model with forward-looking macroeconomic factors for the yield curve in the US," Journal of Economic Dynamics and Control, Elsevier, vol. 106(C), pages 1-1.
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    449. Christos Ioannidis & Kook Ka, 2021. "Economic Policy Uncertainty and Bond Risk Premia," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 53(6), pages 1479-1522, September.
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  60. Andersen, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Vega, Clara, 2004. "Real-time price discovery in stock, bond and foreign exchange markets," CFS Working Paper Series 2004/19, Center for Financial Studies (CFS).

    Cited by:

    1. Michael Ehrmann & Marcel Fratzscher & Roberto Rigobon, 2011. "Stocks, bonds, money markets and exchange rates: measuring international financial transmission," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(6), pages 948-974, September.
    2. Mihaela NICOLAU, 2010. "Financial Markets Interactions between Economic Theory and Practice," Economics and Applied Informatics, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, issue 2, pages 27-36.
    3. Alenka Kavkler & Mejra Festić, 2011. "Modelling Stock Exchange Index Returns in Different GDP Growth Regimes," Prague Economic Papers, Prague University of Economics and Business, vol. 2011(1), pages 3-22.
    4. Bredin, Don & Hyde, Stuart & O'Reilly, Gerard, 2005. "European Monetary Policy Surprises: The Aggregate and Sectoral Stock Market Response," Research Technical Papers 10/RT/05, Central Bank of Ireland.
    5. Laurent E. Calvet & Adlai J. Fisher, 2005. "Multifrequency News and Stock Returns," NBER Working Papers 11441, National Bureau of Economic Research, Inc.
    6. Mo, Henry & Wu, Liuren, 2007. "International capital asset pricing: Evidence from options," Journal of Empirical Finance, Elsevier, vol. 14(4), pages 465-498, September.
    7. Saban Nazlioglu & Shawkat Hammoudeh & Rangan Gupta, 2015. "Volatility transmission between Islamic and conventional equity markets: evidence from causality-in-variance test," Applied Economics, Taylor & Francis Journals, vol. 47(46), pages 4996-5011, October.
    8. Victor Fang & Chien-Ting Lin & Kunaal Parbhoo, 2008. "Macroeconomic News, Business Cycles and Australian Financial Markets," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 15(3), pages 185-207, December.
    9. Faust, Jon & Rogers, John H. & Wang, Shing-Yi B. & Wright, Jonathan H., 2007. "The high-frequency response of exchange rates and interest rates to macroeconomic announcements," Journal of Monetary Economics, Elsevier, vol. 54(4), pages 1051-1068, May.
    10. Özer Karagedikli & Pierre L. Siklos, 2008. "Explaining Movements in the NZ Dollar - Central Bank Communication and the Surprise Element in Monetary Policy?," Reserve Bank of New Zealand Discussion Paper Series DP2008/02, Reserve Bank of New Zealand.
    11. Bent Jesper Christensen & Morten Ø. Nielsen & Thomas Busch, 2008. "The Role Of Implied Volatility In Forecasting Future Realized Volatility And Jumps In Foreign Exchange, Stock, And Bond Markets," Working Paper 1181, Economics Department, Queen's University.
    12. George Tauchen & Hao Zhou, 2006. "Realized jumps on financial markets and predicting credit spreads," Finance and Economics Discussion Series 2006-35, Board of Governors of the Federal Reserve System (U.S.).
    13. Schneider, Martin & Albuquerque, Rui & ,, 2006. "Global Private Information in International Equity Markets," CEPR Discussion Papers 5819, C.E.P.R. Discussion Papers.
    14. Joshua Hausman & Jon Wongswan, 2006. "Global asset prices and FOMC announcements," International Finance Discussion Papers 886, Board of Governors of the Federal Reserve System (U.S.).
    15. Marcel Fratzscher, 2011. "Capital Flows, Push versus Pull Factors and the Global Financial Crisis," NBER Working Papers 17357, National Bureau of Economic Research, Inc.
    16. Luc Arrondel & Hector Calvo Pardo & Xisco Oliver, 2007. "Temperant portfolio choice and background risk: evidence from France," PSE Working Papers halshs-00588069, HAL.
    17. Massimo Guidolin & Allan Timmerman, 2005. "An econometric model of nonlinear dynamics in the joint distribution of stock and bond returns," Working Papers 2005-003, Federal Reserve Bank of St. Louis.
    18. Hashimoto, Yuko & Ito, Takatoshi, 2010. "Effects of Japanese macroeconomic statistic announcements on the dollar/yen exchange rate: High-resolution picture," Journal of the Japanese and International Economies, Elsevier, vol. 24(3), pages 334-354, September.
    19. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005. "Practical Volatility and Correlation Modeling for Financial Market Risk Management," PIER Working Paper Archive 05-007, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    20. Oikarinen, Elias, 2006. "Price Linkages between Stock, Bond and Housing Markets - Evidence from Finnish Data," Discussion Papers 1004, The Research Institute of the Finnish Economy.
    21. Erenburg, Grigori & Kurov, Alexander & Lasser, Dennis J., 2006. "Trading around macroeconomic announcements: Are all traders created equal?," Journal of Financial Intermediation, Elsevier, vol. 15(4), pages 470-493, October.
    22. Christopher J. Neely, 2011. "A survey of announcement effects on foreign exchange volatility and jumps," Review, Federal Reserve Bank of St. Louis, vol. 93(Sep), pages 361-385.
    23. Özatay, Fatih & Özmen, Erdal & Sahinbeyoglu, Gülbin, 2009. "Emerging market sovereign spreads, global financial conditions and U.S. macroeconomic news," Economic Modelling, Elsevier, vol. 26(2), pages 526-531, March.
    24. Marc Simpson & Sanjay Ramchander & James Webb, 2007. "The Asymmetric Response of Equity REIT Returns to Inflation," The Journal of Real Estate Finance and Economics, Springer, vol. 34(4), pages 513-529, May.
    25. Gropp, Reint E. & Kadareja, Arjan, 2007. "Stale information, shocks and volatility," ZEW Discussion Papers 07-012, ZEW - Leibniz Centre for European Economic Research.
    26. Guo, Hui & Savickas, Robert, 2008. "Forecasting foreign exchange rates using idiosyncratic volatility," Journal of Banking & Finance, Elsevier, vol. 32(7), pages 1322-1332, July.
    27. Torben G. Andersen & Tim Bollerslev & Xin Huang, 2007. "A Reduced Form Framework for Modeling Volatility of Speculative Prices based on Realized Variation Measures," CREATES Research Papers 2007-14, Department of Economics and Business Economics, Aarhus University.
    28. Stefano d'Addona & Axel H. Kind, 2005. "International Stock-Bond Correlations in a Simple Affine Asset Pricing Model," Finance 0502018, University Library of Munich, Germany.
    29. Bollerslev, Tim & Law, Tzuo Hann & Tauchen, George, 2008. "Risk, jumps, and diversification," Journal of Econometrics, Elsevier, vol. 144(1), pages 234-256, May.
    30. Celine Gimet & Sandra Montchaud, 2016. "What Drives European Football Clubs’ Stock Returns and Volatility?," International Journal of the Economics of Business, Taylor & Francis Journals, vol. 23(3), pages 351-390, September.
    31. Beechey, Meredith J. & Wright, Jonathan H., 2009. "The high-frequency impact of news on long-term yields and forward rates: Is it real?," Journal of Monetary Economics, Elsevier, vol. 56(4), pages 535-544, May.
    32. Aaron Drew & Özer Karagedikli, 2008. "Some benefits of monetary policy transparency in New Zealand," Reserve Bank of New Zealand Discussion Paper Series DP2008/01, Reserve Bank of New Zealand.
    33. Alessandro BEBER & Michael W. BRANDT, 2004. "The Effects of Macroeconomic News on Beliefs and Preferences: Evidence from the Options Market," FAME Research Paper Series rp105, International Center for Financial Asset Management and Engineering.
    34. Troy Davig & Jeffrey R. Gerlach, 2006. "Monetary Policy, the Bond Market, and Changes in FOMC Communication Policy," Working Papers 31, Department of Economics, College of William and Mary.
    35. Michael Ehrmann & Marcel Fratzscher, 2009. "Global Financial Transmission of Monetary Policy Shocks," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(6), pages 739-759, December.
    36. Pietro Cova & Mr. Alessandro Rebucci & Mr. Akito Matsumoto & Massimiliano Pisani, 2008. "New Shocks, Exchange Rates and Equity Prices," IMF Working Papers 2008/284, International Monetary Fund.
    37. Michael Ehrmann & Marcel Fratzscher & Refet S. Gürkaynak & Eric T. Swanson, 2007. "Convergence and anchoring of yield curves in the Euro area," Working Paper Series 2007-24, Federal Reserve Bank of San Francisco.
    38. Paola Paiardini, 2010. "The Price Impact of Economic News, Private Information and Trading Intensity," Birkbeck Working Papers in Economics and Finance 1011, Birkbeck, Department of Economics, Mathematics & Statistics.
    39. Mizrach, Bruce & Neely, Christopher J., 2008. "Information shares in the US Treasury market," Journal of Banking & Finance, Elsevier, vol. 32(7), pages 1221-1233, July.
    40. Guglielmo Maria Caporale & Fabio Spagnolo & Nicola Spagnolo, 2015. "Macro News and Commodity Returns," Discussion Papers of DIW Berlin 1508, DIW Berlin, German Institute for Economic Research.
    41. Robert F. Engle & Jose Gonzalo Rangel, 2005. "The Spline GARCH Model for Unconditional Volatility and its Global Macroeconomic Causes," Working Papers 2005/13, Czech National Bank.
    42. Guglielmo Maria Caporale & Fabio Spagnolo & Nicola Spagnolo, 2014. "Macro News and Bond Yield Spreads in the Euro Area," CESifo Working Paper Series 5008, CESifo.
    43. Guidolin, Massimo & Timmermann, Allan, 2007. "Asset allocation under multivariate regime switching," Journal of Economic Dynamics and Control, Elsevier, vol. 31(11), pages 3503-3544, November.
    44. Lindner Axel, 2009. "Evaluating Communication Strategies for Public Agencies: Transparency, Opacity, and Secrecy," The B.E. Journal of Macroeconomics, De Gruyter, vol. 9(1), pages 1-18, July.
    45. Neil Shephard & Torben G. Andersen, 2008. "Stochastic Volatility: Origins and Overview," OFRC Working Papers Series 2008fe23, Oxford Financial Research Centre.
    46. Charlotte Christiansen & Angelo Ranaldo, 2007. "Realized bond—stock correlation: Macroeconomic announcement effects," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 27(5), pages 439-469, May.
    47. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2007. "Roughing It Up: Including Jump Components in the Measurement, Modeling, and Forecasting of Return Volatility," The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 701-720, November.
    48. Torben G. Andersen & Luca Benzoni, 2010. "Do Bonds Span Volatility Risk in the U.S. Treasury Market? A Specification Test for Affine Term Structure Models," Journal of Finance, American Finance Association, vol. 65(2), pages 603-653, April.
    49. Weihua Shi & Larry Eisenberg & Cheng-few Lee, 2009. "Intraday Patterns, Announcement Effects, and Volatility Persistence in the Japanese Government Bond Futures Market," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 12(01), pages 63-85.
    50. Wongswan, Jon, 2009. "The response of global equity indexes to U.S. monetary policy announcements," Journal of International Money and Finance, Elsevier, vol. 28(2), pages 344-365, March.
    51. George Jiang & Ingrid Lo & Adrien Verdelhan, 2008. "Information Shocks, Jumps, and Price Discovery -- Evidence from the U.S. Treasury Market," Staff Working Papers 08-22, Bank of Canada.
    52. Albuquerque, Rui & Vega, Clara, 2006. "Asymmetric Information in the Stock Market: Economic News and Co-movement," CEPR Discussion Papers 5598, C.E.P.R. Discussion Papers.
    53. Gregory H. Bauer & Clara Vega, 2006. "The monetary origins of asymmetric information in international equity markets," International Finance Discussion Papers 872, Board of Governors of the Federal Reserve System (U.S.).
    54. Alexandr Cerny, 2004. "Stock market integration and the speed of information transmission," CERGE-EI Working Papers wp242, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    55. Viceira, Luis M., 2012. "Bond risk, bond return volatility, and the term structure of interest rates," International Journal of Forecasting, Elsevier, vol. 28(1), pages 97-117.
    56. Tuysuz, Sukriye, 2007. "The asymmetric impact of macroeconomic announcements on U.S. Government bond rate level and volatility," MPRA Paper 5381, University Library of Munich, Germany.
    57. Andersen, Torben G. & Bollerslev, Tim & Dobrev, Dobrislav, 2007. "No-arbitrage semi-martingale restrictions for continuous-time volatility models subject to leverage effects, jumps and i.i.d. noise: Theory and testable distributional implications," Journal of Econometrics, Elsevier, vol. 138(1), pages 125-180, May.
    58. Paolo Pasquariello & Clara Vega, 2007. "Informed and Strategic Order Flow in the Bond Markets," The Review of Financial Studies, Society for Financial Studies, vol. 20(6), pages 1975-2019, November.
    59. Gourieroux, C. & Monfort, A. & Sufana, R., 2010. "International money and stock market contingent claims," Journal of International Money and Finance, Elsevier, vol. 29(8), pages 1727-1751, December.
    60. Pierre L. Siklos & Martin T. Bohl, 2008. "Policy words and policy deeds: the ECB and the euro," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 13(3), pages 247-265.
    61. Ghent, Andra, 2007. "Why do markets react badly to good news? Evidence from Fed Funds Futures," MPRA Paper 1708, University Library of Munich, Germany.
    62. Jon Faust & Jonathan H. Wright, 2008. "Efficient Prediction of Excess Returns," NBER Working Papers 14169, National Bureau of Economic Research, Inc.
    63. Dominique Guegan & Florian Ielpo, 2009. "Further evidence on the impact of economic news on interest rates," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00439820, HAL.
    64. Yuko Hashimoto & Takatoshi Ito, 2009. "Effects of Japanese Macroeconomic Announcements on the Dollar/Yen Exchange Rate: High-Resolution Picture," NBER Working Papers 15020, National Bureau of Economic Research, Inc.
    65. Hanno Lustig & Stijn Van Nieuwerburgh, 2005. "The Returns on Human Capital: Good News on Wall Street is Bad News on Main Street," NBER Working Papers 11564, National Bureau of Economic Research, Inc.
    66. Enzo Weber, 2007. "Volatility and Causality in Asia Pacific Financial Markets," SFB 649 Discussion Papers SFB649DP2007-004, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    67. Francis X. Diebold & Kamil Yilmaz, 2008. "Macroeconomic Volatility and Stock Market Volatility, World-Wide," PIER Working Paper Archive 08-031, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    68. Bruce Mizrach & Christopher J. Neely, 2007. "The microstructure of the U.S. treasury market," Working Papers 2007-052, Federal Reserve Bank of St. Louis.
    69. Bent Jesper Christensen & Morten Ø. Nielsen & Thomas Busch, 2006. "The Information Content Of Treasury Bond Options Concerning Future Volatility And Price Jumps," Working Paper 1188, Economics Department, Queen's University.
    70. Rui Albuquerque & Gregory Bauer & Martin Schneider, 2004. "Characterizing Asymmetric Information in International Equity Markets," International Finance 0405005, University Library of Munich, Germany.
    71. Patrice T. Robitaille & Jennifer E. Roush, 2006. "How do FOMC actions and U.S. macroeconomic data announcements move Brazilian sovereign yield spreads and stock prices?," International Finance Discussion Papers 868, Board of Governors of the Federal Reserve System (U.S.).
    72. Savaser, Tanseli, 2011. "Exchange rate response to macronews: Through the lens of microstructure," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 21(1), pages 107-126, February.
    73. Alessandro Beber & Michael W. Brandt, 2009. "Resolving Macroeconomic Uncertainty in Stock and Bond Markets," Review of Finance, European Finance Association, vol. 13(1), pages 1-45.
    74. Laakkonen Helinä & Lanne Markku, 2009. "Asymmetric News Effects on Exchange Rate Volatility: Good vs. Bad News in Good vs. Bad Times," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(1), pages 1-38, December.
    75. Condie, Scott & Ganguli, Jayant, 2017. "The pricing effects of ambiguous private information," Journal of Economic Theory, Elsevier, vol. 172(C), pages 512-557.
    76. Hui Guo & Robert Savickas, 2006. "Idiosyncratic volatility, economic fundamentals, and foreign exchange rates," Working Papers 2005-025, Federal Reserve Bank of St. Louis.
    77. Andersson, Magnus & Hansen, Lars Jul & Sebestyén, Szabolcs, 2006. "Which news moves the euro area bond market?," Working Paper Series 631, European Central Bank.
    78. Helena Chuliá & Hipòlit Torró, 2008. "The economic value of volatility transmission between the stock and bond markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 28(11), pages 1066-1094, November.
    79. Tamim Bayoumi & Andrew Swiston, 2010. "The Ties that Bind: Measuring International Bond Spillovers Using Inflation-Indexed Bond Yields," IMF Staff Papers, Palgrave Macmillan, vol. 57(2), pages 366-406, June.
    80. Herrmann, Klaus & Teis, Stefan & Yu, Weijun, 2014. "Components of intraday volatility and their prediction at different sampling frequencies with application to DAX and BUND futures," FAU Discussion Papers in Economics 15/2014, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    81. Lindner, Axel, 2008. "Evaluating communication strategies for public agencies: transparency, opacity, and secrecy," IWH Discussion Papers 8/2008, Halle Institute for Economic Research (IWH).
    82. Apergis, Nicholas, 2015. "The role of FOMC minutes for US asset prices before and after the 2008 crisis: Evidence from GARCH volatility modeling," The Quarterly Review of Economics and Finance, Elsevier, vol. 55(C), pages 100-107.
    83. Bent Jesper Christensen & Morten Ørregaard Nielsen, 2007. "The Effect of Long Memory in Volatility on Stock Market Fluctuations," The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 684-700, November.
    84. Laakkonen, Helinä, 2004. "The impact of macroeconomic news on exchange rate volatility," Bank of Finland Research Discussion Papers 24/2004, Bank of Finland.
    85. Bent Jesper Christensen & Morten Ø. Nielsen, 2005. "The Implied-realized Volatility Relation With Jumps In Underlying Asset Prices," Working Paper 1186, Economics Department, Queen's University.
    86. Jeffrey R. Gerlach, 2007. "Macroeconomic News And Stock Market Calendar And Weather Anomalies," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 30(2), pages 283-300, June.

  61. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Jin Wu, 2003. "Realized Beta: Persistence and Predictability," PIER Working Paper Archive 04-018, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 01 Mar 2004.

    Cited by:

    1. Gregory Bauer & Keith Vorkink, 2007. "Multivariate Realized Stock Market Volatility," Staff Working Papers 07-20, Bank of Canada.
    2. Helmut Herwartz, 2006. "Econometric analysis of high frequency data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 90(1), pages 89-104, March.
    3. Alfred Mbairadjim Moussa & Jules Sadefo Kamdem & Arnold F. Shapiro & Michel Terraza, 2012. "Capital asset pricing model with fuzzy returns and hypothesis testing," Working Papers 12-33, LAMETA, Universtiy of Montpellier, revised Sep 2012.
    4. Stoja, Evarist & Polanski, Arnold & Nguyen, Linh H. & Pereverzin, Aleksandr, 2023. "Does systematic tail risk matter?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
    5. Robert Ślepaczuk & Grzegorz Zakrzewski, 2009. "High-Frequency and Model-Free Volatility Estimators," Working Papers 2009-13, Faculty of Economic Sciences, University of Warsaw.
    6. Haselmann, Rainer & Herwartz, Helmut, 2008. "Portfolio performance and the Euro: Prospects for new potential EMU members," Journal of International Money and Finance, Elsevier, vol. 27(2), pages 314-330, March.
    7. José L. B. Fernandes & Augusto Hasman & Juan Ignacio Peña, 2006. "Risk Premium: Insights Over The Threshold," Working Papers Series 126, Central Bank of Brazil, Research Department.
    8. Levich, Richard M. & Potì, Valerio, 2015. "Predictability and ‘good deals’ in currency markets," International Journal of Forecasting, Elsevier, vol. 31(2), pages 454-472.
    9. Nekhili, Ramzi & Bouri, Elie, 2023. "Higher-order moments and co-moments' contribution to spillover analysis and portfolio risk management," Energy Economics, Elsevier, vol. 119(C).
    10. Mbairadjim Moussa, A. & Sadefo Kamdem, J. & Shapiro, A.F. & Terraza, M., 2014. "CAPM with fuzzy returns and hypothesis testing," Insurance: Mathematics and Economics, Elsevier, vol. 55(C), pages 40-57.
    11. Dovern, Jonas, 2006. "Predicting GDP components: do leading indicators increase predictability?," Kiel Advanced Studies Working Papers 436, Kiel Institute for the World Economy (IfW Kiel).
    12. David W. Berger & Alain P. Chaboud & Erik Hjalmarsson & Edward Howorka, 2006. "What drives volatility persistence in the foreign exchange market?," International Finance Discussion Papers 862, Board of Governors of the Federal Reserve System (U.S.).
    13. Papavassiliou, Vassilios G., 2013. "A new method for estimating liquidity risk: Insights from a liquidity-adjusted CAPM framework," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 24(C), pages 184-197.

  62. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2003. "Some Like it Smooth, and Some Like it Rough: Untangling Continuous and Jump Components in Measuring, Modeling, and Forecasting Asset Return Volatility," PIER Working Paper Archive 03-025, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 01 Sep 2003.

    Cited by:

    1. Nielsen, Morten Ørregaard & Frederiksen, Per, 2008. "Finite sample accuracy and choice of sampling frequency in integrated volatility estimation," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 265-286, March.
    2. Dominique Guegan & Florian Ielpo, 2007. "Further evidence on the impact of economic news on interest rates," Post-Print halshs-00188331, HAL.
    3. Laurent E. Calvet & Adlai J. Fisher, 2005. "Multifrequency News and Stock Returns," NBER Working Papers 11441, National Bureau of Economic Research, Inc.
    4. Mende, Alexander, 2005. "09/11 on the USD/EUR Foreign Exchange Market," Hannover Economic Papers (HEP) dp-312, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    5. Gregory Bauer & Keith Vorkink, 2007. "Multivariate Realized Stock Market Volatility," Staff Working Papers 07-20, Bank of Canada.
    6. Ole E. Barndorff-Nielsen & Sven Erik Graversen & Jean Jacod & Neil Shephard, 2005. "Limit theorems for bipower variation in financial econometrics," OFRC Working Papers Series 2005fe09, Oxford Financial Research Centre.
    7. Dufour, Jean-Marie & García, René & Taamouti, Abderrahim, 2008. "Measuring causality between volatility and returns with high-frequency data," UC3M Working papers. Economics we084422, Universidad Carlos III de Madrid. Departamento de Economía.
    8. Zheng, Tingguo & Zuo, Haomiao, 2013. "Reexamining the time-varying volatility spillover effects: A Markov switching causality approach," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 643-662.
    9. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005. "Practical Volatility and Correlation Modeling for Financial Market Risk Management," PIER Working Paper Archive 05-007, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    10. Ole E. Barndorff-Nielsen & Neil Shephard, 2005. "Variation, jumps, market frictions and high frequency data in financial econometrics," Economics Papers 2005-W16, Economics Group, Nuffield College, University of Oxford.
    11. Ole E. Barndorff-Nielsen & Neil Shephard, 2004. "Econometrics of testing for jumps in financial economics using bipower variationÂ," OFRC Working Papers Series 2004fe01, Oxford Financial Research Centre.
    12. Anderson, Heather M. & Vahid, Farshid, 2007. "Forecasting the Volatility of Australian Stock Returns: Do Common Factors Help?," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 76-90, January.
    13. Álvaro Cartea & Dimitrios Karyampas, 2009. "The Relationship Between the Volatility of Returns and the Number of Jumps in Financial Markets," Birkbeck Working Papers in Economics and Finance 0914, Birkbeck, Department of Economics, Mathematics & Statistics.
    14. Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "Predicting Volatility: Getting the Most out of Return Data Sampled at Different Frequencies," CIRANO Working Papers 2004s-19, CIRANO.
    15. Wanidwaranan, Phasin & Padungsaksawasdi, Chaiyuth, 2020. "The effect of return jumps on herd behavior," Journal of Behavioral and Experimental Finance, Elsevier, vol. 27(C).
    16. Lars Forsberg & Eric Ghysels, 2007. "Why Do Absolute Returns Predict Volatility So Well?," Journal of Financial Econometrics, Oxford University Press, vol. 5(1), pages 31-67.
    17. Ysusi Carla, 2006. "Detecting Jumps in High-Frequency Financial Series Using Multipower Variation," Working Papers 2006-10, Banco de México.
    18. Ghorbel, Ahmed & Trabelsi, Abdelwahed, 2007. "Predictive Performance of Conditional Extreme Value Theory and Conventional Methods in Value at Risk Estimation," MPRA Paper 3963, University Library of Munich, Germany.
    19. Wagner, Niklas & Szimayer, Alexander, 2004. "Local and spillover shocks in implied market volatility: evidence for the U.S. and Germany," Research in International Business and Finance, Elsevier, vol. 18(3), pages 237-251, September.
    20. Eric Ghysels & Arthur Sinko & Rossen Valkanov, 2007. "MIDAS Regressions: Further Results and New Directions," Econometric Reviews, Taylor & Francis Journals, vol. 26(1), pages 53-90.
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    24. Tim Leung & Theodore Zhao, 2024. "A Noisy Fractional Brownian Motion Model for Multiscale Correlation Analysis of High-Frequency Prices," Mathematics, MDPI, vol. 12(6), pages 1-21, March.
    25. Audrino, Francesco & Camponovo, Lorenzo & Roth, Constantin, 2015. "Testing the lag structure of assets’ realized volatility dynamics," Economics Working Paper Series 1501, University of St. Gallen, School of Economics and Political Science.
    26. Andrew Ang & Robert J. Hodrick & Yuhang Xing & Xiaoyan Zhang, 2004. "The Cross-Section of Volatility and Expected Returns," NBER Working Papers 10852, National Bureau of Economic Research, Inc.
    27. Basel Awartani & Valentina Corradi, 2004. "Testing and Modelling Market Microstructure Effects with an Application to the Dow Jones Industrial Average," Econometric Society 2004 North American Summer Meetings 487, Econometric Society.
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  63. Francis X. Diebold & Glenn D. Rudebusch & S. Boragan Aruoba, 2003. "The Macroeconomy and the Yield Curve: A Nonstructural Analysis," PIER Working Paper Archive 03-024, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.

    Cited by:

    1. Marco Lyrio & Hans Dewachter, 2004. "Filtering Long-Run Inflation Expectations with a Structural Macro Model of the Yield Curve," Computing in Economics and Finance 2004 188, Society for Computational Economics.
    2. Tao Wu & Glenn Rudebusch, 2004. "A Macro-Finance Model of the Term Structure, Monetary Policy, and the Economy," 2004 Meeting Papers 104, Society for Economic Dynamics.
    3. Daniel L. Thornton, 2005. "Predictions of short-term rates and the expectations hypothesis of the term structure of interest rates," Working Papers 2004-010, Federal Reserve Bank of St. Louis.
    4. Leo Krippner, 2005. "Investigating the Relationships between the Yield Curve, Output and Inflation using an Arbitrage-Free Version of the Nelson and Siegel Class of Yield Curve Models," Working Papers in Economics 05/02, University of Waikato.
    5. Beechey, Meredith, 2004. "Excess Sensitivity and Volatility of Long Interest Rates: The Role of Limited Information in Bond Markets," Working Paper Series 173, Sveriges Riksbank (Central Bank of Sweden).
    6. David Bolder & Grahame Johnson & Adam Metzler, 2004. "An Empirical Analysis of the Canadian Term Structure of Zero-Coupon Interest Rates," Staff Working Papers 04-48, Bank of Canada.
    7. Michael R. Wickens & Chiona Balfoussia, 2004. "Macroeconomic Sources of Risk in the Term Structure," CEIS Research Paper 61, Tor Vergata University, CEIS.
    8. Greg Duffee, 2005. "Term structure estimation without using latent factors," Computing in Economics and Finance 2005 103, Society for Computational Economics.
    9. Kanjilal, Kakali, 2013. "Factors causing movements of yield curve in India," Economic Modelling, Elsevier, vol. 31(C), pages 739-751.
    10. Leo Krippner, 2005. "An Intertemporally-Consistent and Arbitrage-Free Version of the Nelson and Siegel Class of Yield Curve Models," Working Papers in Economics 05/01, University of Waikato.
    11. Peter Spencer, 2007. "Macro volatility in a model of the UK Gilt edged bond market," Money Macro and Finance (MMF) Research Group Conference 2006 73, Money Macro and Finance Research Group.

  64. Francis X. Diebold & Canlin Li, 2003. "Forecasting the Term Structure of Government Bond Yields," NBER Working Papers 10048, National Bureau of Economic Research, Inc.

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    1. Driffill, John & Sola, Martin & Kenc, Turalay & Spagnolo, Fabio, 2004. "On Model Selection and Markov Switching: A Empirical Examination of Term Structure Models with Regime Shifts," CEPR Discussion Papers 4165, C.E.P.R. Discussion Papers.
    2. Andres Vesilind, 2003. "Application Of Fundamental Models To Money And Exchange Rate Markets," University of Tartu - Faculty of Economics and Business Administration Working Paper Series 22, Faculty of Economics and Business Administration, University of Tartu (Estonia).
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    5. Owadally, Iqbal & Jang, Chul & Clare, Andrew, 2021. "Optimal investment for a retirement plan with deferred annuities," Insurance: Mathematics and Economics, Elsevier, vol. 98(C), pages 51-62.
    6. Matteo Barigozzi & Lorenzo Trapani, 2018. "Determining the dimension of factor structures in non-stationary large datasets," Papers 1806.03647, arXiv.org.
    7. Martins, Manuel M.F. & Afonso, António, 2010. "Level, slope, curvature of the sovereign yield curve, and fiscal behaviour," Working Paper Series 1276, European Central Bank.
    8. Moench, Emanuel & Soofi-Siavash, Soroosh, 2022. "What moves treasury yields?," Journal of Financial Economics, Elsevier, vol. 146(3), pages 1016-1043.
    9. Pegoraro, F. & Siegel, A. F. & Tiozzo Pezzoli, L., 2014. "Specification Analysis of International Treasury Yield Curve Factors," Working papers 490, Banque de France.
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    11. Zhou, Siwen, 2019. "Assessing the Macroeconomic Impact of the ECB’s Asset Purchase Programme in a Dynamic Nelson–Siegel Modelling Framework," MPRA Paper 92530, University Library of Munich, Germany.
    12. Fernando Broner & Guido Lorenzoni & Sergio Schmuckler, 2006. "Why Do Emerging Economies Borrow Short Term?," 2006 Meeting Papers 841, Society for Economic Dynamics.
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    1. Michael Ehrmann & Marcel Fratzscher & Roberto Rigobon, 2011. "Stocks, bonds, money markets and exchange rates: measuring international financial transmission," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(6), pages 948-974, September.
    2. Mihaela NICOLAU, 2010. "Financial Markets Interactions between Economic Theory and Practice," Economics and Applied Informatics, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, issue 2, pages 27-36.
    3. Alenka Kavkler & Mejra Festić, 2011. "Modelling Stock Exchange Index Returns in Different GDP Growth Regimes," Prague Economic Papers, Prague University of Economics and Business, vol. 2011(1), pages 3-22.
    4. Bredin, Don & Hyde, Stuart & O'Reilly, Gerard, 2005. "European Monetary Policy Surprises: The Aggregate and Sectoral Stock Market Response," Research Technical Papers 10/RT/05, Central Bank of Ireland.
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    6. Mo, Henry & Wu, Liuren, 2007. "International capital asset pricing: Evidence from options," Journal of Empirical Finance, Elsevier, vol. 14(4), pages 465-498, September.
    7. Saban Nazlioglu & Shawkat Hammoudeh & Rangan Gupta, 2015. "Volatility transmission between Islamic and conventional equity markets: evidence from causality-in-variance test," Applied Economics, Taylor & Francis Journals, vol. 47(46), pages 4996-5011, October.
    8. Victor Fang & Chien-Ting Lin & Kunaal Parbhoo, 2008. "Macroeconomic News, Business Cycles and Australian Financial Markets," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 15(3), pages 185-207, December.
    9. Faust, Jon & Rogers, John H. & Wang, Shing-Yi B. & Wright, Jonathan H., 2007. "The high-frequency response of exchange rates and interest rates to macroeconomic announcements," Journal of Monetary Economics, Elsevier, vol. 54(4), pages 1051-1068, May.
    10. Özer Karagedikli & Pierre L. Siklos, 2008. "Explaining Movements in the NZ Dollar - Central Bank Communication and the Surprise Element in Monetary Policy?," Reserve Bank of New Zealand Discussion Paper Series DP2008/02, Reserve Bank of New Zealand.
    11. Bent Jesper Christensen & Morten Ø. Nielsen & Thomas Busch, 2008. "The Role Of Implied Volatility In Forecasting Future Realized Volatility And Jumps In Foreign Exchange, Stock, And Bond Markets," Working Paper 1181, Economics Department, Queen's University.
    12. George Tauchen & Hao Zhou, 2006. "Realized jumps on financial markets and predicting credit spreads," Finance and Economics Discussion Series 2006-35, Board of Governors of the Federal Reserve System (U.S.).
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    1. Lunina, Veronika, 2016. "Joint Modelling of Power Price, Temperature, and Hydrological Balance with a View towards Scenario Analysis," Working Papers 2016:30, Lund University, Department of Economics.
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    7. Zhang, Li, 2008. "Three essays on agricultural risk and insurance," ISU General Staff Papers 2008010108000016857, Iowa State University, Department of Economics.
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    45. Fred Espen Benth & Jūratė Šaltytė Benth & Steen Koekebakker, 2007. "Putting a Price on Temperature," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 34(4), pages 746-767, December.
    46. Javadi, Siamak & Masum, Abdullah-Al, 2021. "The impact of climate change on the cost of bank loans," Journal of Corporate Finance, Elsevier, vol. 69(C).
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    48. Wolfgang Karl Härdle & Brenda López Cabrera & Awdesch Melzer, 2021. "Pricing wind power futures," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(4), pages 1083-1102, August.
    49. Baojing Sun, 2017. "Financial Weather Derivatives for Corn Production in Northeastern China: Modelling the underlying Weather Index," Working Papers 2017-05, University of Victoria, Department of Economics, Resource Economics and Policy Analysis Research Group.
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    1543. Zhou, Dong-hai & Liu, Xiao-xing & Tang, Chun & Yang, Guang-yi, 2023. "Time-varying risk spillovers in Chinese stock market – New evidence from high-frequency data," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
    1544. Danyan Wen & Mengxi He & Yaojie Zhang & Yudong Wang, 2022. "Forecasting realized volatility of Chinese stock market: A simple but efficient truncated approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 230-251, March.
    1545. Nick James, 2021. "Evolutionary correlation, regime switching, spectral dynamics and optimal trading strategies for cryptocurrencies and equities," Papers 2112.15321, arXiv.org, revised Mar 2022.
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    1550. Jose Olmo, 2023. "A nonparametric predictive regression model using partitioning estimators based on Taylor expansions," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(3), pages 294-318, May.
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    1553. Daniel Felix Ahelegbey & Luis Carvalho & Eric D. Kolaczyk, 2020. "A Bayesian Covariance Graph And Latent Position Model For Multivariate Financial Time Series," DEM Working Papers Series 181, University of Pavia, Department of Economics and Management.
    1554. Urquhart, Andrew & McGroarty, Frank, 2016. "Are stock markets really efficient? Evidence of the adaptive market hypothesis," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 39-49.
    1555. Anine E. Bolko & Kim Christensen & Mikko S. Pakkanen & Bezirgen Veliyev, 2020. "Roughness in spot variance? A GMM approach for estimation of fractional log-normal stochastic volatility models using realized measures," CREATES Research Papers 2020-12, Department of Economics and Business Economics, Aarhus University.
    1556. Wesselhöfft, Niels & Härdle, Wolfgang Karl, 2019. "Estimating low sampling frequency risk measure by high-frequency data," IRTG 1792 Discussion Papers 2019-003, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    1557. Brause, Alexander, 2008. "Foreign exchange interventions in emerging market countries: New lessons from Argentina," W.E.P. - Würzburg Economic Papers 79, University of Würzburg, Department of Economics.
    1558. Haugom, Erik & Westgaard, Sjur & Solibakke, Per Bjarte & Lien, Gudbrand, 2011. "Realized volatility and the influence of market measures on predictability: Analysis of Nord Pool forward electricity data," Energy Economics, Elsevier, vol. 33(6), pages 1206-1215.
    1559. Torben G. Andersen & Luca Benzoni, 2008. "Realized volatility," Working Paper Series WP-08-14, Federal Reserve Bank of Chicago.
    1560. Mala Dutt & Sanjay Sehgal, 2018. "Domestic and International Information Linkages between Gold Spot and Futures Markets: An Empirical Study for India," Metamorphosis: A Journal of Management Research, , vol. 17(1), pages 1-17, June.
    1561. Chen, Wei-Peng & Choudhry, Taufiq & Wu, Chih-Chiang, 2013. "The extreme value in crude oil and US dollar markets," Journal of International Money and Finance, Elsevier, vol. 36(C), pages 191-210.
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    1564. Chun-Hung Chen & Wei-Choun Yu & Eric Zivot, 2009. "Predicting Stock Volatility Using After-Hours Information," Working Papers UWEC-2009-01, University of Washington, Department of Economics.
    1565. María García Centeno & Román Mínguez Salido, 2009. "Estimation of Asymmetric Stochastic Volatility Models for Stock-Exchange Index Returns," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 15(1), pages 71-87, February.
    1566. Lee, Hyunchul & Kim, Heeho, 2020. "Time varying integration of European stock markets and monetary drivers," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 369-385.
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    1569. Zhenwei Li & Jing Han & Yuping Song, 2020. "On the forecasting of high‐frequency financial time series based on ARIMA model improved by deep learning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(7), pages 1081-1097, November.
    1570. Wang, Yudong & Ma, Feng & Wei, Yu & Wu, Chongfeng, 2016. "Forecasting realized volatility in a changing world: A dynamic model averaging approach," Journal of Banking & Finance, Elsevier, vol. 64(C), pages 136-149.
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    1572. Grønborg, Niels S. & Lunde, Asger & Olesen, Kasper V. & Vander Elst, Harry, 2022. "Realizing correlations across asset classes," Journal of Financial Markets, Elsevier, vol. 59(PA).
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    Cited by:

    1. Tim Bollerslev & Michael Gibson & Hao Zhou, 2007. "Dynamic Estimation of Volatility Risk Premia and Investor Risk Aversion from Option-Implied and Realized Volatilities," CREATES Research Papers 2007-16, Department of Economics and Business Economics, Aarhus University.
    2. Anisha Ghosh & Oliver Linton, 2019. "Estimation with Mixed Data Frequencies: A Bias-Correction Approach," CeMMAP working papers CWP65/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Campbell, Sean D. & Diebold, Francis X., 2004. "Weather forecasting for weather derivatives," CFS Working Paper Series 2004/10, Center for Financial Studies (CFS).
    4. Degiannakis, Stavros & Floros, Christos, 2013. "Modeling CAC40 volatility using ultra-high frequency data," Research in International Business and Finance, Elsevier, vol. 28(C), pages 68-81.
    5. Ole E. Barndorff-Nielsen & Neil Shephard, 2001. "Econometric Analysis of Realised Covariation: High Frequency Covariance, Regression and Correlation in Financial Economics," Economics Papers 2002-W13, Economics Group, Nuffield College, University of Oxford, revised 18 Mar 2002.
    6. Athanasia Gavala & Nikolay Gospodinov & Deming Jiang, 2006. "Forecasting volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(6), pages 381-400.
    7. Laarni Bulan & Christopher Mayer & C. Tsuriel Somerville, "undated". "Irreversible Investment, Real Options, and Competition: Evidence from Real Estate Development," Zell/Lurie Center Working Papers 391, Wharton School Samuel Zell and Robert Lurie Real Estate Center, University of Pennsylvania.
    8. Sabrina Camargo & Silvio M. Duarte Queiros & Celia Anteneodo, 2013. "Bridging stylized facts in finance and data non-stationarities," Papers 1302.3197, arXiv.org, revised May 2013.
    9. George Tauchen & Hao Zhou, 2006. "Realized jumps on financial markets and predicting credit spreads," Finance and Economics Discussion Series 2006-35, Board of Governors of the Federal Reserve System (U.S.).
    10. Turgut Kısınbay, 2010. "Predictive ability of asymmetric volatility models at medium-term horizons," Applied Economics, Taylor & Francis Journals, vol. 42(30), pages 3813-3829.
    11. Christensen, Kim & Podolskij, Mark, 2006. "Range-Based Estimation of Quadratic Variation," Technical Reports 2006,37, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    12. Michael W. Brandt & Francis X. Diebold, 2006. "A No-Arbitrage Approach to Range-Based Estimation of Return Covariances and Correlations," The Journal of Business, University of Chicago Press, vol. 79(1), pages 61-74, January.
    13. Ole E. Barndorff-Nielsen & Elisa Nicolato & Neil Shephard, 2001. "Some recent developments in stochastic volatility modelling," Economics Papers 2001-W25, Economics Group, Nuffield College, University of Oxford.
    14. Sydney C. Ludvigson & Serena Ng, 2005. "The Empirical Risk-Return Relation: A Factor Analysis Approach," NBER Working Papers 11477, National Bureau of Economic Research, Inc.
    15. Nadhem Selmi & Nejib Hachicha, 2014. "Were Oil Price Markets the Source of Credit Crisis in European Countries? Evidence Using a VAR-MGARCH-DCC Model," International Journal of Energy Economics and Policy, Econjournals, vol. 4(2), pages 169-177.
    16. Lars Forsberg & Tim Bollerslev, 2002. "Bridging the gap between the distribution of realized (ECU) volatility and ARCH modelling (of the Euro): the GARCH-NIG model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 535-548.
    17. Li, Handong & Cao, Shi-Nan & Wang, Yan, 2010. "The properties and mechanism of long-term memory in nonparametric volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(16), pages 3254-3259.
    18. Bollerslev, Tim & Law, Tzuo Hann & Tauchen, George, 2008. "Risk, jumps, and diversification," Journal of Econometrics, Elsevier, vol. 144(1), pages 234-256, May.
    19. Peter Christoffersen & Francis X. Diebold, 2002. "Financial Asset Returns, Market Timing, and Volatility Dynamics," CIRANO Working Papers 2002s-02, CIRANO.
    20. Carol Alexander & Emese Lazar, 2006. "Normal mixture GARCH(1,1): applications to exchange rate modelling," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(3), pages 307-336, April.
    21. ANDERSEN, Torben G. & BOLLERSLEV, Tim & MEDDAHI, Nour, 2002. "Correcting the Errors : A Note on Volatility Forecast Evaluation Based on High-Frequency Data and Realized Volatilities," Cahiers de recherche 2002-21, Universite de Montreal, Departement de sciences economiques.
    22. Sean D. Campbell & Canlin Li, 2004. "Alternative estimates of the presidential premium," Finance and Economics Discussion Series 2004-69, Board of Governors of the Federal Reserve System (U.S.).
    23. Yi, Chae-Deug, 2020. "Jump probability using volatility periodicity filters in US Dollar/Euro exchange rates," The North American Journal of Economics and Finance, Elsevier, vol. 53(C).
    24. Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "Predicting Volatility: Getting the Most out of Return Data Sampled at Different Frequencies," CIRANO Working Papers 2004s-19, CIRANO.
    25. Fornari, Fabio, 2010. "Assessing the compensation for volatility risk implicit in interest rate derivatives," Journal of Empirical Finance, Elsevier, vol. 17(4), pages 722-743, September.
    26. Ghosh, Anisha & Linton, Oliver, 2007. "Consistent estimation of the risk-return tradeoff in the presence of measurement error," LSE Research Online Documents on Economics 24506, London School of Economics and Political Science, LSE Library.
    27. Juan Manuel Julio & Norberto Rodríguez & Hector Zárate, 2005. "Estimating the COP Exchange Rate Volatility Smile and the Market Effect of Central Bank Interventions: A CHARN Approach," Borradores de Economia 347, Banco de la Republica de Colombia.
    28. Tim Bollerslev & Hao Zhou, 2003. "Volatility puzzles: a unified framework for gauging return-volatility regressions," Finance and Economics Discussion Series 2003-40, Board of Governors of the Federal Reserve System (U.S.).
    29. Andersen, Torben G. & Dobrev, Dobrislav & Schaumburg, Ernst, 2012. "Jump-robust volatility estimation using nearest neighbor truncation," Journal of Econometrics, Elsevier, vol. 169(1), pages 75-93.
    30. Bansal, Ravi & Khatchatrian, Varoujan & Yaron, Amir, 2005. "Interpretable asset markets?," European Economic Review, Elsevier, vol. 49(3), pages 531-560, April.
    31. Robert F. Engle & Giampiero M. Gallo, 2003. "A Multiple Indicators Model For Volatility Using Intra-Daily Data," Econometrics Working Papers Archive wp2003_07, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    32. Degiannakis, Stavros, 2004. "Volatility Forecasting: Evidence from a Fractional Integrated Asymmetric Power ARCH Skewed-t Model," MPRA Paper 96330, University Library of Munich, Germany.
    33. Ceylan, Ozcan, 2012. "Time-Varying Volatility Asymmetry: A Conditioned HAR-RV(CJ) EGARCH-M Model," GIAM Working Papers 12-4, Galatasaray University Economic Research Center.
    34. Olkhov, Victor, 2020. "Volatility Depend on Market Trades and Macro Theory," MPRA Paper 102434, University Library of Munich, Germany.
    35. Jeremy Large, 2005. "Estimating quadratic variation when quoted prices jump by a constant increment," Economics Papers 2005-W05, Economics Group, Nuffield College, University of Oxford.
    36. YI, Chae-Deug, 2023. "Exchange rate volatility and intraday jump probability with periodicity filters using a local robust variance," Finance Research Letters, Elsevier, vol. 55(PA).
    37. Zagaglia, Paolo, 2008. "Money-market segmentation in the euro area: what has changed during the turmoil?," Bank of Finland Research Discussion Papers 23/2008, Bank of Finland.
    38. Haselmann, Rainer & Helmut, Herwartz, 2005. "The Introduction of the Euro and its Effects on Investment Decisions," Economics Working Papers 2005-15, Christian-Albrechts-University of Kiel, Department of Economics.
    39. Ole E. Barndorff-Nielsen & Neil Shephard, 2002. "Estimating quadratic variation using realized variance," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 457-477.
    40. Brousseau, Vincent & Durré, Alain, 2013. "Interest rate volatility: a consol rate-based measure," Working Paper Series 1505, European Central Bank.
    41. Martin Martens & Dick van Dijk & Michiel de Pooter, 2004. "Modeling and Forecasting S&P 500 Volatility: Long Memory, Structural Breaks and Nonlinearity," Tinbergen Institute Discussion Papers 04-067/4, Tinbergen Institute.
    42. Henker, Thomas & Husodo, Zaäfri A., 2010. "Noise and efficient variance in the Indonesia Stock Exchange," Pacific-Basin Finance Journal, Elsevier, vol. 18(2), pages 199-216, April.
    43. Frowin Schulz & Karl Mosler, 2011. "The effect of infrequent trading on detecting price jumps," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(1), pages 27-58, March.
    44. Julian Pareja Vasseur & Juan Giraldo Cerón & Santiago Zapata Valencia, 2017. "Market Risk, Non-parametric Methods: Hong-Kong Case," Economia Coyuntural,Revista de temas de perspectivas y coyuntura, Instituto de Investigaciones Economicas y Sociales 'Jose Ortiz Mercado' (IIES-JOM), Facultad de Ciencias Economicas, Administrativas y Financieras, Universidad Autonoma Gabriel Rene Moreno, vol. 2(4), pages 45-80.
    45. Ole E. Barndorff-Nielsen & Bent Nielsen & Neil Shephard & Carla Ysusi, 2002. "Measuring and forecasting financial variability using realised variance with and without a model," Economics Papers 2002-W21, Economics Group, Nuffield College, University of Oxford.
    46. René Garcia & Eric Ghysels & Eric Renault, 2004. "The Econometrics of Option Pricing," CIRANO Working Papers 2004s-04, CIRANO.
    47. Werner, Thomas & Stapf, Jelena, 2003. "How wacky is the DAX? The changing structure of German stock market volatility," Discussion Paper Series 1: Economic Studies 2003,18, Deutsche Bundesbank.
    48. B. Jungbacker & S.J. Koopman, 2005. "Model-based Measurement of Actual Volatility in High-Frequency Data," Tinbergen Institute Discussion Papers 05-002/4, Tinbergen Institute.
    49. Jianqing Fan & Yingying Fan & Jinchi Lv, 0. "Aggregation of Nonparametric Estimators for Volatility Matrix," Journal of Financial Econometrics, Oxford University Press, vol. 5(3), pages 321-357.
    50. Hellström, Jörgen & Lönnbark, Carl, 2011. "Identi�cation of jumps in �financial price series," MPRA Paper 30977, University Library of Munich, Germany.
    51. Fornari, Fabio, 2008. "Assessing the compensation for volatility risk implicit in interest rate derivatives," Working Paper Series 859, European Central Bank.
    52. Amir Safari & Detlef Seese, 2009. "Non-parametric estimation of a multiscale CHARN model using SVR," Quantitative Finance, Taylor & Francis Journals, vol. 9(1), pages 105-121.
    53. Patton, Andrew J., 2011. "Volatility forecast comparison using imperfect volatility proxies," Journal of Econometrics, Elsevier, vol. 160(1), pages 246-256, January.
    54. E. C. Brechmann & M. Heiden & Y. Okhrin, 2018. "A multivariate volatility vine copula model," Econometric Reviews, Taylor & Francis Journals, vol. 37(4), pages 281-308, April.
    55. Daniel Jubinski & Amy F. Lipton, 2012. "Equity volatility, bond yields, and yield spreads," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 32(5), pages 480-503, May.
    56. Christensen, Kim & Podolskij, Mark, 2007. "Realized range-based estimation of integrated variance," Journal of Econometrics, Elsevier, vol. 141(2), pages 323-349, December.
    57. Hyeong-Ohk Bae & Seung-Yeal Ha & Yongsik Kim & Hyuncheul Lim & Jane Yoo, 2020. "Volatility Flocking by Cucker–Smale Mechanism in Financial Markets," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 27(3), pages 387-414, September.
    58. Degiannakis, Stavros & Xekalaki, Evdokia, 2004. "Autoregressive Conditional Heteroskedasticity (ARCH) Models: A Review," MPRA Paper 80487, University Library of Munich, Germany.
    59. Fornari, Fabio & Mele, Antonio, 2006. "Approximating volatility diffusions with CEV-ARCH models," Journal of Economic Dynamics and Control, Elsevier, vol. 30(6), pages 931-966, June.
    60. Elena Andreou & Eric Ghysels, 2004. "Monitoring for Disruptions in Financial Markets," CIRANO Working Papers 2004s-26, CIRANO.
    61. Chun-Hung Chen & Wei-Choun Yu & Eric Zivot, 2009. "Predicting Stock Volatility Using After-Hours Information," Working Papers UWEC-2009-01, University of Washington, Department of Economics.
    62. Ole E. Barndorff-Nielsen & Neil Shephard, 2001. "How accurate is the asymptotic approximation to the distribution of realised volatility?," Economics Papers 2001-W16, Economics Group, Nuffield College, University of Oxford.

  72. Peter Christoffersen & Francis X. Diebold, 2002. "Financial Asset Returns, Market Timing, and Volatility Dynamics," CIRANO Working Papers 2002s-02, CIRANO.

    Cited by:

    1. Jaehun Chung & Yongmiao Hong, 2007. "Model-free evaluation of directional predictability in foreign exchange markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(5), pages 855-889.
    2. Ayedi Ahmed & Marjène Gana & Stéphane Goutte & Khaled Guesmi, 2023. "Managing Portfolio Risk During the BREXIT Crisis: A Cross-Quantilogram Analysis of Stock Markets and Commodities Across European Countries, the US, and BRICS," Working Papers halshs-04068651, HAL.
    3. Heejoon Han & Oliver Linton & Tatsushi Oka & Yoon-Jae Whang, 2014. "The Cross-Quantilogram: Measuring Quantile Dependence and Testing Directional Predictability between Time Series," Cambridge Working Papers in Economics 1452, Faculty of Economics, University of Cambridge.
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    1. Ignacio Arango & Diego A. Agudelo, 2017. "How does information disclosure affect liquidity?Evidence from an Emerging Market," Documentos de Trabajo de Valor Público 16990, Universidad EAFIT.
    2. Wang, Jianxin, 2007. "Foreign equity trading and emerging market volatility: Evidence from Indonesia and Thailand," Journal of Development Economics, Elsevier, vol. 84(2), pages 798-811, November.
    3. Galina Hale & Assaf Razin & Hui Tong, 2009. "The impact of creditor protection on stock prices in the presence of credit crunches," Proceedings, Federal Reserve Bank of San Francisco, issue Jan.
    4. Pan, Jun, 2002. "The jump-risk premia implicit in options: evidence from an integrated time-series study," Journal of Financial Economics, Elsevier, vol. 63(1), pages 3-50, January.
    5. Diego A. Agudelo & Ignacio Arango, 2017. "How does information disclosure affect liquidity? Evidence from an Emerging Market," Documentos de Trabajo de Valor Público 16944, Universidad EAFIT.
    6. Arango, Ignacio & Agudelo, Diego A., 2019. "How does information disclosure affect liquidity? Evidence from an emerging market," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    7. Siddique, Akhtar R., 2003. "Common asset pricing factors in volatilities and returns in futures markets," Journal of Banking & Finance, Elsevier, vol. 27(12), pages 2347-2368, December.

  75. Francis X. Diebold & Atsushi Inoue, 2000. "Long Memory and Regime Switching," NBER Technical Working Papers 0264, National Bureau of Economic Research, Inc.

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    1. Eric Hillebrand & Gunther Schnabl & Yasemin Ulu, 2006. "Japanese Foreign Exchange Intervention and the Yen/Dollar Exchange Rate: A Simultaneous Equations Approach Using Realized Volatility," CESifo Working Paper Series 1766, CESifo.
    2. Chen, Xiaohong & Hansen, Lars Peter & Carrasco, Marine, 2008. "Nonlinearity and Temporal Dependence," Working Papers 48, Yale University, Department of Economics.
    3. J. Cuñado & L. Gil-Alana & F. Gracia, 2009. "US stock market volatility persistence: evidence before and after the burst of the IT bubble," Review of Quantitative Finance and Accounting, Springer, vol. 33(3), pages 233-252, October.
    4. Abi Morshed, Alaa & Andreou, E. & Boldea, Otilia, 2016. "Structural Break Tests Robust to Regression Misspecification," Discussion Paper 2016-019, Tilburg University, Center for Economic Research.
    5. Chin Wen Cheong, 2010. "Estimating the Hurst parameter in financial time series via heuristic approaches," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(2), pages 201-214.
    6. Gürtler, Marc & Rauh, Ronald, 2012. "Challenging traditional risk models by a non-stationary approach with nonparametric heteroscedasticity," Working Papers IF41V1, Technische Universität Braunschweig, Institute of Finance.
    7. Morten Ø. Nielsen & Per Houmann Frederiksen, 2005. "Finite Sample Comparison Of Parametric, Semiparametric, And Wavelet Estimators Of Fractional Integration," Working Paper 1189, Economics Department, Queen's University.
    8. Haldrup, Niels & Nielsen, Frank S. & Nielsen, Morten Ørregaard, 2010. "A vector autoregressive model for electricity prices subject to long memory and regime switching," Energy Economics, Elsevier, vol. 32(5), pages 1044-1058, September.
    9. Geoffrey Ngene & Charles Lambert & Ali Darrat, 2015. "Testing Long Memory in the Presence of Structural Breaks: An Application to Regional and National Housing Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 50(4), pages 465-483, May.
    10. Monge, Manuel & Gil-Alana, Luis A. & Pérez de Gracia, Fernando, 2017. "U.S. shale oil production and WTI prices behaviour," Energy, Elsevier, vol. 141(C), pages 12-19.
    11. Claudio Morana, 2010. "Heteroskedastic Factor Vector Autoregressive Estimation of Persistent and Non Persistent Processes Subject to Structural Breaks," ICER Working Papers - Applied Mathematics Series 36-2010, ICER - International Centre for Economic Research.
    12. Carlos Barros & Luis Gil-Alana, 2012. "Inflation forecasting in Angola: a fractional approach," CEsA Working Papers 103, CEsA - Centre for African and Development Studies.
    13. Luis A Gil-Alana & Christophe André & Rangan Gupta & Tsangyao Chang & Omid Ranjbar, 2015. "The Feldstein-Horioka Puzzle in South Africa: A Fractional Cointegration Approach," Working Papers 201501, University of Pretoria, Department of Economics.
    14. Claudio Morana, 2014. "Factor Vector Autoregressive Estimation of Heteroskedastic Persistent and Non Persistent Processes Subject to Structural Breaks," Working Papers 273, University of Milano-Bicocca, Department of Economics, revised May 2014.
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    18. Dark Jonathan Graeme, 2010. "Estimation of Time Varying Skewness and Kurtosis with an Application to Value at Risk," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(2), pages 1-50, March.
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    23. Luis A. Gil-Alana & Juncal Cunado & Rangan Gupta, 2015. "Persistence, Mean-Reversion and Non-Linearities in Infant Mortality Rates," Working Papers 201574, University of Pretoria, Department of Economics.
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    29. Claudio Morana & Giacomo Sbrana, 2017. "Temperature Anomalies, Radiative Forcing and ENSO," Working Papers 2017.09, Fondazione Eni Enrico Mattei.
    30. Guillaume Chevillon & Alain Hecq & Sébastien Laurent, 2018. "Generating Univariate Fractional Integration within a Large VAR(1)," AMSE Working Papers 1844, Aix-Marseille School of Economics, France.
    31. Chen, Ying & Han, Qian & Niu, Linlin, 2018. "Forecasting the Term Structure of Option Implied Volatility: The Power of an Adaptive Method," IRTG 1792 Discussion Papers 2018-046, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    32. Shaher Al-Gounmeein Remal & Ismail Mohd Tahir, 2021. "Modelling and forecasting monthly Brent crude oil prices: a long memory and volatility approach," Statistics in Transition New Series, Polish Statistical Association, vol. 22(1), pages 29-54, March.
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    35. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
    36. Christophe Andre & Luis A. Gil-Alana & Rangan Gupta, 2013. "Testing for Persistence in Housing Price-to-Income and Price-to-Rent Ratios in 16 OECD Countries," Working Papers 201321, University of Pretoria, Department of Economics.
    37. Lean, Hooi Hooi & Smyth, Russell, 2009. "Long memory in US disaggregated petroleum consumption: Evidence from univariate and multivariate LM tests for fractional integration," Energy Policy, Elsevier, vol. 37(8), pages 3205-3211, August.
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    42. Lux, Thomas & Kaizoji, Taisei, 2006. "Forecasting volatility and volume in the Tokyo stock market: Long memory, fractality and regime switching," Economics Working Papers 2006-13, Christian-Albrechts-University of Kiel, Department of Economics.
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    56. Guglielmo Maria Caporale & Juncal Cunado & Luis A. Gil-Alana & Rangan Gupta, 2015. "The Relationship between Healthcare Expenditure and Disposable Personal Income in the US States: A Fractional Integration and Cointegration Analysis," Discussion Papers of DIW Berlin 1486, DIW Berlin, German Institute for Economic Research.
    57. Luis Alberiko Gil-Alaña & Rangan Gupta, 2016. "Trends and Cycles in Historical Gold and Silver Prices," NCID Working Papers 05/2016, Navarra Center for International Development, University of Navarra.
    58. Emmanuel Joel Aikins Abakah & Guglielmo Maria Caporale & Luis A. Gil-Alana, 2020. "Economic Policy Uncertainty: Persistence and Cross-Country Linkages," CESifo Working Paper Series 8289, CESifo.
    59. Philippe Charlot & Vêlayoudom Marimoutou, 2014. "On the relationship between the prices of oil and the precious metals: Revisiting with a multivariate regime-switching decision tree," Working Papers hal-00980125, HAL.
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    61. Wang, Cindy Shin-Huei & Bauwens, Luc & Hsiao, Cheng, 2013. "Forecasting a long memory process subject to structural breaks," Journal of Econometrics, Elsevier, vol. 177(2), pages 171-184.
    62. Katsumi Shimotsu, 2006. "Simple (but Effective) Tests Of Long Memory Versus Structural Breaks," Working Paper 1101, Economics Department, Queen's University.
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    70. Han, Heejoon & Park, Joon Y., 2006. "Time series properties of ARCH processes with persistent covariates," MPRA Paper 5199, University Library of Munich, Germany.
    71. Kunal Saha & Vinodh Madhavan & Chandrashekhar G. R. & David McMillan, 2020. "Pitfalls in long memory research," Cogent Economics & Finance, Taylor & Francis Journals, vol. 8(1), pages 1733280-173, January.
    72. Xu, Jiawen & Perron, Pierre, 2014. "Forecasting return volatility: Level shifts with varying jump probability and mean reversion," International Journal of Forecasting, Elsevier, vol. 30(3), pages 449-463.
    73. Shi, Yanlin & Ho, Kin-Yip, 2015. "Modeling high-frequency volatility with three-state FIGARCH models," Economic Modelling, Elsevier, vol. 51(C), pages 473-483.
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    79. Yaya, OlaOluwa A & Gil-Alana, Luis A., 2018. "Modelling Long Range Dependence and Non-linearity in the Infant Mortality Rates of Africa Countries," MPRA Paper 88752, University Library of Munich, Germany.
    80. Bhardwaj, Geetesh & Swanson, Norman R., 2006. "An empirical investigation of the usefulness of ARFIMA models for predicting macroeconomic and financial time series," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 539-578.
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    83. Ulrich K. Müller & Mark W. Watson, 2008. "Testing Models of Low-Frequency Variability," Econometrica, Econometric Society, vol. 76(5), pages 979-1016, September.
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    87. Adnen Ben Nasr & Ahdi N. Ajmi & Rangan Gupta, 2013. "Modeling the Volatility of the Dow Jones Islamic Market World Index Using a Fractionally Integrated Time Varying GARCH (FITVGARCH) Model," Working Papers 201357, University of Pretoria, Department of Economics.
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    91. Christian Fischer & Luis Gil-Alana, 2009. "The nature of the relationship between international tourism and international trade: the case of German imports of Spanish wine," Applied Economics, Taylor & Francis Journals, vol. 41(11), pages 1345-1359.
    92. Di Sanzo, Silvestro, 2018. "A Markov switching long memory model of crude oil price return volatility," Energy Economics, Elsevier, vol. 74(C), pages 351-359.
    93. Pierre Perron & Zhongjun Qu, 2007. "An Analytical Evaluation of the Log-periodogram Estimate in the Presence of Level Shifts," Boston University - Department of Economics - Working Papers Series wp2007-044, Boston University - Department of Economics.
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    99. Davidson, James & Sibbertsen, Philipp, 2002. "Generating schemes for long memory processes: Regimes, aggregation and linearity," Technical Reports 2002,46, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    100. Luis Alberiko Gil-Alaña & Shinhye Chang & Mehmet Balcilar & Goodness C. Aye & Rangan Gupta, 2015. "Persistence of precious metal prices: a fractional integration approach with structural breaks," NCID Working Papers 06/2015, Navarra Center for International Development, University of Navarra.
    101. David E. Allen & Michael McAleer & Marcel Scharth, 2014. "Asymmetric Realized Volatility Risk," Tinbergen Institute Discussion Papers 14-075/III, Tinbergen Institute.
    102. Yoon, Gawon, 2009. "Is high real interest rate persistence an intrinsic characteristic of industrialized economies?," Economic Modelling, Elsevier, vol. 26(2), pages 359-363, March.
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    104. Harry Vander Elst, 2015. "FloGARCH : Realizing long memory and asymmetries in returns volatility," Working Paper Research 280, National Bank of Belgium.
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    108. Manuel Monge & Luis A. Gil-Alana, 2020. "The Lithium Industry and Analysis of the Beta Term Structure of Oil Companies," Risks, MDPI, vol. 8(4), pages 1-17, December.
    109. Beran, Jan, 2007. "On parameter estimation for locally stationary long-memory processes," CoFE Discussion Papers 07/13, University of Konstanz, Center of Finance and Econometrics (CoFE).
    110. Arouri, Mohamed El Hédi & Lahiani, Amine & Lévy, Aldo & Nguyen, Duc Khuong, 2012. "Forecasting the conditional volatility of oil spot and futures prices with structural breaks and long memory models," Energy Economics, Elsevier, vol. 34(1), pages 283-293.
    111. Luis A. Gil-Alana, 2004. "Modelling the Japanese Exchange Rate in Terms of I(d) Statistical Models with Parametric and Semiparametric Techniques," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 3(2), pages 123-138, August.
    112. Minford, Patrick & Peel, David, 2005. "On the equality of Real Interest Rates across borders in Integrated Capital Markets," Cardiff Economics Working Papers E2005/3, Cardiff University, Cardiff Business School, Economics Section.
    113. L.A. Gil‐Alana, 2006. "Fractional integration in daily stock market indexes," Review of Financial Economics, John Wiley & Sons, vol. 15(1), pages 28-48.
    114. L.A. Gil-Alana & G.M. caporale, 2004. "Long-run and Cyclical Dynamics in the US Stock Market," Econometric Society 2004 Latin American Meetings 344, Econometric Society.
    115. Li, Ziran & Sun, Jiajing & Wang, Shouyang, 2013. "Amplitude-Duration-Persistence Trade-off Relationship for Long Term Bear Stock Markets," MPRA Paper 54177, University Library of Munich, Germany.
    116. Mateo Isoardi & Luis A. Gil-Alana, 2019. "Inflation in Argentina: Analysis of Persistence Using Fractional Integration," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 45(2), pages 204-223, April.
    117. Davide Delle Monache & Stefano Grassi & Paolo Santucci, 2015. "Testing for Level Shifts in Fractionally Integrated Processes: a State Space Approach," Studies in Economics 1511, School of Economics, University of Kent.
    118. Luis A. Gil-Alana & Jiang Liang, 2011. "The PPP hypothesis in the US/China relationship. Fractional integration, time variation and data frequency," Faculty Working Papers 13/11, School of Economics and Business Administration, University of Navarra.
    119. Abdul Aziz Karia & Imbarine Bujang & Ismail Ahmad, 2013. "Fractionally integrated ARMA for crude palm oil prices prediction: case of potentially overdifference," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(12), pages 2735-2748, December.
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    125. Villanueva, O. Miguel, 2007. "Spot-forward cointegration, structural breaks and FX market unbiasedness," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 17(1), pages 58-78, February.
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    130. Richard T. Baillie & Claudio Morana, 2014. "Modeling Long Memory and Structural Breaks in Conditional Variances: An Adaptive FIGARCH Approach," Working Papers 593, Queen Mary University of London, School of Economics and Finance.
    131. Daniela Osterrieder & Daniel Ventosa-Santaulària & J. Eduardo Vera-Valdés, 2015. "Unbalanced Regressions and the Predictive Equation," CREATES Research Papers 2015-09, Department of Economics and Business Economics, Aarhus University.
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    135. Luis A. Gil-Alana & Antonio Moreno, 2009. "Fractional Integration and Structural Breaks in U.S. Macro Dynamics," Faculty Working Papers 02/09, School of Economics and Business Administration, University of Navarra.
    136. Bertanha, Marinho & Moreira, Marcelo J., 2020. "Impossible inference in econometrics: Theory and applications," Journal of Econometrics, Elsevier, vol. 218(2), pages 247-270.
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    159. Elie Bouri & Luis A. Gil-Alana & Rangan Gupta & David Roubaud, 2016. "Modelling Long Memory Volatility in the Bitcoin Market: Evidence of Persistence and Structural Breaks," Working Papers 201654, University of Pretoria, Department of Economics.
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    187. Derek Bond & Michael J. Harrison & Edward J. O'Brien, 2006. "Purchasing Power Parity: The Irish Experience Re-visited," Trinity Economics Papers tep200615, Trinity College Dublin, Department of Economics.
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    189. Juan Carlos Cuestas & Luis A. Gil-Alana & Paulo José Regis, 2015. "The Sustainability of European External Debt: What have We Learned?," Review of International Economics, Wiley Blackwell, vol. 23(3), pages 445-468, August.
    190. Fillol, Jerome, 2007. "Estimating long memory: Scaling function vs Andrews and Guggenberger GPH," Economics Letters, Elsevier, vol. 95(2), pages 309-314, May.
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    193. Kuswanto, Heri & Sibbertsen, Philipp, 2009. "Testing for Long Memory Against ESTAR Nonlinearities," Hannover Economic Papers (HEP) dp-427, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    194. Chen, Shengming & Bouteska, Ahmed & Sharif, Taimur & Abedin, Mohammad Zoynul, 2023. "The Russia–Ukraine war and energy market volatility: A novel application of the volatility ratio in the context of natural gas," Resources Policy, Elsevier, vol. 85(PA).
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    196. Young Wook Han, 2010. "The Effects of US Macroeconomic Surprises on the Intraday Movements of Foreign Exchange Rates: Cases of USD-EUR and USD-JPY Exchange Rates," International Economic Journal, Taylor & Francis Journals, vol. 24(3), pages 375-396.
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    203. Gilles Dufrénot & Valérie Mignon & Théo Naccache, 2009. "The slow convergence of per capita income between the developing countries: “growth resistance” and sometimes “growth tragedy”," Discussion Papers 09/03, University of Nottingham, CREDIT.
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    205. Luis A. Gil-Alana, 2015. "Linear and segmented trends in sea surface temperature data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(7), pages 1531-1546, July.
    206. Gil-Alana, Luis A., 2002. "Structural breaks and fractional integration in the US output and unemployment rate," Economics Letters, Elsevier, vol. 77(1), pages 79-84, September.
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    213. Guglielmo Maria Caporale & Hector Carcel & Luis A. Gil-Alana, 2015. "Modelling African inflation rates: nonlinear deterministic terms and long-range dependence," Applied Economics Letters, Taylor & Francis Journals, vol. 22(5), pages 421-424, March.
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    218. Javier Haulde & Morten Ørregaard Nielsen, 2022. "Fractional integration and cointegration," CREATES Research Papers 2022-02, Department of Economics and Business Economics, Aarhus University.
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    220. Davidson James E. H. & Peel David A & Byers J. David, 2006. "Support for Governments and Leaders: Fractional Cointegration Analysis of Poll Evidence from the UK, 1960-2004," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 10(1), pages 1-23, March.
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    226. Luis A. Gil-Alana & Fernando Perez de Gracia & Rangan Gupta, 2015. "Modeling Persistence of Carbon Emission Allowance Prices," Working Papers 201515, University of Pretoria, Department of Economics.
    227. Ivelina Pavlova & Jang Hyung Cho & A.M. Parhizgari & William G. Hardin, 2014. "Long memory in REIT volatility and changes in the unconditional mean: a modified FIGARCH approach," Journal of Property Research, Taylor & Francis Journals, vol. 31(4), pages 315-332, December.
    228. Iacone, Fabrizio & Robinson, Peter M., 2004. "Cointegration in fractional systems with deterministic trends," LSE Research Online Documents on Economics 2232, London School of Economics and Political Science, LSE Library.
    229. Luis A. Gil-Alana & Rangan Gupta & Olanrewaju I. Shittu & OlaOluwa S. Yaya, 2016. "Market Efficiency of Baltic Stock Markets: A Fractional Integration Approach," Working Papers 201617, University of Pretoria, Department of Economics.
    230. Katarzyna Lasak & Carlos Velasco, 2014. "Fractional Cointegration Rank Estimation," Tinbergen Institute Discussion Papers 14-021/III, Tinbergen Institute.
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    235. Luis A. Gil-Alana & Sakiru Adebola Solarin & Rangan Gupta, 2021. "Productivity and GDP: International Evidence of Persistence and Trends Over 130 Years of Data," Working Papers 202170, University of Pretoria, Department of Economics.
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    239. Fabrizio Iacone, 2009. "A Semiparametric Analysis of the Term Structure of the US Interest Rates," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(4), pages 475-490, August.
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    242. Golinski, Adam & Madeira, Joao & Rambaccussing, Dooruj, 2014. "Fractional Integration of the Price-Dividend Ratio in a Present-Value Model," MPRA Paper 58554, University Library of Munich, Germany.
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    245. Robinson Kruse & Christoph Wegener, 2019. "Explosive behaviour and long memory with an application to European bond yield spreads," Scottish Journal of Political Economy, Scottish Economic Society, vol. 66(1), pages 139-153, February.
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    247. Christophe Andre & Mehmet Balcilar & Tsangyao Chang & Luis Alberiko Gil-Alana & Rangan Gupta, 2018. "Current account sustainability in G7 and BRICS: Evidence from a long-memory model with structural breaks," The Journal of International Trade & Economic Development, Taylor & Francis Journals, vol. 27(6), pages 638-654, August.
    248. Les Oxley & Chris Price & William Rea & Marco Reale, 2008. "A New Procedure to Test for H Self-Similarity," Working Papers in Economics 08/16, University of Canterbury, Department of Economics and Finance.
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    251. Gil-Alana, Luis Alberiko & Abakah, Emmanuel Joel Aikins & Rojo, María Fátima Romero, 2020. "Cryptocurrencies and stock market indices. Are they related?," Research in International Business and Finance, Elsevier, vol. 51(C).
    252. Marinko Skare & Luis A. Gil-Alana & Gloria Claudio-Quiroga & Romina Pržiklas Družeta, 2021. "Income inequality in China 1952–2017: persistence and main determinants," Oeconomia Copernicana, Institute of Economic Research, vol. 12(4), pages 863-888, December.
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    535. Steven Clark & T. Coggin, 2011. "Are U.S. stock prices mean reverting? Some new tests using fractional integration models with overlapping data and structural breaks," Empirical Economics, Springer, vol. 40(2), pages 373-391, April.

  76. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Heiko Ebens, 2000. "The Distribution of Stock Return Volatility," NBER Working Papers 7933, National Bureau of Economic Research, Inc.

    Cited by:

    1. Hau, Harald, 2002. "The Role of Transaction Costs for Financial Volatility: Evidence from the Paris Bourse," CEPR Discussion Papers 3651, C.E.P.R. Discussion Papers.
    2. Adam Wu, 2017. "Systematic Noise: Micro-movements in Equity Options Markets," Papers 1708.06855, arXiv.org.
    3. Magdalena Vorzsak & Carmen Maria Gut, 2008. "Constraints Concerning Investment And Participation In Professional Training In The Companies From The Romanian Manufacturing Industry," JOURNAL STUDIA UNIVERSITATIS BABES-BOLYAI NEGOTIA, Babes-Bolyai University, Faculty of Business.
    4. Theodoros Diasakos, 2008. "Comparative Statics of Asset Prices," Carlo Alberto Notebooks 72, Collegio Carlo Alberto, revised 2011.
    5. Özer Karagedikli & Pierre L. Siklos, 2008. "Explaining Movements in the NZ Dollar - Central Bank Communication and the Surprise Element in Monetary Policy?," Reserve Bank of New Zealand Discussion Paper Series DP2008/02, Reserve Bank of New Zealand.
    6. John M. Maheu & Thomas McCurdy, 2001. "Nonlinear Features of Realized FX Volatility," CIRANO Working Papers 2001s-42, CIRANO.
    7. Tiberiu Cristian Avramescu, 2008. "Romanian Tourism: A Regional Approach," JOURNAL STUDIA UNIVERSITATIS BABES-BOLYAI NEGOTIA, Babes-Bolyai University, Faculty of Business.
    8. John Cotter, 2004. "Realized volatility and minimum capital requirements," Money Macro and Finance (MMF) Research Group Conference 2003 20, Money Macro and Finance Research Group.
    9. Šárka Brychtová, 2008. "Spa Healing Sources In Czech Republic," JOURNAL STUDIA UNIVERSITATIS BABES-BOLYAI NEGOTIA, Babes-Bolyai University, Faculty of Business.
    10. Chang, Yoosoon & Isaac Miller, J. & Park, Joon Y., 2009. "Extracting a common stochastic trend: Theory with some applications," Journal of Econometrics, Elsevier, vol. 150(2), pages 231-247, June.
    11. Manole Velicanu & Gheorghe Matei, 2008. "Decision Support Systems: Present And Future Trends," JOURNAL STUDIA UNIVERSITATIS BABES-BOLYAI NEGOTIA, Babes-Bolyai University, Faculty of Business.
    12. Borgsen, Sina & Glaser, Markus, 2005. "Diversifikationseffekte durch Small und Mid Caps?," Sonderforschungsbereich 504 Publications 05-10, Sonderforschungsbereich 504, Universität Mannheim;Sonderforschungsbereich 504, University of Mannheim.
    13. Cristina Silvia Nistor & Crina Ioana Filip & Adela Deaconu, 2008. "Derivative Instruments – Alternatives To Cover The Foreign Exchange Rate In The Case Of Import-Export Operations - Accounting Approach For Romania," JOURNAL STUDIA UNIVERSITATIS BABES-BOLYAI NEGOTIA, Babes-Bolyai University, Faculty of Business.
    14. Asger Lunde & Peter Reinhard Hansen, 2001. "A Forecast Comparison of Volatility Models: Does Anything Beat a GARCH(1,1)?," Working Papers 2001-04, Brown University, Department of Economics.
    15. Rasmus Tangsgaard Varneskov & Pierre Perron, 2011. "Combining Long Memory and Level Shifts in Modeling and Forecasting the Volatility of Asset Returns," CREATES Research Papers 2011-26, Department of Economics and Business Economics, Aarhus University.
    16. Barucci, Emilio & Reno, Roberto, 2002. "On measuring volatility and the GARCH forecasting performance," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 12(3), pages 183-200, July.
    17. Cristina Curutiu, 2008. "Methods Of Portfolio Management - A Review Of Literature -," JOURNAL STUDIA UNIVERSITATIS BABES-BOLYAI NEGOTIA, Babes-Bolyai University, Faculty of Business.
    18. Michael W. Brandt & Qiang Kang, 2002. "On the Relationship Between the Conditional Mean and Volatility of Stock Returns: A Latent VAR Approach," NBER Working Papers 9056, National Bureau of Economic Research, Inc.
    19. Bollerslev, Tim, 2001. "Financial econometrics: Past developments and future challenges," Journal of Econometrics, Elsevier, vol. 100(1), pages 41-51, January.
    20. Srečko Devjak & Andraž Grum, 2006. "Third Moment of Yield Probability Distributions for Instruments on Slovenian Financial Markets," Prague Economic Papers, Prague University of Economics and Business, vol. 2006(4), pages 364-373.
    21. Dimitrios D. Thomakos & Michail S. Koubouros, 2005. "Realized Volatility and Asymmetries in the A.S.E. Returns," Finance 0507012, University Library of Munich, Germany, revised 17 Jan 2006.
    22. Juan A. Lafuente & Manuel Illueca Muñoz, 2006. "New Evidence On Expiration-Day Effects Using Realized Volatility: An Intraday Analysis For The Spanish Stock Exchange," Working Papers. Serie EC 2006-05, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    23. Degiannakis, Stavros, 2004. "Volatility Forecasting: Evidence from a Fractional Integrated Asymmetric Power ARCH Skewed-t Model," MPRA Paper 96330, University Library of Munich, Germany.
    24. Degiannakis, Stavros & Livada, Alexandra & Panas, Epaminondas, 2008. "Rolling-sampled parameters of ARCH and Levy-stable models," MPRA Paper 80464, University Library of Munich, Germany.
    25. Eugenie Hol & Siem Jan Koopman, 2000. "Forecasting the Variability of Stock Index Returns with Stochastic Volatility Models and Implied Volatility," Tinbergen Institute Discussion Papers 00-104/4, Tinbergen Institute.
    26. Hayette Gatfaoui, 2004. "Idiosyncratic Risk, Systematic Risk and Stochastic Volatility: An Implementation of Merton's Credit Risk Valuation," Research Paper Series 123, Quantitative Finance Research Centre, University of Technology, Sydney.
    27. Sam Howison & David Lamper, 2001. "Trading volume in models of financial derivatives," Applied Mathematical Finance, Taylor & Francis Journals, vol. 8(2), pages 119-135.
    28. Mihaela Dragan & Zenovia Cristiana Pop, 2008. "CRITERIA FOR PRODUCT QUALITY IN THE FRAME OF INTERCULTURAL MARKET STRATEGIES OF SMALL AND MEDIUM SIZED ENTERPRISES - a brief review of literature -," JOURNAL STUDIA UNIVERSITATIS BABES-BOLYAI NEGOTIA, Babes-Bolyai University, Faculty of Business.
    29. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Heiko Ebens, 2000. "The Distribution of Stock Return Volatility," NBER Working Papers 7933, National Bureau of Economic Research, Inc.
    30. David S. Bates, 2003. "Maximum Likelihood Estimation of Latent Affine Processes," NBER Working Papers 9673, National Bureau of Economic Research, Inc.
    31. Partenie Dumbrava & Ioan Pop & Eniko Fazakas & Jozsef Fazakas & Ludovica Breban, 2008. "The Environmental Impact Of Beer Production," JOURNAL STUDIA UNIVERSITATIS BABES-BOLYAI NEGOTIA, Babes-Bolyai University, Faculty of Business.
    32. Su, Ender & Wong, Kai Wen, 2018. "Measuring bank downside systemic risk in Taiwan," The Quarterly Review of Economics and Finance, Elsevier, vol. 70(C), pages 172-193.
    33. Srecko Devjak & Andraz Grum, 2005. "Market Risk Control In Stable Paretian Markets," Economic Thought and Practice, Department of Economics and Business, University of Dubrovnik, vol. 14(2), pages 147-160, december.
    34. Borgsen, Sina & Glaser, Markus, 2005. "Diversifikationseffekte durch small und mid caps? : Eine empirische Untersuchung basierend auf europäischen Aktienindizes," Papers 05-10, Sonderforschungsbreich 504.
    35. Adina Negrusa & Oana Adriana Gica, 2008. "Analysis Of Potential Sme’S Role For Developing Tourism In Transylvania," JOURNAL STUDIA UNIVERSITATIS BABES-BOLYAI NEGOTIA, Babes-Bolyai University, Faculty of Business.
    36. Høg, Esben, 2008. "Volatility and realized quadratic variation of differenced returns : A wavelet method approach," Finance Research Group Working Papers F-2008-06, University of Aarhus, Aarhus School of Business, Department of Business Studies.
    37. Ivanovski, Zoran & Stojanovski, Toni & Narasanov, Zoran, 2015. "Volatility And Kurtosis Of Daily Stock Returns At Mse," UTMS Journal of Economics, University of Tourism and Management, Skopje, Macedonia, vol. 6(2), pages 209-221.
    38. Adrian Grosanu & Paula Ramona Rachisan, 2008. "The Implementation Of Profit Centres Inside An Economic Entity," JOURNAL STUDIA UNIVERSITATIS BABES-BOLYAI NEGOTIA, Babes-Bolyai University, Faculty of Business.
    39. Haugom, Erik & Westgaard, Sjur & Solibakke, Per Bjarte & Lien, Gudbrand, 2011. "Realized volatility and the influence of market measures on predictability: Analysis of Nord Pool forward electricity data," Energy Economics, Elsevier, vol. 33(6), pages 1206-1215.

  77. Anil Bangia & Francis X. Diebold & Til Schuermann, 2000. "Ratings Migration and the Business Cycle, With Application to Credit Portfolio Stress Testing," Center for Financial Institutions Working Papers 00-26, Wharton School Center for Financial Institutions, University of Pennsylvania.

    Cited by:

    1. Guillermo Ordonez, 2008. "Fragility of Reputation and Clustering in Risk Taking," 2008 Meeting Papers 441, Society for Economic Dynamics.
    2. Liuren Wu & Frank X. Zhang, 2005. "A no-arbitrage analysis of economic determinants of the credit spread term structure," Finance and Economics Discussion Series 2005-59, Board of Governors of the Federal Reserve System (U.S.).
    3. Siem Jan Koopman & André Lucas & André Monteiro, 2005. "The Multi-State Latent Factor Intensity Model for Credit Rating Transitions," Tinbergen Institute Discussion Papers 05-071/4, Tinbergen Institute, revised 04 Jul 2005.
    4. Nicolas Jannone Bellot, MaLuisa Marti Selva, Leandro Garcia Menendez, 2017. "Herding Behaviour among Credit Rating Agencies," Journal of Finance and Economics Research, Geist Science, Iqra University, Faculty of Business Administration, vol. 2(1), pages 56-83, March.
    5. Alain Monfort & Jean-Paul Renne, 2010. "Default, Liquidity and Crises : An Econometric Framework," Working Papers 2010-46, Center for Research in Economics and Statistics.
    6. Bonfim, Diana, 2009. "Credit risk drivers: Evaluating the contribution of firm level information and of macroeconomic dynamics," Journal of Banking & Finance, Elsevier, vol. 33(2), pages 281-299, February.
    7. Wiem Ben Jabra & Zouheir Mighri & Faysal Mansouri, 2017. "Determinants of European bank risk during financial crisis," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1298420-129, January.
    8. Dmitri Boreiko & Serguei Kaniovski & Yuri Kaniovski & Georg Pflug, 2017. "Traces of business cycles in credit-rating migrations," PLOS ONE, Public Library of Science, vol. 12(4), pages 1-29, April.
    9. Schuermann, Til, 2013. "Stress Testing Banks," Working Papers 12-08, University of Pennsylvania, Wharton School, Weiss Center.
    10. Yi Jiang & Stewart Jones, 2018. "Corporate distress prediction in China: a machine learning approach," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(4), pages 1063-1109, December.
    11. M. Hashem Pesaran & Til Schuermann & Björn-Jakob Treutler & Scott M. Weiner & April, "undated". "Macroeconomic Dynamics and Credit Risk: A Global Perspective," Center for Financial Institutions Working Papers 03-13, Wharton School Center for Financial Institutions, University of Pennsylvania.
    12. Philip Lowe, 2002. "Credit risk measurement and procyclicality," BIS Working Papers 116, Bank for International Settlements.
    13. Claudio Borio, 2011. "Rediscovering the Macroeconomic Roots of Financial Stability Policy: Journey, Challenges, and a Way Forward," Annual Review of Financial Economics, Annual Reviews, vol. 3(1), pages 87-117, December.
    14. Rasha Alsakka & Owain ap Gwilym, 2010. "Sovereign Ratings and Migrations: Emerging Markets," Working Papers 10009, Bangor Business School, Prifysgol Bangor University (Cymru / Wales).
    15. Weißbach, Rafael & Walter, Ronja, 2010. "A likelihood ratio test for stationarity of rating transitions," Journal of Econometrics, Elsevier, vol. 155(2), pages 188-194, April.
    16. Zhang, Tianwei & Katchova, Ani L., 2005. "Credit Risk Migration Analysis of Illinois Farm Business: Possible Impacts of Farm Business Cycle," 2005 Annual meeting, July 24-27, Providence, RI 19292, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    17. Brian BARNARD, 2017. "Rating Migration and Bond Valuation: Decomposing Rating Migration Matrices from Market Data via Default Probability Term Structures," Expert Journal of Finance, Sprint Investify, vol. 5, pages 49-72.
    18. Hakimi, Abdelaziz & Hamdi, Helmi, 2013. "Credit Information, Guarantees and Non-Performing Loans," MPRA Paper 55750, University Library of Munich, Germany, revised 2014.
    19. Ferrer, Alex & Casals, José & Sotoca, Sonia, 2015. "Sample dependency during unconditional credit capital estimation," Finance Research Letters, Elsevier, vol. 15(C), pages 175-186.
    20. Koopman, Siem Jan & Lucas, Andre & Klaassen, Pieter, 2005. "Empirical credit cycles and capital buffer formation," Journal of Banking & Finance, Elsevier, vol. 29(12), pages 3159-3179, December.
    21. Schechtman, Ricardo, 2013. "Default matrices: A complete measurement of banks’ consumer credit delinquency," Journal of Financial Stability, Elsevier, vol. 9(4), pages 460-474.
    22. M. Hashem Pesaran & Til Schuermann & Bjorn-Jakob Treutler, 2007. "Global Business Cycles and Credit Risk," NBER Chapters, in: The Risks of Financial Institutions, pages 419-469, National Bureau of Economic Research, Inc.
    23. Avouyi-Dovi, S. & Bardos, M. & Jardet, C. & Kendaoui, L. & Moquet , J., 2009. "Macro stress testing with a macroeconomic credit risk model: Application to the French manufacturing sector," Working papers 238, Banque de France.
    24. Philip Lowe & Miguel Angel Segoviano, 2002. "Internal ratings, the business cycle, and capital requirements: some evidence from an emerging market economy," Conference Series ; [Proceedings], Federal Reserve Bank of Boston.
    25. Miroslav Plasil & Tomas Konecny & Jakub Seidler & Petr Hlavac, 2015. "In the Quest of Measuring the Financial Cycle," Working Papers 2015/05, Czech National Bank.
    26. Carlos González-Aguado & Max Bruche, 2006. "Recovery Rates, Default Probabilities and the Credit Cycle," FMG Discussion Papers dp572, Financial Markets Group.
    27. Ebnother, Silvan & Vanini, Paolo, 2007. "Credit portfolios: What defines risk horizons and risk measurement?," Journal of Banking & Finance, Elsevier, vol. 31(12), pages 3663-3679, December.
    28. Cornaglia, Anna & Morone, Marco, 2009. "Rating philosophy and dynamic properties of internal rating systems: A general framework and an application to backtesting," MPRA Paper 14711, University Library of Munich, Germany.
    29. Siem Jan Koopman & André Lucas & Robert Daniels, 2005. "A Non-Gaussian Panel Time Series Model for Estimating and Decomposing Default Risk," Tinbergen Institute Discussion Papers 05-060/4, Tinbergen Institute.
    30. Andre Lucas & Pieter Klaassen & Peter Spreij & Stefan Straetmans, 2003. "Tail behaviour of credit loss distributions for general latent factor models," Applied Mathematical Finance, Taylor & Francis Journals, vol. 10(4), pages 337-357.
    31. D. V. Boreiko & Y. M. Kaniovski & G. Ch. Pflug, 2016. "Modeling dependent credit rating transitions: a comparison of coupling schemes and empirical evidence," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 24(4), pages 989-1007, December.
    32. Irina Peaucelle, 2005. "Dynamic analysis of bankruptcy and economic waves," PSE Working Papers halshs-00590851, HAL.
    33. Yusuf Jafry & Til Schuermann, 2003. "Metrics for Comparing Credit Migration Matrices," Center for Financial Institutions Working Papers 03-09, Wharton School Center for Financial Institutions, University of Pennsylvania.
    34. Guglielmo D'Amico & Filippo Petroni & Philippe Regnault & Stefania Scocchera & Loriano Storchi, 2019. "A copula based Markov Reward approach to the credit spread in European Union," Papers 1902.00691, arXiv.org.
    35. Cifter, Atilla & Yilmazer, Sait & Cifter, Elif, 2009. "Analysis of sectoral credit default cycle dependency with wavelet networks: Evidence from Turkey," Economic Modelling, Elsevier, vol. 26(6), pages 1382-1388, November.
    36. Kim, Joocheol & Lee, Duyeol, 2007. "Simulation based approach for measuring concentration risk," MPRA Paper 2968, University Library of Munich, Germany, revised 19 Apr 2007.
    37. Vanel, Grégory, 2008. "La normalisation financière internationale face à l’émergence de nouvelles autorités épistémiques américaines," Revue de la Régulation - Capitalisme, institutions, pouvoirs, Association Recherche et Régulation, vol. 3.
    38. Virolainen, Kimmo, 2004. "Macro stress testing with a macroeconomic credit risk model for Finland," Bank of Finland Research Discussion Papers 18/2004, Bank of Finland.
    39. Konrad Banachewicz & André Lucas, 2007. "Quantile Forecasting for Credit Risk Management using possibly Mis-specified Hidden Markov Models," Tinbergen Institute Discussion Papers 07-046/2, Tinbergen Institute.
    40. Patrick Gagliardini, 2005. "Stochastic Migration Models with Application to Corporate Risk," Journal of Financial Econometrics, Oxford University Press, vol. 3(2), pages 188-226.
    41. Alsakka, Rasha & ap Gwilym, Owain, 2012. "Rating agencies' credit signals: An analysis of sovereign watch and outlook," International Review of Financial Analysis, Elsevier, vol. 21(C), pages 45-55.
    42. Georg von Pföstl & Markus Ricke, 2007. "Quantitative Validation of Rating Models for Low Default Portfolios through Benchmarking," Financial Stability Report, Oesterreichische Nationalbank (Austrian Central Bank), issue 14, pages 117-125.
    43. Ferrer, Alex & Casals, José & Sotoca, Sonia, 2015. "Capital cyclicality, conditional coverage and long-term capital assessment," Finance Research Letters, Elsevier, vol. 15(C), pages 246-256.
    44. Telg, Sean & Dubinova, Anna & Lucas, Andre, 2023. "Covid-19, credit risk management modeling, and government support," Journal of Banking & Finance, Elsevier, vol. 147(C).
    45. Buncic, Daniel & Melecky, Martin, 2013. "Macroprudential stress testing of credit risk: A practical approach for policy makers," Journal of Financial Stability, Elsevier, vol. 9(3), pages 347-370.
    46. Torresetti, Roberto & Pallavicini, Andrea, 2007. "Stressing rating criteria allowing for default clustering: the CPDO case," MPRA Paper 17104, University Library of Munich, Germany, revised 04 Sep 2009.
    47. Arnildo da Silva Correa & Jaqueline Terra Moura Marins & Myrian Beatriz Eiras das Neves & Antonio Carlos Magalhães da Silva, 2011. "Credit Default and Business Cycles: an empirical investigation of Brazilian retail loans," Working Papers Series 260, Central Bank of Brazil, Research Department.
    48. Areski Cousin & J'er^ome Lelong & Tom Picard, 2021. "Rating transitions forecasting: a filtering approach," Papers 2109.10567, arXiv.org, revised Jun 2023.
    49. Carr, Peter & Wu, Liuren, 2007. "Theory and evidence on the dynamic interactions between sovereign credit default swaps and currency options," Journal of Banking & Finance, Elsevier, vol. 31(8), pages 2383-2403, August.
    50. Dionne, Georges & Gauthier, Geneviève & Hammami, Khemais & Maurice, Mathieu & Simonato, Jean-Guy, 2010. "A reduced form model of default spreads with Markov-switching macroeconomic factors," Working Papers 10-6, HEC Montreal, Canada Research Chair in Risk Management.
    51. Trueck, Stefan & Rachev, Svetlozar T., 2008. "Rating Based Modeling of Credit Risk," Elsevier Monographs, Elsevier, edition 1, number 9780123736833.
    52. Gagliardini, P. & Gourieroux, C., 2005. "Migration correlation: Definition and efficient estimation," Journal of Banking & Finance, Elsevier, vol. 29(4), pages 865-894, April.
    53. Salvador, Carlos & Fernández de Guevara, Juan & Pastor, José Manuel, 2018. "The adjustment of bank ratings in the financial crisis: International evidence," The North American Journal of Economics and Finance, Elsevier, vol. 44(C), pages 289-313.
    54. Nobuo Inaba & Takashi Kozu & Toshitaka Sekine & Takashi Nagahata, 2005. "Non-performing loans and the real economy: Japan’s experience," BIS Papers chapters, in: Bank for International Settlements (ed.), Investigating the relationship between the financial and real economy, volume 22, pages 106-27, Bank for International Settlements.
    55. Michael Jacobs, 2016. "Stress Testing and a Comparison of Alternative Methodologies for Scenario Generation," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 6(6), pages 1-7.
    56. Malik, Madhur & Thomas, Lyn C., 2012. "Transition matrix models of consumer credit ratings," International Journal of Forecasting, Elsevier, vol. 28(1), pages 261-272.
    57. Yi-Ping Chang & Chih-Tun Yu, 2014. "Bayesian confidence intervals for probability of default and asset correlation of portfolio credit risk," Computational Statistics, Springer, vol. 29(1), pages 331-361, February.
    58. G'eraldine Bouveret & Jean-Franc{c}ois Chassagneux & Smail Ibbou & Antoine Jacquier & Lionel Sopgoui, 2023. "Propagation of a carbon price in a credit portfolio through macroeconomic factors," Papers 2307.12695, arXiv.org, revised Apr 2024.
    59. Elena Kalotychou & Ana-Maria Fuertes, 2006. "On Sovereign Credit Migration: A Study of Alternative Estimators and Rating Dynamics," Computing in Economics and Finance 2006 509, Society for Computational Economics.
    60. Kadam, Ashay & Lenk, Peter, 2008. "Bayesian inference for issuer heterogeneity in credit ratings migration," Journal of Banking & Finance, Elsevier, vol. 32(10), pages 2267-2274, October.
    61. Areski Cousin & Mohamed Reda Kheliouen, 2016. "A comparative study on the estimation of factor migration models," Working Papers halshs-01351926, HAL.
    62. Bhattacharjee, Arnab & Hany, Jie, 2010. "Financial Distress in Chinese Industry: Microeconomic, Macroeconomic and Institutional Infuences," SIRE Discussion Papers 2010-53, Scottish Institute for Research in Economics (SIRE).
    63. Michael C. Munnix & Rudi Schafer & Thomas Guhr, 2011. "A Random Matrix Approach to Credit Risk," Papers 1102.3900, arXiv.org, revised Jun 2011.
    64. Kim, Yoonseong & Sohn, So Young, 2008. "Random effects model for credit rating transitions," European Journal of Operational Research, Elsevier, vol. 184(2), pages 561-573, January.
    65. M. Hashem Pesaran & Til Schuermann & Björn-Jakob Treutler, 2005. "The Role of Industry, Geography and Firm Heterogeneity in Credit Risk Diversification," IEPR Working Papers 05.25, Institute of Economic Policy Research (IEPR).
    66. Kilian R. Dinkelaker & Andreas-Walter Mattig & Stefan Morkoetter, 2019. "A Closer Look at Credt Rating Processes: Uncovering the Impact of Analyst Rotation," Working Papers on Finance 1911, University of St. Gallen, School of Finance.
    67. Louzis, Dimitrios P. & Vouldis, Angelos T. & Metaxas, Vasilios L., 2012. "Macroeconomic and bank-specific determinants of non-performing loans in Greece: A comparative study of mortgage, business and consumer loan portfolios," Journal of Banking & Finance, Elsevier, vol. 36(4), pages 1012-1027.
    68. Collet, Jerome & Ielpo, Florian, 2018. "Sector spillovers in credit markets," Journal of Banking & Finance, Elsevier, vol. 94(C), pages 267-278.
    69. Rina Bhattacharya & Pranav Gupta & Xingwei Hu & Peter Pedroni, 2018. "How do Structural Features Affect Corporate Exposures to Macro-financial Shocks in Open Economies?," Department of Economics Working Papers 2018-10, Department of Economics, Williams College.
    70. Gunter Löffler, 2013. "Can rating agencies look through the cycle?," Review of Quantitative Finance and Accounting, Springer, vol. 40(4), pages 623-646, May.
    71. Jose Eduardo Gómez & Paola Morales Acevedo & Fernando Pineda & Nancy Zamudio, 2007. "An Alternative Methodology for Estimating Credit Quality Transition Matrices," Borradores de Economia 4395, Banco de la Republica.
    72. Victor Olkhov, 2020. "Business Cycles as Collective Risk Fluctuations," Papers 2012.04506, arXiv.org.
    73. Christensen, Jens H.E. & Hansen, Ernst & Lando, David, 2004. "Confidence sets for continuous-time rating transition probabilities," Journal of Banking & Finance, Elsevier, vol. 28(11), pages 2575-2602, November.
    74. Koopman, Siem Jan & Kräussl, Roman & Lucas, André, 2006. "Credit cycles and macro fundamentals," CFS Working Paper Series 2006/33, Center for Financial Studies (CFS).
    75. Tatiana Cesaroni, 2015. "Procyclicality of credit rating systems: how to manage it," Mo.Fi.R. Working Papers 109, Money and Finance Research group (Mo.Fi.R.) - Univ. Politecnica Marche - Dept. Economic and Social Sciences.
    76. Simone Varotto, 2010. "Stress Testing Credit Risk: The Great Depression Scenario," ICMA Centre Discussion Papers in Finance icma-dp2010-03, Henley Business School, University of Reading.
    77. Chen, Bin & Hong, Yongmiao, 2012. "Testing For The Markov Property In Time Series," Econometric Theory, Cambridge University Press, vol. 28(1), pages 130-178, February.
    78. Giuseppe Marotta & Chiara Pederzoli & Costanza Torricelli, 2005. "Forward-looking estimation of default probabilities with Italian data," Heterogeneity and monetary policy 0504, Universita di Modena e Reggio Emilia, Dipartimento di Economia Politica.
    79. Mizen, Paul & Tsoukas, Serafeim, 2012. "Forecasting US bond default ratings allowing for previous and initial state dependence in an ordered probit model," International Journal of Forecasting, Elsevier, vol. 28(1), pages 273-287.
    80. Weißbach, Rafael & Mollenhauer, Thomas, 2011. "Modelling Rating Transitions," VfS Annual Conference 2011 (Frankfurt, Main): The Order of the World Economy - Lessons from the Crisis 48698, Verein für Socialpolitik / German Economic Association.
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    83. Florence Béranger & Jérôme Teïletche, 2003. "Bâle II et la procyclicité," Revue d'Économie Financière, Programme National Persée, vol. 73(4), pages 227-250.
    84. Carlos Castro, 2012. "Confidence sets for asset correlations in portfolio credit risk," Revista de Economía del Rosario, Universidad del Rosario, June.
    85. Brian Barnard, 2019. "Rating Migration and Bond Valuation: Towards Ahistorical Rating Migration Matrices and Default Probability Term Structures," Applied Finance and Accounting, Redfame publishing, vol. 5(1), pages 12-41, February.
    86. Carling, Kenneth & Rönnegård, Lars & Roszbach, Kasper, 2004. "Is Firm Interdependence within Industries Important for Portfolio Credit Risk?," Working Paper Series 168, Sveriges Riksbank (Central Bank of Sweden).
    87. Mejra Festić, 2006. "Procyclicality of Financial and Real Sector in Transition Economies," Prague Economic Papers, Prague University of Economics and Business, vol. 2006(4), pages 315-349.
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    89. Georges Dionne & Geneviève Gauthier & Khemais Hammami & Mathieu Maurice & Jean‐Guy Simonato, 2010. "Default Risk in Corporate Yield Spreads," Financial Management, Financial Management Association International, vol. 39(2), pages 707-731, June.
    90. Frydman, Halina & Schuermann, Til, 2008. "Credit rating dynamics and Markov mixture models," Journal of Banking & Finance, Elsevier, vol. 32(6), pages 1062-1075, June.
    91. Joan Jasiak & D. Feng & C. Gourieroux, 2006. "The Ordered Qualitative Model For Credit Rating Transitions," Working Papers 2006_2, York University, Department of Economics.
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    3. Lütkepohl, Helmut & Proietti, Tommaso, 2011. "Does the Box-Cox transformation help in forecasting macroeconomic time series?," Working Papers 08/2011, University of Sydney Business School, Discipline of Business Analytics.
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    11. Marc Brisson & Bryan Campbell & John W. Galbraith, 2001. "Forecasting Some Low-Predictability Time Series Using Diffusion Indices," CIRANO Working Papers 2001s-46, CIRANO.
    12. Lutz Kilian & Xiaoqing Zhou, 2017. "Modeling Fluctuations in the Global Demand for Commodities," CESifo Working Paper Series 6749, CESifo.
    13. Aruoba, S. Borağan & Diebold, Francis X. & Nalewaik, Jeremy & Schorfheide, Frank & Song, Dongho, 2016. "Improving GDP measurement: A measurement-error perspective," Journal of Econometrics, Elsevier, vol. 191(2), pages 384-397.
    14. John W. Galbraith & Greg Tkacz, 2007. "Forecast content and content horizons for some important macroeconomic time series," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 40(3), pages 935-953, August.
    15. John G. Galbraith & Greg Tkacz, 2006. "How Far Can We Forecast? Forecast Content Horizons For Some Important Macroeconomic Time Series," Departmental Working Papers 2006-13, McGill University, Department of Economics.
    16. Francis X. Diebold, 1997. "The Past, Present, and Future of Macroeconomic Forecasting," NBER Working Papers 6290, National Bureau of Economic Research, Inc.
    17. Glenn D. Rudebusch, 2001. "Term structure evidence on interest rate smoothing and monetary policy inertia," Working Paper Series 2001-02, Federal Reserve Bank of San Francisco.
    18. Oller, Lars-Erik & Teterukovsky, Alex, 2007. "Quantifying the quality of macroeconomic variables," International Journal of Forecasting, Elsevier, vol. 23(2), pages 205-217.
    19. Sridevi Narayanan & Chee Keong Choong & Lin Sea Lau, 2020. "An investigation on the role of good governance as a mediating factor in the FDI-Growth nexus: An ASEAN Perspective," Economics Bulletin, AccessEcon, vol. 40(4), pages 2769-2779.
    20. Fanelli, Luca & Paruolo, Paolo, 2007. "Speed of Adjustment in Cointegrated Systems," MPRA Paper 9174, University Library of Munich, Germany.
    21. Konstantin A. Kholodilin & Boriss Siliverstovs, 2009. "Do forecasters inform or reassure?," KOF Working papers 09-215, KOF Swiss Economic Institute, ETH Zurich.
    22. Degenhardt, Thomas & Auer, Benjamin R., 2018. "The “Sell in May” effect: A review and new empirical evidence," The North American Journal of Economics and Finance, Elsevier, vol. 43(C), pages 169-205.
    23. David McMillan & Isabel Ruiz & Alan Speight, 2010. "Correlations and spillovers among three euro rates: evidence using realised variance," The European Journal of Finance, Taylor & Francis Journals, vol. 16(8), pages 753-767.
    24. Yoshua Bengio & François Gingras & Claude Nadeau, 2002. "On Out-of-Sample Statistics for Time-Series," CIRANO Working Papers 2002s-51, CIRANO.
    25. Timothy Cogley & Giorgio E. Primiceri & Thomas J. Sargent, 2010. "Inflation-Gap Persistence in the US," American Economic Journal: Macroeconomics, American Economic Association, vol. 2(1), pages 43-69, January.
    26. Robert L. Czudaj, 2021. "Heterogeneity of Beliefs and Information Rigidity in the Crude Oil Market: Evidence from Survey Data," Chemnitz Economic Papers 050, Department of Economics, Chemnitz University of Technology, revised Sep 2021.
    27. Knetsch, Thomas A., 2006. "Forecasting the price of crude oil via convenience yield predictions," Discussion Paper Series 1: Economic Studies 2006,12, Deutsche Bundesbank.
    28. Barnett, Alina & Groen, Jan J J & Mumtaz, Haroon, 2010. "Time-varying inflation expectations and economic fluctuations in the United Kingdom: a structural VAR analysis," Bank of England working papers 392, Bank of England.
    29. Potì, Valerio & Siddique, Akhtar, 2013. "What drives currency predictability?," Journal of International Money and Finance, Elsevier, vol. 36(C), pages 86-106.
    30. Michael Clements, 2016. "Are Macroeconomic Density Forecasts Informative?," ICMA Centre Discussion Papers in Finance icma-dp2016-02, Henley Business School, University of Reading.
    31. Ionel Birgean & Lutz Kilian, 2002. "Data-Driven Nonparametric Spectral Density Estimators For Economic Time Series: A Monte Carlo Study," Econometric Reviews, Taylor & Francis Journals, vol. 21(4), pages 449-476.
    32. Osmani Teixeira de Carvalho Guillén & João Victor Issler & George Athanasopoulos, 2005. "Forecasting Accuracy and Estimation Uncertainty Using VAR Models with Short- and Long-Term Economic Restrictions: A Monte-Carlo Study," Monash Econometrics and Business Statistics Working Papers 15/05, Monash University, Department of Econometrics and Business Statistics.
    33. Breitung, Jörg & Knüppel, Malte, 2018. "How far can we forecast? Statistical tests of the predictive content," Discussion Papers 07/2018, Deutsche Bundesbank.
    34. Isiklar, Gultekin & Lahiri, Kajal, 2007. "How far ahead can we forecast? Evidence from cross-country surveys," International Journal of Forecasting, Elsevier, vol. 23(2), pages 167-187.
    35. Zhang, Gang & Yang, Dazhi & Galanis, George & Androulakis, Emmanouil, 2022. "Solar forecasting with hourly updated numerical weather prediction," Renewable and Sustainable Energy Reviews, Elsevier, vol. 154(C).
    36. Dovern, Jonas, 2006. "Predicting GDP components: do leading indicators increase predictability?," Kiel Advanced Studies Working Papers 436, Kiel Institute for the World Economy (IfW Kiel).
    37. António Brandão Moniz, 2008. "Assessing scenarios on the future of work," Enterprise and Work Innovation Studies, Universidade Nova de Lisboa, IET/CICS.NOVA-Interdisciplinary Centre on Social Sciences, Faculty of Science and Technology, vol. 4(4), pages 91-106, November.
    38. Rosa, Carlo & Verga, Giovanni, 2007. "On the consistency and effectiveness of central bank communication: Evidence from the ECB," European Journal of Political Economy, Elsevier, vol. 23(1), pages 146-175, March.
    39. Hendry, David F. & Hubrich, Kirstin, 2006. "Forecasting economic aggregates by disaggregates," Working Paper Series 589, European Central Bank.
    40. Monica Jain, 2013. "Perceived Inflation Persistence," Staff Working Papers 13-43, Bank of Canada.
    41. Marc-Oliver Pohle, 2020. "The Murphy Decomposition and the Calibration-Resolution Principle: A New Perspective on Forecast Evaluation," Papers 2005.01835, arXiv.org.
    42. Dovern, Jonas, 2024. "Eliciting expectation uncertainty from private households," International Journal of Forecasting, Elsevier, vol. 40(1), pages 113-123.
    43. Romeo-Catalin CRETU & Irina-Daniela CISMASU & Adrian ANICA-POPA & Petrica STEFAN, 2021. "Education In Digital Era Between Analysis Of Predictability And Consolidation Of Resiliance," Proceedings of the INTERNATIONAL MANAGEMENT CONFERENCE, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 15(1), pages 274-289, November.
    44. Ruan, Xinfeng & Zhang, Jin E., 2018. "Risk-neutral moments in the crude oil market," Energy Economics, Elsevier, vol. 72(C), pages 583-600.
    45. Edoardo Otrano & Umberto Triacca, 2007. "Testing for Equal Predictability of Stationary ARMA Processes," Journal of Applied Statistics, Taylor & Francis Journals, vol. 34(9), pages 1091-1108.
    46. Yang, Dazhi & Wang, Wenting & Gueymard, Christian A. & Hong, Tao & Kleissl, Jan & Huang, Jing & Perez, Marc J. & Perez, Richard & Bright, Jamie M. & Xia, Xiang’ao & van der Meer, Dennis & Peters, Ian , 2022. "A review of solar forecasting, its dependence on atmospheric sciences and implications for grid integration: Towards carbon neutrality," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    47. Luati, Alessandra & Proietti, Tommaso & Reale, Marco, 2011. "The Variance Profile," MPRA Paper 30378, University Library of Munich, Germany.
    48. Dufour, Jean-Marie & Taamouti, Abderrahim, 2010. "Short and long run causality measures: Theory and inference," Journal of Econometrics, Elsevier, vol. 154(1), pages 42-58, January.
    49. Kieran Mc Morrow & Werner Roeger & Valerie Vandermeulen, 2017. "Evaluating Medium Term Forecasting Methods and their Implications for EU Output Gap Calculations," European Economy - Discussion Papers 070, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    50. Kirstin Hubrich & David F. Hendry, 2005. "Forecasting Aggregates by Disaggregates," Computing in Economics and Finance 2005 270, Society for Computational Economics.
    51. Liu, Bai & Yang, Dazhi & Mayer, Martin János & Coimbra, Carlos F.M. & Kleissl, Jan & Kay, Merlinde & Wang, Wenting & Bright, Jamie M. & Xia, Xiang’ao & Lv, Xin & Srinivasan, Dipti & Wu, Yan & Beyer, H, 2023. "Predictability and forecast skill of solar irradiance over the contiguous United States," Renewable and Sustainable Energy Reviews, Elsevier, vol. 182(C).
    52. Vardhan, Harsh & Sinha, Pankaj, 2015. "Influence of Macroeconomic Variable on Indian Stock Movement: Cointegration Approach," MPRA Paper 64369, University Library of Munich, Germany, revised 10 May 2015.
    53. Lahiri, Kajal & Sheng, Xuguang, 2008. "Evolution of forecast disagreement in a Bayesian learning model," Journal of Econometrics, Elsevier, vol. 144(2), pages 325-340, June.

  79. Sassan Alizadeh & Michael W. Brandt & Francis X. Diebold, 1999. "Range-Based Estimation of Stochastic Volatility Models or Exchange Rate Dynamics are More Interesting Than You Think," Center for Financial Institutions Working Papers 00-28, Wharton School Center for Financial Institutions, University of Pennsylvania.

    Cited by:

    1. Gregory Bauer & Keith Vorkink, 2007. "Multivariate Realized Stock Market Volatility," Staff Working Papers 07-20, Bank of Canada.
    2. John M. Maheu & Thomas McCurdy, 2001. "Nonlinear Features of Realized FX Volatility," CIRANO Working Papers 2001s-42, CIRANO.
    3. Tsiotas, Georgios, 2012. "On generalised asymmetric stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 56(1), pages 151-172, January.
    4. Bollerslev, Tim, 2001. "Financial econometrics: Past developments and future challenges," Journal of Econometrics, Elsevier, vol. 100(1), pages 41-51, January.
    5. Chen, Cathy W.S. & Gerlach, Richard & Lin, Edward M.H., 2008. "Volatility forecasting using threshold heteroskedastic models of the intra-day range," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2990-3010, February.
    6. Chan, Leo & Lien, Donald, 2003. "Using high, low, open, and closing prices to estimate the effects of cash settlement on futures prices," International Review of Financial Analysis, Elsevier, vol. 12(1), pages 35-47.
    7. Chan, Kam C. & Fung, Hung-Gay & Leung, Wai K., 2004. "Daily volatility behavior in Chinese futures markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 14(5), pages 491-505, December.
    8. Sin, Chor-Yiu (CY), 2013. "Using CARRX models to study factors affecting the volatilities of Asian equity markets," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 552-564.
    9. Venetis, Ioannis A. & Peel, David, 2005. "Non-linearity in stock index returns: the volatility and serial correlation relationship," Economic Modelling, Elsevier, vol. 22(1), pages 1-19, January.
    10. Chan, J.S.K. & Lam, C.P.Y. & Yu, P.L.H. & Choy, S.T.B. & Chen, C.W.S., 2012. "A Bayesian conditional autoregressive geometric process model for range data," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3006-3019.

  80. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 1999. "The Distribution of Exchange Rate Volatility," New York University, Leonard N. Stern School Finance Department Working Paper Seires 99-059, New York University, Leonard N. Stern School of Business-.

    Cited by:

    1. Sassan Alizadeh & Michael W. Brandt & Francis X. Diebold, 1999. "Range-Based Estimation of Stochastic Volatility Models or Exchange Rate Dynamics are More Interesting Than You Think," Center for Financial Institutions Working Papers 00-28, Wharton School Center for Financial Institutions, University of Pennsylvania.
    2. Ralf Becker & Adam Clements, 2007. "Are combination forecasts of S&P 500 volatility statistically superior?," NCER Working Paper Series 17, National Centre for Econometric Research.
    3. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 1999. "The Distribution of Exchange Rate Volatility," Center for Financial Institutions Working Papers 99-08, Wharton School Center for Financial Institutions, University of Pennsylvania.
    4. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2000. "Exchange Rate Returns Standardized by Realized Volatility are (Nearly) Gaussian," NBER Working Papers 7488, National Bureau of Economic Research, Inc.
    5. Ole E. Barndorff-Nielsen & Neil Shephard, 2001. "Econometric Analysis of Realised Covariation: High Frequency Covariance, Regression and Correlation in Financial Economics," Economics Papers 2002-W13, Economics Group, Nuffield College, University of Oxford, revised 18 Mar 2002.
    6. Klaassen, F.J.G.M., 1999. "Why is it so Difficult to Find An Effect of Exchange Rate Risk on Trade?," Discussion Paper 1999-73, Tilburg University, Center for Economic Research.
    7. Campbell, John Y & Kim, Sangjoon & Lettau, Martin, 1998. "Dispersion and Volatility in Stock Returns: An Empirical Investigation," CEPR Discussion Papers 1923, C.E.P.R. Discussion Papers.
    8. Eric Hillebrand & Marcelo Cunha Medeiros, 2007. "Forecasting realized volatility models:the benefits of bagging and nonlinear specifications," Textos para discussão 547, Department of Economics PUC-Rio (Brazil).
    9. John M. Maheu & Thomas McCurdy, 2001. "Nonlinear Features of Realized FX Volatility," CIRANO Working Papers 2001s-42, CIRANO.
    10. John Cotter, 2004. "Realized volatility and minimum capital requirements," Money Macro and Finance (MMF) Research Group Conference 2003 20, Money Macro and Finance Research Group.
    11. Ole E. Barndorff-Nielsen & Elisa Nicolato & Neil Shephard, 2001. "Some recent developments in stochastic volatility modelling," Economics Papers 2001-W25, Economics Group, Nuffield College, University of Oxford.
    12. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 1999. "(Understanding, Optimizing, Using and Forecasting) Realized Volatility and Correlation," New York University, Leonard N. Stern School Finance Department Working Paper Seires 99-061, New York University, Leonard N. Stern School of Business-.
    13. Ait-Sahalia, Yacine & Mykland, Per A. & Zhang, Lan, 2005. "Ultra high frequency volatility estimation with dependent microstructure noise," Discussion Paper Series 1: Economic Studies 2005,30, Deutsche Bundesbank.
    14. Laura Mayoral, 2005. "The persistence of inflation in OECD countries: A fractionally integrated approach," Economics Working Papers 958, Department of Economics and Business, Universitat Pompeu Fabra, revised Oct 2005.
    15. Nuno Cassola & Claudio Morana, 2006. "Volatility of interest rates in the euro area: Evidence from high frequency data," The European Journal of Finance, Taylor & Francis Journals, vol. 12(6-7), pages 513-528.
    16. John Y. Campbell & Martin Lettau & Burton G. Malkiel & Yexiao Xu, 2001. "Have Individual Stocks Become More Volatile? An Empirical Exploration of Idiosyncratic Risk," Journal of Finance, American Finance Association, vol. 56(1), pages 1-43, February.
    17. Nour Meddahi, 2002. "A theoretical comparison between integrated and realized volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 479-508.
    18. Nour Meddahi, 2003. "ARMA representation of integrated and realized variances," Econometrics Journal, Royal Economic Society, vol. 6(2), pages 335-356, December.
    19. Nour Meddahi & Eric Renault, 2000. "Temporal Aggregation of Volatility Models," CIRANO Working Papers 2000s-22, CIRANO.
    20. Stephan Schulmeister, 2000. "Technical Analysis and Exchange Rate Dynamics," WIFO Studies, WIFO, number 25857, April.
    21. Asger Lunde & Peter Reinhard Hansen, 2001. "A Forecast Comparison of Volatility Models: Does Anything Beat a GARCH(1,1)?," Working Papers 2001-04, Brown University, Department of Economics.
    22. Laurent-Emmanuel Calvet & Adlai J. Fisher, 2001. "Forecasting multifractal volatility," Post-Print hal-00477952, HAL.
    23. ANDERSEN, Torben G. & BOLLERSLEV, Tim & MEDDAHI, Nour, 2002. "Correcting the Errors : A Note on Volatility Forecast Evaluation Based on High-Frequency Data and Realized Volatilities," Cahiers de recherche 2002-21, Universite de Montreal, Departement de sciences economiques.
    24. Pérez, Ana & Ruiz Ortega, Esther, 2001. "Modelos de memoria larga para series económicas y financieras," DES - Documentos de Trabajo. Estadística y Econometría. DS ds010101, Universidad Carlos III de Madrid. Departamento de Estadística.
    25. Morana, Claudio & Beltratti, Andrea, 2004. "Structural change and long-range dependence in volatility of exchange rates: either, neither or both?," Journal of Empirical Finance, Elsevier, vol. 11(5), pages 629-658, December.
    26. Elena Andreou & Eric Ghysels, 2002. "Detecting multiple breaks in financial market volatility dynamics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 579-600.
    27. Barucci, Emilio & Reno, Roberto, 2002. "On measuring volatility and the GARCH forecasting performance," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 12(3), pages 183-200, July.
    28. van Mierlo, J.G.A., 2001. "Over de verhouding tussen overheid, marktwerking en privatisering. Een economische meta-analyse," Research Memorandum 014, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    29. Pérez, Ana & Ruiz Ortega, Esther, 1999. "Finite sample properties of a QML estimator of stochastic volatility models with long memory," DES - Working Papers. Statistics and Econometrics. WS 6360, Universidad Carlos III de Madrid. Departamento de Estadística.
    30. Friederich, Sylvain & Payne, Richard, 2002. "Dealer liquidity in an auction market: evidence fom the London Stock Exchange," LSE Research Online Documents on Economics 24947, London School of Economics and Political Science, LSE Library.
    31. Claudio Morana, 2004. "Frequency domain principal components estimation of fractionally cointegrated processes," Applied Economics Letters, Taylor & Francis Journals, vol. 11(13), pages 837-842.
    32. Nour Meddahi, 2001. "A Theoretical Comparison Between Integrated and Realized Volatilities," CIRANO Working Papers 2001s-71, CIRANO.
    33. Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "Predicting Volatility: Getting the Most out of Return Data Sampled at Different Frequencies," CIRANO Working Papers 2004s-19, CIRANO.
    34. Becker Ralf & Clements Adam E & Hurn Stan, 2011. "Semi-Parametric Forecasting of Realized Volatility," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(3), pages 1-23, May.
    35. Gerhard, Frank & Hautsch, Nikolaus, 1999. "Volatility Estimation on the Basis of Price Intensities," CoFE Discussion Papers 99/19, University of Konstanz, Center of Finance and Econometrics (CoFE).
    36. Carnero, María Ángeles & Peña, Daniel & Ruiz Ortega, Esther, 2001. "Outliers and conditional autoregressive heteroscedasticity in time series," DES - Working Papers. Statistics and Econometrics. WS ws010704, Universidad Carlos III de Madrid. Departamento de Estadística.
    37. Beine, Michel, 2004. "Conditional covariances and direct central bank interventions in the foreign exchange markets," Journal of Banking & Finance, Elsevier, vol. 28(6), pages 1385-1411, June.
    38. Bollerslev, Tim, 2001. "Financial econometrics: Past developments and future challenges," Journal of Econometrics, Elsevier, vol. 100(1), pages 41-51, January.
    39. Christian Schittenkopf & Peter Tino & Georg Dorffner, 2002. "The benefit of information reduction for trading strategies," Applied Economics, Taylor & Francis Journals, vol. 34(7), pages 917-930.
    40. Elena Andreou & Eric Ghysels, 2003. "Test for Breaks in the Conditional Co-Movements of Asset Returns," University of Cyprus Working Papers in Economics 3-2003, University of Cyprus Department of Economics.
    41. John Cotter, 2011. "Uncovering Long Memory in High Frequency UK Futures," Papers 1103.5651, arXiv.org.
    42. Dimitrios D. Thomakos & Michail S. Koubouros, 2005. "Realized Volatility and Asymmetries in the A.S.E. Returns," Finance 0507012, University Library of Munich, Germany, revised 17 Jan 2006.
    43. John W. Galbraith & Victoria Zinde-Walsh, 2001. "Properties of Estimates of Daily GARCH Parameters Basaed on Intra-Day Observations," CIRANO Working Papers 2001s-15, CIRANO.
    44. Degiannakis, Stavros, 2004. "Volatility Forecasting: Evidence from a Fractional Integrated Asymmetric Power ARCH Skewed-t Model," MPRA Paper 96330, University Library of Munich, Germany.
    45. Christian Bontemps & Nour Meddahi, 2002. "Testing Normality: A GMM Approach," CIRANO Working Papers 2002s-63, CIRANO.
    46. Eugenie Hol & Siem Jan Koopman, 2000. "Forecasting the Variability of Stock Index Returns with Stochastic Volatility Models and Implied Volatility," Tinbergen Institute Discussion Papers 00-104/4, Tinbergen Institute.
    47. Christodoulakis, George A. & Satchell, Stephen E., 2002. "Correlated ARCH (CorrARCH): Modelling the time-varying conditional correlation between financial asset returns," European Journal of Operational Research, Elsevier, vol. 139(2), pages 351-370, June.
    48. Fernando Moreno-Pino & Stefan Zohren, 2022. "DeepVol: Volatility Forecasting from High-Frequency Data with Dilated Causal Convolutions," Papers 2210.04797, arXiv.org, revised Oct 2022.
    49. Neil Shephard & Ole E. Barndorff-Nielsen & University of Aarhus, 2001. "Econometric Analysis of Realised Volatility and Its Use in Estimating Stochastic Volatility Models," Economics Series Working Papers 71, University of Oxford, Department of Economics.
    50. Ole E. Barndorff-Nielsen & Neil Shephard, 2003. "Impact of jumps on returns and realised variances: econometric analysis of time-deformed Levy processes," Economics Papers 2003-W12, Economics Group, Nuffield College, University of Oxford.
    51. Ole E. Barndorff-Nielsen & Svend Erik Graversen & Neil Shephard, 2003. "Power variation & stochastic volatility: a review and some new results," Economics Papers 2003-W19, Economics Group, Nuffield College, University of Oxford.
    52. Scott I White & Ralf Becker & Adam E Clements, 2004. "Forward looking information in S&P 500 options," Econometric Society 2004 Australasian Meetings 233, Econometric Society.
    53. Jumah, Adusei & Kunst, Robert M., 1999. "The Effects of Dollar/Sterling Exchange Rate Volatility on Futures Markets for Coffee and Cocoa," Economics Series 73, Institute for Advanced Studies.
    54. Torben G. Andersen & Tim Bollerslev & Nour Meddahi, 2002. "Analytic Evaluation of Volatility Forecasts," CIRANO Working Papers 2002s-90, CIRANO.
    55. Dmitri Koulikov, 2002. "Modeling Sequences of Long Memory Positive Weakly Stationary Random Variables," William Davidson Institute Working Papers Series 493, William Davidson Institute at the University of Michigan.
    56. Elena Andreou & Eric Ghysels, 2000. "Rolling-Sample Volatility Estimators: Some New Theoretical, Simulation and Empirical Results," CIRANO Working Papers 2000s-19, CIRANO.
    57. Ole E. Barndorff-Nielsen & Neil Shephard, 2002. "Estimating quadratic variation using realized variance," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 457-477.
    58. Murat Körs & Mehmet Baha Karan, 2023. "Stock exchange volatility forecasting under market stress with MIDAS regression," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 295-306, January.
    59. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Heiko Ebens, 2000. "The Distribution of Stock Return Volatility," NBER Working Papers 7933, National Bureau of Economic Research, Inc.
    60. Ole E. Barndorff-Nielsen & Bent Nielsen & Neil Shephard & Carla Ysusi, 2002. "Measuring and forecasting financial variability using realised variance with and without a model," Economics Papers 2002-W21, Economics Group, Nuffield College, University of Oxford.
    61. Jarl G. Kallberg & Paolo Pasquariello, 2005. "An Examination of the Asian Crisis: Regime Shifts in Currency and Equity Markets," The Journal of Business, University of Chicago Press, vol. 78(1), pages 169-212, January.
    62. Mapa, Dennis S., 2003. "A Range-Based GARCH Model for Forecasting Volatility," MPRA Paper 21323, University Library of Munich, Germany.
    63. Ole E. Barndorff-Nielsen & Neil Shephard, 2001. "Realised power variation and stochastic volatility models," Economics Papers 2001-W18, Economics Group, Nuffield College, University of Oxford.
    64. Mr. Armando Méndez Morales & Miss Liliana B Schumacher, 2003. "Market Volatility As a Financial Soundness Indicator: An Application to Israel," IMF Working Papers 2003/047, International Monetary Fund.
    65. Pascual, Lorenzo & Romo, Juan & Ruiz Ortega, Esther, 2000. "Forecasting returns and volatilities in GARCH processes using the bootstrap," DES - Working Papers. Statistics and Econometrics. WS 10059, Universidad Carlos III de Madrid. Departamento de Estadística.
    66. Brusco, Sandro & Manzano, Carolina & Tapia, Mikel, 2003. "Price discovery in the pre-opening period. theory and evidence from the madrid stock exchange," DEE - Working Papers. Business Economics. WB wb035814, Universidad Carlos III de Madrid. Departamento de Economía de la Empresa.
    67. Moosa, Imad A. & Bollen, Bernard, 2002. "A benchmark for measuring bias in estimated daily value at risk," International Review of Financial Analysis, Elsevier, vol. 11(1), pages 85-100.
    68. Stanley, H.E. & Gopikrishnan, P. & Plerou, V. & Amaral, L.A.N., 2000. "Quantifying fluctuations in economic systems by adapting methods of statistical physics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 287(3), pages 339-361.
    69. Pérez, Ana & Ruiz Ortega, Esther, 2001. "Properties of the sample autocorrelations in autoregressive stochastic volatllity models," DES - Working Papers. Statistics and Econometrics. WS ws011208, Universidad Carlos III de Madrid. Departamento de Estadística.
    70. Zhang, Lan & Mykland, Per A. & Ait-Sahalia, Yacine, 2005. "A Tale of Two Time Scales: Determining Integrated Volatility With Noisy High-Frequency Data," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 1394-1411, December.
    71. Ole E. Barndorff-Nielsen, 2004. "Power and Bipower Variation with Stochastic Volatility and Jumps," Journal of Financial Econometrics, Oxford University Press, vol. 2(1), pages 1-37.
    72. Laurini, Márcio Poletti & Portugal, Marcelo Savino, 2004. "Long memory in the R$ / US$ exchange rate: A robust analysis," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 24(1), May.
    73. GARCIA, René & RENAULT, Éric, 2000. "Latent Variable Models for Stochastic Discount Factors," Cahiers de recherche 2000-01, Universite de Montreal, Departement de sciences economiques.
    74. Veiga, Helena, 2006. "Volatility forecasts: a continuous time model versus discrete time models," DES - Working Papers. Statistics and Econometrics. WS ws062509, Universidad Carlos III de Madrid. Departamento de Estadística.
    75. Das, Suman & Roy, Saikat Sinha, 2023. "Following the leaders? A study of co-movement and volatility spillover in BRICS currencies," Economic Systems, Elsevier, vol. 47(2).
    76. Rohit Deo & Clifford Hurvich & Philippe Soulier & Yi Wang, 2005. "Propagation of Memory Parameter from Durations to Counts," Econometrics 0511010, University Library of Munich, Germany.
    77. Ole E. Barndorff-Nielsen & Neil Shephard, 2001. "Estimating quadratic variation using realised volatility," Economics Papers 2001-W20, Economics Group, Nuffield College, University of Oxford, revised 01 Nov 2001.
    78. Peter Christoffersen & Jinyong Hahn & Atsushi Inoue, 2001. "Testing and Comparing Value-at-Risk Measures," CIRANO Working Papers 2001s-03, CIRANO.
    79. Ole E. Barndorff-Nielsen & Neil Shephard, 2001. "Integrated OU Processes," Economics Papers 2001-W1, Economics Group, Nuffield College, University of Oxford.
    80. Ole E. Barndorff-Nielsen & Neil Shephard, 2001. "How accurate is the asymptotic approximation to the distribution of realised volatility?," Economics Papers 2001-W16, Economics Group, Nuffield College, University of Oxford.

  81. Francis X. Diebold & Anthony M. Santomero, 1999. "Financial Risk Management in a Volatile Global Environment," Center for Financial Institutions Working Papers 99-43, Wharton School Center for Financial Institutions, University of Pennsylvania.

    Cited by:

    1. Terence D.Agbeyegbe, 2003. "The tail behavior of stock index return on the Jamaican Stock Exchange," Economics Working Paper Archive at Hunter College 305, Hunter College Department of Economics.
    2. Andrew Kuritzkes & Til Schuermann & Scott M. Weiner, 2002. "Risk Measurement, Risk Management and Capital Adequacy in Financial Conglomerates," Center for Financial Institutions Working Papers 03-02, Wharton School Center for Financial Institutions, University of Pennsylvania.
    3. David L. Eckles & Anthony M. Santomero, 2000. "The determinants of success in the new financial services environment: now that firms can do everything, what should they do and why should regulators care?," Economic Policy Review, Federal Reserve Bank of New York, issue Oct, pages 11-23.
    4. Anthony M Santomero & David L. Eckles, 2000. "The Determinants Of Success In the New Financial Services Environment: Now That Firms Can Do Everything, What Should They Do And Why Should Regulators Care?," Center for Financial Institutions Working Papers 00-32, Wharton School Center for Financial Institutions, University of Pennsylvania.
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  82. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 1999. "Exchange Rate Returns Standardized by Realized Volatility are (Nearly) Gaussian," New York University, Leonard N. Stern School Finance Department Working Paper Seires 99-060, New York University, Leonard N. Stern School of Business-.

    Cited by:

    1. Takaishi, Tetsuya, 2018. "Bias correction in the realized stochastic volatility model for daily volatility on the Tokyo Stock Exchange," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 500(C), pages 139-154.
    2. Márcio Gomes Pinto Garcia & Marcelo Cunha Medeiros & Francisco Eduardo de Luna e Almeida Santos, 2014. "Economic gains of realized volatility in the Brazilian stock market," Brazilian Review of Finance, Brazilian Society of Finance, vol. 12(3), pages 319-349.
    3. Degiannakis, Stavros & Floros, Christos, 2014. "Intra-Day Realized Volatility for European and USA Stock Indices," MPRA Paper 64940, University Library of Munich, Germany, revised Jan 2015.
    4. Cotter, John, 2004. "Varying the VaR for Unconditional and Conditional Environments," MPRA Paper 3483, University Library of Munich, Germany.
    5. Ferland, Rene & Lalancette, Simon, 2006. "Dynamics of realized volatilities and correlations: An empirical study," Journal of Banking & Finance, Elsevier, vol. 30(7), pages 2109-2130, July.
    6. Mihaela Craioveanu & Eric Hillebrand, 2012. "Why It Is Ok To Use The Har-Rv(1,5,21) Model," Working Papers 1201, University of Central Missouri, Department of Economics & Finance, revised Aug 2012.
    7. Hooper, Vincent J. & Ng, Kevin & Reeves, Jonathan J., 2008. "Quarterly beta forecasting: An evaluation," International Journal of Forecasting, Elsevier, vol. 24(3), pages 480-489.
    8. Filip Žikeš & Jozef Baruník, 2016. "Semi-parametric Conditional Quantile Models for Financial Returns and Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 14(1), pages 185-226.
    9. Mueller, Philippe & Stathopoulos, Andreas & Vedolin, Andrea, 2014. "International correlation risk," LSE Research Online Documents on Economics 60955, London School of Economics and Political Science, LSE Library.
    10. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2002. "Parametric and Nonparametric Volatility Measurement," Center for Financial Institutions Working Papers 02-27, Wharton School Center for Financial Institutions, University of Pennsylvania.
    11. Weiß, Gregor N.F. & Supper, Hendrik, 2013. "Forecasting liquidity-adjusted intraday Value-at-Risk with vine copulas," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3334-3350.
    12. Degiannakis, Stavros & Xekalaki, Evdokia, 2007. "Assessing the Performance of a Prediction Error Criterion Model Selection Algorithm in the Context of ARCH Models," MPRA Paper 96324, University Library of Munich, Germany.
    13. Tetsuya Takaishi, 2016. "Dynamical cross-correlation of multiple time series Ising model," Evolutionary and Institutional Economics Review, Springer, vol. 13(2), pages 455-468, December.
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    15. Sebastien Valeyre, 2022. "Optimal trend following portfolios," Papers 2201.06635, arXiv.org.
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    18. Clements, Michael P. & Galvão, Ana Beatriz & Kim, Jae H., 2006. "Quantile Forecasts of Daily Exchange Rate Returns from Forecasts of Realized Volatility," The Warwick Economics Research Paper Series (TWERPS) 777, University of Warwick, Department of Economics.
    19. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 1999. "(Understanding, Optimizing, Using and Forecasting) Realized Volatility and Correlation," New York University, Leonard N. Stern School Finance Department Working Paper Seires 99-061, New York University, Leonard N. Stern School of Business-.
    20. M Ali Kemal, 2005. "Exchange Rate Instability and Trade: The Case of Pakistan," PIDE Research Report 2005:186, Pakistan Institute of Development Economics.
    21. George Jiang & Ingrid Lo, 2011. "Private Information Flow and Price Discovery in the U.S. Treasury Market," Staff Working Papers 11-5, Bank of Canada.
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    58. Georgios Chortareas & John Nankervis & Ying Jiang, 2007. "Forecasting Exchange Rate Volatility with High Frequency Data: Is the Euro Different?," Money Macro and Finance (MMF) Research Group Conference 2006 79, Money Macro and Finance Research Group.
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    61. Yalama, Abdullah & Celik, Sibel, 2013. "Real or spurious long memory characteristics of volatility: Empirical evidence from an emerging market," Economic Modelling, Elsevier, vol. 30(C), pages 67-72.
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    63. Bo Young Chang & Bruno Feunou, 2013. "Measuring Uncertainty in Monetary Policy Using Implied Volatility and Realized Volatility," Staff Working Papers 13-37, Bank of Canada.
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    67. Rim Ammar Lamouchi & Ruba Khalid Shira, 2023. "Heterogeneous Behavior and Volatility Transmission in the Forex Market using High-Frequency Data," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 13(3), pages 1-3.
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    Cited by:

    1. Lenarčič, Črt & Zorko, Robert & Herman, Uroš & Savšek, Simon, 2016. "A Primer on Slovene House Prices Forecast," MPRA Paper 103552, University Library of Munich, Germany.
    2. Narayan, Paresh Kumar & Liu, Ruipeng, 2015. "A unit root model for trending time-series energy variables," Energy Economics, Elsevier, vol. 50(C), pages 391-402.
    3. Hansen, Bruce E., 2010. "Averaging estimators for autoregressions with a near unit root," Journal of Econometrics, Elsevier, vol. 158(1), pages 142-155, September.
    4. Marcellino, Massimiliano, 2002. "Forecasting EMU Macroeconomic Variables," CEPR Discussion Papers 3529, C.E.P.R. Discussion Papers.
    5. Pan, Guochen & Chang, Hsu-Ling & Su, Chi-Wei, 2012. "Regional differences in development of life insurance markets in China," Emerging Markets Review, Elsevier, vol. 13(4), pages 548-558.
    6. Mohitosh Kejriwal & Xuewen Yu, 2019. "Generalized Forecasr Averaging in Autoregressions with a Near Unit Root," Purdue University Economics Working Papers 1318, Purdue University, Department of Economics.
    7. Tsangyao Chang & Wen-Chi Liu & Goodness C. Aye & Rangan Gupta, 2016. "Are there housing bubbles in South Africa? Evidence from SPSM-based panel KSS test with a Fourier function," Global Business and Economics Review, Inderscience Enterprises Ltd, vol. 18(5), pages 517-532.
    8. Alberto Baffigi & Roberto Golinelli & Giuseppe Parigi, 2002. "Real-time GDP forecasting in the euro area," Temi di discussione (Economic working papers) 456, Bank of Italy, Economic Research and International Relations Area.
    9. Massimiliano Marcellino, "undated". "Instability and non-linearity in the EMU," Working Papers 211, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    10. Peter C. B. Phillips & Zhentao Shi, 2021. "Boosting: Why You Can Use The Hp Filter," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 62(2), pages 521-570, May.
    11. Junsoo Lee & John A. List & Mark Strazicich, 2005. "Nonrenewable Resource Prices: Deterministic or Stochastic Trends?," NBER Working Papers 11487, National Bureau of Economic Research, Inc.
    12. Massimiliano Marcellino, 2008. "A linear benchmark for forecasting GDP growth and inflation?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(4), pages 305-340.
    13. Christiane Baumeister & Lutz Kilian & Thomas K. Lee, 2016. "Inside the Crystal Ball: New Approaches to Predicting the Gasoline Price at the Pump," CESifo Working Paper Series 5759, CESifo.
    14. Ali F. Darrat & Omar M. Benkato, 2003. "Interdependence and Volatility Spillovers Under Market Liberalization: The Case of Istanbul Stock Exchange," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 30(7‐8), pages 1089-1114, September.
    15. Simonetta Longhi & Peter Nijkamp & Aura Reggianni & Erich Maierhofer, 2005. "Neural Network Modeling as a Tool for Forecasting Regional Employment Patterns," International Regional Science Review, , vol. 28(3), pages 330-346, July.
    16. Ralf Brüggemann & Helmut Lütkepohl & Massimiliano Marcellino, 2008. "Forecasting euro area variables with German pre-EMU data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(6), pages 465-481.
    17. Timmermann, Allan & Elliott, Graham, 2007. "Economic Forecasting," CEPR Discussion Papers 6158, C.E.P.R. Discussion Papers.
    18. Giorgio Canarella & Stephen M. Miller & Stephen K. Pollard, 2013. "Unemployment Rate Hysteresis and the Great Recession: Exploring the Metropolitan Evidence," Working papers 2013-19, University of Connecticut, Department of Economics.
    19. George Athanasopoulos & Rob J Hyndman & Haiyan Song & Doris C Wu, 2008. "The tourism forecasting competition," Monash Econometrics and Business Statistics Working Papers 10/08, Monash University, Department of Econometrics and Business Statistics, revised Oct 2009.
    20. Ron Alquist & Lutz Kilian, 2010. "What do we learn from the price of crude oil futures?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 539-573.
    21. Manuel Landajo & Mar'ia Jos'e Presno, 2024. "The prices of renewable commodities: A robust stationarity analysis," Papers 2402.01005, arXiv.org.
    22. Ghoshray, A., 2018. "The Dynamic Properties of Natural Resource Prices," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277210, International Association of Agricultural Economists.
    23. Tsangyao Chang & Tsung-Pao Wu & Rangan Gupta, 2015. "Are house prices in South Africa really nonstationary? Evidence from SPSM-based panel KSS test with a Fourier function," Applied Economics, Taylor & Francis Journals, vol. 47(1), pages 32-53, January.
    24. Van Heerden, Dorathea & Rodrigues, Jose & Hockly, Dale & Lambert, Bongani & Taljard, Tjaart & Phiri, Andrew, 2013. "Efficient Market Hypothesis in South Africa: Evidence from a threshold autoregressive (TAR) model," MPRA Paper 50544, University Library of Munich, Germany.
    25. Ted Peterson & Zachary Bair, 2022. "United States Tax Rates and Economic Growth," SAGE Open, , vol. 12(3), pages 21582440221, July.
    26. Peter C.B. Phillips & Zhentao Shi, 2019. "Boosting the Hodrick-Prescott Filter," Cowles Foundation Discussion Papers 2192, Cowles Foundation for Research in Economics, Yale University.
    27. Severin Borenstein & James Bushnell & Frank A. Wolak & Matthew Zaragoza-Watkins, 2015. "Expecting the Unexpected: Emissions Uncertainty and Environmental Market Design," NBER Working Papers 20999, National Bureau of Economic Research, Inc.
    28. David Griffiths, 2004. "The big problem of forecasting small change," Applied Economics, Taylor & Francis Journals, vol. 36(19), pages 2195-2207.
    29. Hubrich, Kirstin, 2005. "Forecasting euro area inflation: Does aggregating forecasts by HICP component improve forecast accuracy?," International Journal of Forecasting, Elsevier, vol. 21(1), pages 119-136.
    30. Manuel Landajo & María Presno, 2013. "Nonparametric pseudo-Lagrange multiplier stationarity testing," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 65(1), pages 125-147, February.
    31. Rambeli, Norimah & Awang Marikan, Dayang Affizah & Hashim, Emilda & Mohd. Ariffin, Siti Zubaidah & Hashim, Asmawi & M. Podivinsky, Jan, 2021. "The Determinants of Carbon Dioxide Emissions in Malaysia and Singapore," Jurnal Ekonomi Malaysia, Faculty of Economics and Business, Universiti Kebangsaan Malaysia, vol. 55(2), pages 107-119.
    32. Lee, Cheng-Feng & Tsong, Ching-Chuan, 2009. "Bootstrapping covariate stationarity tests for inflation rates," Economic Modelling, Elsevier, vol. 26(6), pages 1443-1448, November.
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    42. Ahmad Nasseri & Mohammad Sayyadi & Hassan Yazdifar & Rasol Eskandari & Mohammad Albahloul, 2018. "Causality between Cash Flow and Earnings: Evidence from Tehran (Iran) Stock Exchange," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 17(2), pages 210-228, August.
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    45. Massimiliano Marcellino, "undated". "Forecast pooling for short time series of macroeconomic variables," Working Papers 212, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    46. Cheng-Feng Lee & Ching-Chuan Tsong, 2013. "Bootstrapping Covariate Unit Root Tests: An Application To Inflation Rates," Bulletin of Economic Research, Wiley Blackwell, vol. 65, pages 165-174, May.
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    48. Renata Grzeda Latocha & Gernot Nerb, 2004. "Modelling Short-term Interest Rates in the Euro Area Using Business Survey Data," Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2004(1), pages 43-69.
    49. Capistrán, Carlos & Constandse, Christian & Ramos-Francia, Manuel, 2010. "Multi-horizon inflation forecasts using disaggregated data," Economic Modelling, Elsevier, vol. 27(3), pages 666-677, May.
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    51. Hendry, David F. & Hubrich, Kirstin, 2006. "Forecasting economic aggregates by disaggregates," Working Paper Series 589, European Central Bank.
    52. Manuel Landajo & María José Presno, 2022. "The prices of renewable commodities: a robust stationarity analysis," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 66(2), pages 447-470, April.
    53. Capistrán Carlos & Constandse Christian & Ramos Francia Manuel, 2009. "Using Seasonal Models to Forecast Short-Run Inflation in Mexico," Working Papers 2009-05, Banco de México.
    54. Collin Philipps & Sebastian Laumer, 2022. "Government Spending between Active and Passive Monetary Policy," Working Papers 2022-04, Department of Economics and Geosciences, US Air Force Academy.
    55. Duarte, Claudia & Rua, Antonio, 2007. "Forecasting inflation through a bottom-up approach: How bottom is bottom?," Economic Modelling, Elsevier, vol. 24(6), pages 941-953, November.
    56. Blerina Vika & Ilir Vika, 2021. "Forecasting Albanian Time Series with Linear and Nonlinear Univariate Models," Academic Journal of Interdisciplinary Studies, Richtmann Publishing Ltd, vol. 10, September.
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    58. Junsoo Lee & John List, 2004. "Examining Trends of Criteria Air Pollutants: Are the Effects of Governmental Intervention Transitory?," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 29(1), pages 21-37, September.
    59. In Choi & Hanbat Jeong, 2020. "Differencing versus nondifferencing in factor‐based forecasting," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(6), pages 728-750, September.
    60. E Pavlidis & I Paya & D Peel, 2009. "Forecasting the Real Exchange Rate using a Long Span of Data. A Rematch: Linear vs Nonlinear," Working Papers 601190, Lancaster University Management School, Economics Department.
    61. Sarno, Lucio & Daniel l Thornton & Giorgio Valente, 2003. "Federal Funds Rate Prediction," Royal Economic Society Annual Conference 2003 183, Royal Economic Society.
    62. Shujie Shen & Gang Li & Haiyan Song, 2009. "Effect of Seasonality Treatment on the Forecasting Performance of Tourism Demand Models," Tourism Economics, , vol. 15(4), pages 693-708, December.
    63. Tsangyao CHANG & Yifei CAI & Wen-Yi CHEN, 2017. "Are Suicide Rate Fluctuations Transitory or Permanent? Panel KSS Unit Root Test with a Fourier Function through the Sequential Panel Selection Method," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 5-17, September.
    64. Khalaf, Lynda & Saunders, Charles J., 2017. "Monte Carlo forecast evaluation with persistent data," International Journal of Forecasting, Elsevier, vol. 33(1), pages 1-10.
    65. Mohitosh Kejriwal & Linh Nguyen & Xuewen Yu, 2023. "Multistep Forecast Averaging with Stochastic and Deterministic Trends," Econometrics, MDPI, vol. 11(4), pages 1-44, December.
    66. Jae H. Kim & In Choi, 2017. "Unit Roots in Economic and Financial Time Series: A Re-Evaluation at the Decision-Based Significance Levels," Econometrics, MDPI, vol. 5(3), pages 1-23, September.
    67. Jardet, C. & Monfort, A. & Pegoraro, F., 2009. "No-arbitrage Near-Cointegrated VAR(p) Term Structure Models, Term Premia and GDP Growth," Working papers 234, Banque de France.
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    71. Barakchian , Seyed Mahdi & Bayat , Saeed & Karami , Hooman, 2013. "Common Factors of CPI Sub-aggregates and Forecast of Inflation," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 8(4), pages 1-17, October.
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    80. Massimiliano Marcellino, 2004. "Forecast Pooling for European Macroeconomic Variables," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(1), pages 91-112, February.
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  84. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 1999. "(Understanding, Optimizing, Using and Forecasting) Realized Volatility and Correlation," New York University, Leonard N. Stern School Finance Department Working Paper Seires 99-061, New York University, Leonard N. Stern School of Business-.

    Cited by:

    1. Ralf Becker & Adam Clements, 2007. "Are combination forecasts of S&P 500 volatility statistically superior?," NCER Working Paper Series 17, National Centre for Econometric Research.
    2. Elisa Alòs & Maria Elvira Mancino & Tai-Ho Wang, 2019. "Volatility and volatility-linked derivatives: estimation, modeling, and pricing," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 42(2), pages 321-349, December.
    3. Long H. Vo, 2017. "Estimating Financial Volatility with High-Frequency Returns," Journal of Finance and Economics Research, Geist Science, Iqra University, Faculty of Business Administration, vol. 2(2), pages 84-114, October.
    4. Karthik Raju & Saravanan Rangaswamy, 2017. "Forecasting volatility in the Indian equity market using return and range-based models," Applied Economics, Taylor & Francis Journals, vol. 49(49), pages 5027-5039, October.
    5. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
    6. Becker, Ralf & Clements, Adam E. & White, Scott I., 2007. "Does implied volatility provide any information beyond that captured in model-based volatility forecasts?," Journal of Banking & Finance, Elsevier, vol. 31(8), pages 2535-2549, August.
    7. Maria Elvira Mancino & Simona Sanfelici, 2011. "Estimation of Quarticity with High Frequency Data," Working Papers - Mathematical Economics 2011-06, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa, revised Jan 2012.
    8. Byun, Suk Joon & Cho, Hangjun, 2013. "Forecasting carbon futures volatility using GARCH models with energy volatilities," Energy Economics, Elsevier, vol. 40(C), pages 207-221.
    9. Bien, Katarzyna & Nolte, Ingmar & Pohlmeier, Winfried, 2007. "An inflated Multivariate Integer Count Hurdle model: An application to bid and ask quote dynamics," CoFE Discussion Papers 07/04, University of Konstanz, Center of Finance and Econometrics (CoFE).
    10. LAURENT, Sébastien & ROMBOUTS, Jeroen V. K. & VIOLANTE, Francesco, 2010. "On the forecasting accuracy of multivariate GARCH models," LIDAM Discussion Papers CORE 2010025, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    11. Ai-ru (Meg) Cheng & Kuntal Das & Takeshi Shimatani, 2013. "Central Bank Intervention and Exchange Rate Volatility: Evidence from Japan Using Realized Volatility," Working Papers in Economics 13/19, University of Canterbury, Department of Economics and Finance.
    12. Giorgio Mirone, 2017. "Inference from the futures: ranking the noise cancelling accuracy of realized measures," CREATES Research Papers 2017-24, Department of Economics and Business Economics, Aarhus University.
    13. Becker Ralf & Clements Adam E & Hurn Stan, 2011. "Semi-Parametric Forecasting of Realized Volatility," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(3), pages 1-23, May.
    14. Nolte, Ingmar & Voev, Valeri, 2007. "Estimating high-frequency based (co-) variances: A unified approach," CoFE Discussion Papers 07/07, University of Konstanz, Center of Finance and Econometrics (CoFE).
    15. Katarzyna Bien & Ingmar Nolte & Winfried Pohlmeier, 2008. "A multivariate integer count hurdle model: theory and application to exchange rate dynamics," Studies in Empirical Economics, in: Luc Bauwens & Winfried Pohlmeier & David Veredas (ed.), High Frequency Financial Econometrics, pages 31-48, Springer.
    16. Ralf Becker & Adam Clements & Andrew McClelland, 2008. "The Jump component of S&P 500 volatility and the VIX index," NCER Working Paper Series 24, National Centre for Econometric Research.
    17. Sébastien Laurent & Jeroen V.K. Rombouts & Francesco Violante, 2009. "On Loss Functions and Ranking Forecasting Performances of Multivariate Volatility Models," Cahiers de recherche 0948, CIRPEE.
    18. Becker, Ralf & Clements, Adam E. & White, Scott I., 2006. "On the informational efficiency of S&P500 implied volatility," The North American Journal of Economics and Finance, Elsevier, vol. 17(2), pages 139-153, August.
    19. Long, Xiangdong & Su, Liangjun & Ullah, Aman, 2011. "Estimation and Forecasting of Dynamic Conditional Covariance: A Semiparametric Multivariate Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 109-125.
    20. Mancino, M.E. & Sanfelici, S., 2008. "Robustness of Fourier estimator of integrated volatility in the presence of microstructure noise," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2966-2989, February.
    21. Ghorbel, Ahmed & Trabelsi, Abdelwahed, 2007. "Predictive Performance of Conditional Extreme Value Theory and Conventional Methods in Value at Risk Estimation," MPRA Paper 3963, University Library of Munich, Germany.
    22. Gang-Zhi Fan & Zsuzsa Huszár & Weina Zhang, 2013. "The Relationships between Real Estate Price and Expected Financial Asset Risk and Return: Theory and Empirical Evidence," The Journal of Real Estate Finance and Economics, Springer, vol. 46(4), pages 568-595, May.
    23. Scott I. White & Adam E. Clements & Stan Hurn, 2004. "Discretised Non-Linear Filtering for Dynamic Latent Variable Models: with Application to Stochastic Volatility," Econometric Society 2004 Australasian Meetings 46, Econometric Society.
    24. Adam Clements & Annastiina Silvennoinen, 2009. "On the economic benefit of utility based estimation of a volatility model," NCER Working Paper Series 44, National Centre for Econometric Research.
    25. Małgorzata Just & Aleksandra Łuczak, 2020. "Assessment of Conditional Dependence Structures in Commodity Futures Markets Using Copula-GARCH Models and Fuzzy Clustering Methods," Sustainability, MDPI, vol. 12(6), pages 1-22, March.
    26. Georgios Chortareas & John Nankervis & Ying Jiang, 2007. "Forecasting Exchange Rate Volatility with High Frequency Data: Is the Euro Different?," Money Macro and Finance (MMF) Research Group Conference 2006 79, Money Macro and Finance Research Group.
    27. Scott I White & Ralf Becker & Adam E Clements, 2004. "Forward looking information in S&P 500 options," Econometric Society 2004 Australasian Meetings 233, Econometric Society.
    28. Yalama, Abdullah & Celik, Sibel, 2013. "Real or spurious long memory characteristics of volatility: Empirical evidence from an emerging market," Economic Modelling, Elsevier, vol. 30(C), pages 67-72.
    29. Linlan Xiao & Vigdis Boasson & Sergey Shishlenin & Victoria Makushina, 2018. "Volatility forecasting: combinations of realized volatility measures and forecasting models," Applied Economics, Taylor & Francis Journals, vol. 50(13), pages 1428-1441, March.
    30. Benavides Guillermo & Capistrán Carlos, 2009. "Forecasting Exchange Rate Volatility: The Superior Performance of Conditional Combinations of Time Series and Option Implied Forecasts," Working Papers 2009-01, Banco de México.
    31. Fei, Tianlun & Liu, Xiaoquan & Wen, Conghua, 2019. "Cross-sectional return dispersion and volatility prediction," Pacific-Basin Finance Journal, Elsevier, vol. 58(C).
    32. Aldrich, Eric M. & Heckenbach, Indra & Laughlin, Gregory, 2016. "A compound duration model for high-frequency asset returns," Journal of Empirical Finance, Elsevier, vol. 39(PA), pages 105-128.
    33. Selma Chaker & Nour Meddahi, 2013. "A Distributional Approach to Realized Volatility," Staff Working Papers 13-49, Bank of Canada.
    34. Karmakar, Madhusudan & Paul, Samit, 2016. "Intraday risk management in International stock markets: A conditional EVT approach," International Review of Financial Analysis, Elsevier, vol. 44(C), pages 34-55.
    35. Amir Safari & Detlef Seese, 2010. "Behavior of realized volatility and correlation in exchange markets," International Econometric Review (IER), Econometric Research Association, vol. 2(2), pages 73-96, September.
    36. Bandi, Federico M. & Russell, Jeffrey R. & Yang, Chen, 2008. "Realized volatility forecasting and option pricing," Journal of Econometrics, Elsevier, vol. 147(1), pages 34-46, November.
    37. Daniel Djupsjobacka, 2010. "Implications of market microstructure for realized variance measurement," The European Journal of Finance, Taylor & Francis Journals, vol. 16(1), pages 27-43.
    38. Chu, Carlin C.F. & Lam, K.P., 2011. "Modeling intraday volatility: A new consideration," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 21(3), pages 388-418, July.
    39. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2005. "Volatility forecasting," CFS Working Paper Series 2005/08, Center for Financial Studies (CFS).
    40. Eugenie Hol & Siem Jan Koopman, 2002. "Stock Index Volatility Forecasting with High Frequency Data," Tinbergen Institute Discussion Papers 02-068/4, Tinbergen Institute.
    41. Antonakakis, Nikolaos & Darby, Julia, 2012. "Forecasting Volatility in Developing Countries' Nominal Exchange Returns," MPRA Paper 40875, University Library of Munich, Germany.
    42. E. C. Brechmann & M. Heiden & Y. Okhrin, 2018. "A multivariate volatility vine copula model," Econometric Reviews, Taylor & Francis Journals, vol. 37(4), pages 281-308, April.
    43. Fei Su, 2018. "Essays on Price Discovery and Volatility Dynamics in the Foreign Exchange Market," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 2-2018.
    44. Roland Füss & Ferdinand Mager & Michael Stein & Lu Zhao, 2018. "Financial crises, price discovery, and information transmission: a high-frequency perspective," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 32(4), pages 333-365, November.
    45. Su, Fei & Zhang, Jingjing, 2018. "Global price discovery in the Australian dollar market and its determinants," Pacific-Basin Finance Journal, Elsevier, vol. 48(C), pages 35-55.
    46. Dimpfl, Thomas & Peter, Franziska J., 2021. "Nothing but noise? Price discovery across cryptocurrency exchanges," Journal of Financial Markets, Elsevier, vol. 54(C).
    47. Adam Clements & Ralf Becker, 2009. "A nonparametric approach to forecasting realized volatility," NCER Working Paper Series 43, National Centre for Econometric Research.
    48. Wang, Yuanfang & Roberts, Matthew C., 2005. "Realized Volatility in the Agricultural Futures Market," 2005 Annual meeting, July 24-27, Providence, RI 19211, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    49. A. Saichev & D. Sornette, 2014. "A simple microstructure return model explaining microstructure noise and Epps effects," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 25(06), pages 1-36.
    50. André Schöne, 2010. "Zum Informationsgehalt der Volatilitätsindizes VDAX und VDAX-New der Deutsche Börse AG," Schmalenbach Journal of Business Research, Springer, vol. 62(6), pages 625-661, September.

  85. Francis X. Diebold & Til Schuermann & John D. Stroughair, 1998. "Pitfalls and Opportunities in the Use of Extreme Value Theory in Risk Management," New York University, Leonard N. Stern School Finance Department Working Paper Seires 98-081, New York University, Leonard N. Stern School of Business-.

    Cited by:

    1. Cotter, John, 2004. "Varying the VaR for Unconditional and Conditional Environments," MPRA Paper 3483, University Library of Munich, Germany.
    2. Odening, Martin & Hinrichs, Jan, 2003. "Die Quantifizierung von Marktrisiken in der Tierproduktion mittels Value-at-Risk und Extreme-Value-Theory," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 52(02), pages 1-11.
    3. Turan G. Bali, 2007. "A Generalized Extreme Value Approach to Financial Risk Measurement," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(7), pages 1613-1649, October.
    4. Loriano Mancini & Fabio Trojani, 2011. "Robust Value at Risk Prediction," Journal of Financial Econometrics, Oxford University Press, vol. 9(2), pages 281-313, Spring.
    5. Luca Erzegovesi, 2002. "VaR and Liquidity Risk.Impact on Market Behaviour and Measurement Issues," Alea Tech Reports 014, Department of Computer and Management Sciences, University of Trento, Italy, revised 14 Jun 2008.
    6. Jimenez-Martin, Juan-Angel & McAleer, Michael & Pérez-Amaral, Teodosio & Santos, Paulo Araújo, 2013. "GFC-robust risk management under the Basel Accord using extreme value methodologies," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 94(C), pages 223-237.
    7. Dimitrakopoulos, Dimitris N. & Kavussanos, Manolis G. & Spyrou, Spyros I., 2010. "Value at risk models for volatile emerging markets equity portfolios," The Quarterly Review of Economics and Finance, Elsevier, vol. 50(4), pages 515-526, November.
    8. Jobst, Andreas A., 2002. "The Pricing puzzle: The default term structure of collateralised loan obligations," CFS Working Paper Series 2002/14, Center for Financial Studies (CFS).
    9. Marco Rocco, 2011. "Extreme value theory for finance: a survey," Questioni di Economia e Finanza (Occasional Papers) 99, Bank of Italy, Economic Research and International Relations Area.
    10. Sarafrazi, Soodabeh & Hammoudeh, Shawkat & AraújoSantos, Paulo, 2014. "Downside risk, portfolio diversification and the financial crisis in the euro-zone," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 32(C), pages 368-396.
    11. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005. "Practical Volatility and Correlation Modeling for Financial Market Risk Management," PIER Working Paper Archive 05-007, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    12. Wagner, Niklas & Marsh, Terry A., 2005. "Measuring tail thickness under GARCH and an application to extreme exchange rate changes," Journal of Empirical Finance, Elsevier, vol. 12(1), pages 165-185, January.
    13. Bystrom, Hans N. E., 2004. "Managing extreme risks in tranquil and volatile markets using conditional extreme value theory," International Review of Financial Analysis, Elsevier, vol. 13(2), pages 133-152.
    14. Daniele Massacci, 2017. "Tail Risk Dynamics in Stock Returns: Links to the Macroeconomy and Global Markets Connectedness," Management Science, INFORMS, vol. 63(9), pages 3072-3089, September.
    15. Marco Moscadelli, 2004. "The modelling of operational risk: experience with the analysis of the data collected by the Basel Committee," Temi di discussione (Economic working papers) 517, Bank of Italy, Economic Research and International Relations Area.
    16. Singh, Abhay K. & Allen, David E. & Robert, Powell J., 2013. "Extreme market risk and extreme value theory," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 94(C), pages 310-328.
    17. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2011. "Financial Risk Measurement for Financial Risk Management," CREATES Research Papers 2011-37, Department of Economics and Business Economics, Aarhus University.
    18. Odening, Martin & Hinrichs, Jan, 2002. "Assessment Of Market Risk In Hog Production Using Value-At-Risk And Extreme Value Theory," 2002 Annual meeting, July 28-31, Long Beach, CA 19907, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    19. POON, Ser-Huang & ROCKINGER, Michael & TAWN, Jonathan, 2001. "New Extreme-Value Dependance Measures and Finance Applications," HEC Research Papers Series 719, HEC Paris.
    20. Timotheos Angelidis & Alexandros Benos & Stavros Degiannakis, 2007. "A robust VaR model under different time periods and weighting schemes," Review of Quantitative Finance and Accounting, Springer, vol. 28(2), pages 187-201, February.
    21. Peter F. Christoffersen & Francis X. Diebold, 1998. "How Relevant is Volatility Forecasting for Financial Risk Management?," NBER Working Papers 6844, National Bureau of Economic Research, Inc.
    22. Bali, Turan G. & Weinbaum, David, 2007. "A conditional extreme value volatility estimator based on high-frequency returns," Journal of Economic Dynamics and Control, Elsevier, vol. 31(2), pages 361-397, February.
    23. Manfred Gilli & Evis këllezi, 2006. "An Application of Extreme Value Theory for Measuring Financial Risk," Computational Economics, Springer;Society for Computational Economics, vol. 27(2), pages 207-228, May.
    24. Huang, Wei & Liu, Qianqiu & Ghon Rhee, S. & Wu, Feng, 2012. "Extreme downside risk and expected stock returns," Journal of Banking & Finance, Elsevier, vol. 36(5), pages 1492-1502.
    25. Antonio Díaz & Gonzalo García-Donato & Andrés Mora-Valencia, 2017. "Risk quantification in turmoil markets," Risk Management, Palgrave Macmillan, vol. 19(3), pages 202-224, August.
    26. Ghorbel, Ahmed & Trabelsi, Abdelwahed, 2007. "Predictive Performance of Conditional Extreme Value Theory and Conventional Methods in Value at Risk Estimation," MPRA Paper 3963, University Library of Munich, Germany.
    27. Zhang, Zhengjun & Huang, James, 2006. "Extremal financial risk models and portfolio evaluation," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2313-2338, December.
    28. Peter F. Christoffersen & Francis X. Diebold & Til Schuermann, 1998. "Horizon Problems and Extreme Events in Financial Risk Management," Center for Financial Institutions Working Papers 98-16, Wharton School Center for Financial Institutions, University of Pennsylvania.
    29. Chavez-Demoulin, V. & Embrechts, P. & Sardy, S., 2014. "Extreme-quantile tracking for financial time series," Journal of Econometrics, Elsevier, vol. 181(1), pages 44-52.
    30. Chia-Lin Chang & Lydia González-Serrano & Juan-Ángel Jiménez-Martín, 2011. "Currency Hedging Strategies Using Dynamic Multivariate GARCH," Documentos de Trabajo del ICAE 2011-33, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    31. Aboura, Sofiane & Wagner, Niklas, 2016. "Extreme asymmetric volatility: Stress and aggregate asset prices," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 41(C), pages 47-59.
    32. Zhao, Zifeng & Zhang, Zhengjun & Chen, Rong, 2018. "Modeling maxima with autoregressive conditional Fréchet model," Journal of Econometrics, Elsevier, vol. 207(2), pages 325-351.
    33. José L. B. Fernandes & Augusto Hasman & Juan Ignacio Peña, 2006. "Risk Premium: Insights Over The Threshold," Working Papers Series 126, Central Bank of Brazil, Research Department.
    34. Alfredo Calderon Vela & Gabriel Rodríguez, 2014. "Extreme Value Theory: An Application to the Peruvian Stock Market Returns," Documentos de Trabajo / Working Papers 2014-394, Departamento de Economía - Pontificia Universidad Católica del Perú.
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    Cited by:

    1. Lopez, Jose A. & Saidenberg, Marc R., 2000. "Evaluating credit risk models," Journal of Banking & Finance, Elsevier, vol. 24(1-2), pages 151-165, January.
    2. Stefan Jaschke & Gerhard Stahl & Richard Stehle, 2007. "Value-at-risk forecasts under scrutiny—the German experience," Quantitative Finance, Taylor & Francis Journals, vol. 7(6), pages 621-636.

  87. Peter F. Christoffersen & Francis X. Diebold & Til Schuermann, 1998. "Horizon Problems and Extreme Events in Financial Risk Management," Center for Financial Institutions Working Papers 98-16, Wharton School Center for Financial Institutions, University of Pennsylvania.

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    1. Antonio Rubia & Trino-Manuel Ñíguez, 2006. "Forecasting the conditional covariance matrix of a portfolio under long-run temporal dependence," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(6), pages 439-458.
    2. Luca Erzegovesi, 2002. "VaR and Liquidity Risk.Impact on Market Behaviour and Measurement Issues," Alea Tech Reports 014, Department of Computer and Management Sciences, University of Trento, Italy, revised 14 Jun 2008.
    3. Andreas Lehnert & Wayne Passmore, 1999. "Pricing systemic crises: monetary and fiscal policy when savers are uncertain," Finance and Economics Discussion Series 1999-33, Board of Governors of the Federal Reserve System (U.S.).
    4. Gonzalez-Rivera, Gloria & Lee, Tae-Hwy & Mishra, Santosh, 2004. "Forecasting volatility: A reality check based on option pricing, utility function, value-at-risk, and predictive likelihood," International Journal of Forecasting, Elsevier, vol. 20(4), pages 629-645.
    5. Li, Xingyi & Zakamulin, Valeriy, 2020. "The term structure of volatility predictability," International Journal of Forecasting, Elsevier, vol. 36(2), pages 723-737.
    6. Zoia, Maria Grazia & Biffi, Paola & Nicolussi, Federica, 2018. "Value at risk and expected shortfall based on Gram-Charlier-like expansions," Journal of Banking & Finance, Elsevier, vol. 93(C), pages 92-104.
    7. Christoffersen, Peter & Errunza, Vihang, 2000. "Towards a global financial architecture: capital mobility and risk management issues," Emerging Markets Review, Elsevier, vol. 1(1), pages 3-20, May.
    8. Guidolin, Massimo & Timmermann, Allan, 2006. "Term structure of risk under alternative econometric specifications," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 285-308.
    9. Wang, Jying-Nan & Du, Jiangze & Hsu, Yuan-Teng, 2018. "Measuring long-term tail risk: Evaluating the performance of the square-root-of-time rule," Journal of Empirical Finance, Elsevier, vol. 47(C), pages 120-138.
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    11. Wang, Cheng & Bouri, Elie & Xu, Yahua & Zhang, Dingsheng, 2023. "Intraday and overnight tail risks and return predictability in the crude oil market: Evidence from oil-related regular news and extreme shocks," Energy Economics, Elsevier, vol. 127(PB).
    12. Aboura, Sofiane & Chevallier, Julien, 2018. "Tail risk and the return-volatility relation," Research in International Business and Finance, Elsevier, vol. 46(C), pages 16-29.
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    25. Cyril Caillault & Dominique Guegan, 2009. "Forecasting VaR and Expected Shortfall using Dynamical Systems: A Risk Management Strategy," PSE-Ecole d'économie de Paris (Postprint) halshs-00375765, HAL.
    26. Flavio Bazzana, 2001. "I modelli interni per la valutazione del rischio di mercato secondo l'approccio del Value at Risk," Alea Tech Reports 011, Department of Computer and Management Sciences, University of Trento, Italy, revised 14 Jun 2008.
    27. Ho, Lan-Chih & Burridge, Peter & Cadle, John & Theobald, Michael, 2000. "Value-at-risk: Applying the extreme value approach to Asian markets in the recent financial turmoil," Pacific-Basin Finance Journal, Elsevier, vol. 8(2), pages 249-275, May.

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    3. Cotter, John, 2004. "Varying the VaR for Unconditional and Conditional Environments," MPRA Paper 3483, University Library of Munich, Germany.
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    6. Odening, Martin & Hinrichs, Jan, 2003. "Die Quantifizierung von Marktrisiken in der Tierproduktion mittels Value-at-Risk und Extreme-Value-Theory," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 52(02), pages 1-11.
    7. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
    8. Turan G. Bali, 2007. "A Generalized Extreme Value Approach to Financial Risk Measurement," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(7), pages 1613-1649, October.
    9. Tang, Ta-Lun & Shieh, Shwu-Jane, 2006. "Long memory in stock index futures markets: A value-at-risk approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 366(C), pages 437-448.
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    1. Carey, Mark & Stulz, Rene M., 2005. "The Risks of Financial Institutions," Working Paper Series 2005-13, Ohio State University, Charles A. Dice Center for Research in Financial Economics.
    2. Luca Erzegovesi, 2002. "VaR and Liquidity Risk.Impact on Market Behaviour and Measurement Issues," Alea Tech Reports 014, Department of Computer and Management Sciences, University of Trento, Italy, revised 14 Jun 2008.
    3. Hisata, Yoshifumi & Yamai, Yasuhiro, 2000. "Research toward the Practical Application of Liquidity Risk Evaluation Methods," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 18(2), pages 83-127, December.
    4. Ernst, Cornelia & Stange, Sebastian & Kaserer, Christoph, 2012. "Measuring market liquidity risk - which model works best?," Journal of Financial Transformation, Capco Institute, vol. 35, pages 133-146.
    5. Panetta, I. C. & Porretta, P., 2009. "Il rischio di liquidità: regolamentazione e best practice [Liquidity Risk: Supervisory Models and Best Practices]," MPRA Paper 36358, University Library of Munich, Germany.
    6. Alexander, Carol & Sheedy, Elizabeth, 2008. "Developing a stress testing framework based on market risk models," Journal of Banking & Finance, Elsevier, vol. 32(10), pages 2220-2236, October.
    7. Didier Cossin & Zhijiang Huang & Daniel Aunon-Nerin & Fer nando González, 2002. "A Framework for Collateral Risk Control Determination," FAME Research Paper Series rp61, International Center for Financial Asset Management and Engineering.
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    10. GIOT, Pierre & GRAMMIG, Joachim, 2006. "How large is liquidity risk in an automated auction market?," LIDAM Reprints CORE 1846, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    11. Timotheos Angelidis & Alexandros Benos, 2009. "The Components of the Bid‐Ask Spread: the Case of the Athens Stock Exchange," European Financial Management, European Financial Management Association, vol. 15(1), pages 112-144, January.
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    13. Stange, Sebastian & Kaserer, Christoph, 2008. "Why and how to integrate liquidity risk into a VaR-framework," CEFS Working Paper Series 2008-10, Technische Universität München (TUM), Center for Entrepreneurial and Financial Studies (CEFS).
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    7. Li, Y. & Donkers, A.C.D. & Melenberg, B., 2006. "The Non- and Semiparametric Analysis of MS Models : Some Applications," Other publications TiSEM c14adc9f-f490-40d6-81b7-8, Tilburg University, School of Economics and Management.
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    1. Christian Hutter & Enzo Weber, 2015. "Constructing a new leading indicator for unemployment from a survey among German employment agencies," Applied Economics, Taylor & Francis Journals, vol. 47(33), pages 3540-3558, July.
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    3. Barakchian , Seyed Mahdi, 2012. "Implications of Cointegration for Forecasting: A Review and an Empirical Analysis," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 7(1), pages 87-118, October.
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    5. Inske Pirschel & Maik H. Wolters, 2018. "Forecasting with large datasets: compressing information before, during or after the estimation?," Empirical Economics, Springer, vol. 55(2), pages 573-596, September.
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    47. McCrae, Michael, et al, 2002. "Can Cointegration-Based Forecasting Outperform Univariate Models? An Application to Asian Exchange Rates," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 21(5), pages 355-380, August.
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    50. Wang, Zijun & Bessler, David A., 2004. "Forecasting performance of multivariate time series models with full and reduced rank: an empirical examination," International Journal of Forecasting, Elsevier, vol. 20(4), pages 683-695.
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    52. Kelly Burns, 2016. "A Reconsideration of the Meese-Rogoff Puzzle: An Alternative Approach to Model Estimation and Forecast Evaluation," Multinational Finance Journal, Multinational Finance Journal, vol. 20(1), pages 41-83, March.
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    55. Carlos Carvalho & Jared D. Fisher & Davide Pettenuzzo, 2018. "Optimal Asset Allocation with Multivariate Bayesian Dynamic Linear Models," Working Papers 123, Brandeis University, Department of Economics and International Business School.
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    66. T.J. Brailsford & J. H.W. Penm & R.D. Terrell, 2006. "The Equivalence of Causality Detection in VAR and VECM Modeling with Applications to Exchange Rates," Multinational Finance Journal, Multinational Finance Journal, vol. 10(3-4), pages 153-178, September.
    67. Madden, Gary & Savage, Scott J. & Coble-Neal, Grant, 2002. "Forecasting United States-Asia international message telephone service," International Journal of Forecasting, Elsevier, vol. 18(4), pages 523-543.
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    70. Ernst Baltensperger & Thomas Jordan & Marcel Savioz, 2001. "The demand for M3 and inflation forecasts: An empirical analysis for Switzerland," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 137(2), pages 244-272, June.
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    1. von der Gracht, Heiko A. & Hommel, Ulrich & Prokesch, Tobias & Wohlenberg, Holger, 2016. "Testing weighting approaches for forecasting in a Group Wisdom Support System environment," Journal of Business Research, Elsevier, vol. 69(10), pages 4081-4094.
    2. Norman R. Swanson & Nii Ayi Armah, 2011. "Predictive Inference Under Model Misspecification with an Application to Assessing the Marginal Predictive Content of Money for Output," Departmental Working Papers 201103, Rutgers University, Department of Economics.
    3. Clements, Michael P., 2008. "Explanations of the inconsistencies in survey respondents'forecasts," The Warwick Economics Research Paper Series (TWERPS) 870, University of Warwick, Department of Economics.
    4. Campbell, Sean D. & Diebold, Francis X., 2004. "Weather forecasting for weather derivatives," CFS Working Paper Series 2004/10, Center for Financial Studies (CFS).
    5. Alquier Pierre & Li Xiaoyin & Wintenberger Olivier, 2013. "Prediction of time series by statistical learning: general losses and fast rates," Dependence Modeling, De Gruyter, vol. 1(2013), pages 65-93, January.
    6. Richhild Moessner & Feng Zhu & Colin Ellis, 2011. "Measuring disagreement in UK consumer and central bank inflation forecasts," BIS Working Papers 339, Bank for International Settlements.
    7. Tsyplakov, Alexander, 2010. "The links between inflation and inflation uncertainty at the longer horizon," MPRA Paper 26908, University Library of Munich, Germany.
    8. Bharat Barot, 2004. "How accurate are the Swedish forecasters on GDB-Growth, CPI-inflation and unemployment? (1993 - 2001)," Brussels Economic Review, ULB -- Universite Libre de Bruxelles, vol. 47(2), pages 249-278.
    9. Francis X. Diebold & Jinyong Hahn & Anthony S. Tay, 1998. "Real-Time Multivariate Density Forecast Evaluation and Calibration: Monitoring the Risk of High-Frequency Returns on Foreign Exchange," New York University, Leonard N. Stern School Finance Department Working Paper Seires 98-079, New York University, Leonard N. Stern School of Business-.
    10. Refet S. Gürkaynak & Justin Wolfers, 2005. "Macroeconomic derivatives: an initial analysis of market-based macro forecasts, uncertainty, and risk," Working Paper Series 2005-26, Federal Reserve Bank of San Francisco.
    11. Cees Diks & Valentyn Panchenko & Dick van Dijk, 2008. "Partial Likelihood-Based Scoring Rules for Evaluating Density Forecasts in Tails," Discussion Papers 2008-10, School of Economics, The University of New South Wales.
    12. Shamiri, Ahmed & Shaari, Abu Hassan & Isa, Zaidi, 2007. "Practical Volatility Modeling for Financial Market Risk Management," MPRA Paper 9790, University Library of Munich, Germany, revised 15 May 2008.
    13. Michael P. Clements, 2014. "US Inflation Expectations and Heterogeneous Loss Functions, 1968–2010," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(1), pages 1-14, January.
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    15. Christian Grimme & Steffen Henzel & Elisabeth Wieland, 2014. "Inflation uncertainty revisited: a proposal for robust measurement," Empirical Economics, Springer, vol. 47(4), pages 1497-1523, December.
    16. Lahiri, Kajal & Liu, Fushang, 2005. "ARCH models for multi-period forecast uncertainty-a reality check using a panel of density forecasts," MPRA Paper 21693, University Library of Munich, Germany.
    17. Gabriela de Raaij & Burkhard Raunig, 2002. "Evaluating Density Forecasts with an Application to Stock Market Returns," Working Papers 59, Oesterreichische Nationalbank (Austrian Central Bank).
    18. Arrieta-Prieto, Mario & Schell, Kristen R., 2022. "Spatio-temporal probabilistic forecasting of wind power for multiple farms: A copula-based hybrid model," International Journal of Forecasting, Elsevier, vol. 38(1), pages 300-320.
    19. Casey, Eddie, 2021. "Are professional forecasters overconfident?," International Journal of Forecasting, Elsevier, vol. 37(2), pages 716-732.
    20. Valentina Corradi & Norman R. Swanson, 2003. "Bootstrap Conditional Distribution Tests In the Presence of Dynamic Misspecification," Departmental Working Papers 200311, Rutgers University, Department of Economics.
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    22. Warne, Anders & Coenen, Günter & Christoffel, Kai, 2010. "Forecasting with DSGE models," Working Paper Series 1185, European Central Bank.
    23. Shamiri, Ahmed & Shaari, Abu Hassan & Isa, Zaidi, 2008. "Comparing the accuracy of density forecasts from competing GARCH models," MPRA Paper 13662, University Library of Munich, Germany.
    24. Barot, Bharat, 2007. "Empirical Studies in Consumption, House Prices and the Accuracy of European Growth and Inflation Forecasts," Working Papers 98, National Institute of Economic Research.
    25. Clements, Michael P, 2006. "Internal consistency of survey respondents.forecasts : Evidence based on the Survey of Professional Forecasters," The Warwick Economics Research Paper Series (TWERPS) 772, University of Warwick, Department of Economics.
    26. Kreye, M.E. & Goh, Y.M. & Newnes, L.B. & Goodwin, P., 2012. "Approaches to displaying information to assist decisions under uncertainty," Omega, Elsevier, vol. 40(6), pages 682-692.
    27. Norman R. Swanson & Lili Cai, 2011. "In- and Out-of-Sample Specification Analysis of Spot Rate Models: Further Evidence for the Period 1982-2008," Departmental Working Papers 201102, Rutgers University, Department of Economics.
    28. G. Boero & J. Smith & KF. Wallis, 2002. "The properties of some goodness-of-fit tests," Working Paper CRENoS 200209, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    29. Michal Franta & Jozef Barunik & Roman Horvath & Katerina Smidkova, 2011. "Are Bayesian Fan Charts Useful for Central Banks? Uncertainty, Forecasting, and Financial Stability Stress Tests," Working Papers 2011/10, Czech National Bank.
    30. Robert R. Bliss & Nikolaos Panigirtzoglou, 2001. "Recovering risk aversion from options," Working Paper Series WP-01-15, Federal Reserve Bank of Chicago.
    31. Diep Duong & Norman Swanson, 2013. "Density and Conditional Distribution Based Specification Analysis," Departmental Working Papers 201312, Rutgers University, Department of Economics.
    32. Patrick T. Brandt & John R. Freeman & Philip A. Schrodt, 2011. "Real Time, Time Series Forecasting of Inter- and Intra-State Political Conflict," Conflict Management and Peace Science, Peace Science Society (International), vol. 28(1), pages 41-64, February.
    33. Wang, Yudong & Zhang, Bing & Diao, Xundi & Wu, Chongfeng, 2015. "Commodity price changes and the predictability of economic policy uncertainty," Economics Letters, Elsevier, vol. 127(C), pages 39-42.
    34. Dean Croushore, 2010. "Philadelphia Fed forecasting surveys: their value for research," Business Review, Federal Reserve Bank of Philadelphia, issue Q3, pages 1-11.
    35. G. Ascari & E. Marrocu, 2003. "Forecasting inflation: a comparison of linear Phillips curve models and nonlinear time serie models," Working Paper CRENoS 200307, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    36. Mestre, Ricardo, 2007. "Are survey-based inflation expections in the euro area informative?," Working Paper Series 721, European Central Bank.
    37. Clements, Michael P., 2008. "Rounding of probability forecasts: The SPF forecast probabilities of negative output growth," Economic Research Papers 269880, University of Warwick - Department of Economics.
    38. Valentina Corradi & Norman R. Swanson, 2003. "A Test for Comparing Multiple Misspecified Conditional Distributions," Departmental Working Papers 200314, Rutgers University, Department of Economics.
    39. Amisano, Gianni & Giacomini, Raffaella, 2007. "Comparing Density Forecasts via Weighted Likelihood Ratio Tests," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 177-190, April.
    40. Öller, Lars-Erik & Barot, Bharat, 2000. "The Accuracy of European Growth and Inflation Forecasts," Working Papers 72, National Institute of Economic Research.

  93. Francis X. Diebold & Todd A. Gunther & Anthony S. Tay, 1997. "Evaluating density forecasts," Working Papers 97-6, Federal Reserve Bank of Philadelphia.

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    1. von der Gracht, Heiko A. & Hommel, Ulrich & Prokesch, Tobias & Wohlenberg, Holger, 2016. "Testing weighting approaches for forecasting in a Group Wisdom Support System environment," Journal of Business Research, Elsevier, vol. 69(10), pages 4081-4094.
    2. Luc Bauwens & Pierre Giot & Joachim Grammig & David Veredas, 2000. "A Comparison of Financial Duration Models via Density Forecasts," Econometric Society World Congress 2000 Contributed Papers 0810, Econometric Society.
    3. Taillardat, Maxime & Fougères, Anne-Laure & Naveau, Philippe & de Fondeville, Raphaël, 2023. "Evaluating probabilistic forecasts of extremes using continuous ranked probability score distributions," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1448-1459.
    4. Clive G. Bowsher, 2005. "Modelling Security Market Events in Continuous Time: Intensity Based, Multivariate Point Process Models," Economics Papers 2005-W26, Economics Group, Nuffield College, University of Oxford.
    5. Campbell, Sean D. & Diebold, Francis X., 2004. "Weather forecasting for weather derivatives," CFS Working Paper Series 2004/10, Center for Financial Studies (CFS).
    6. Jeremy Berkowitz, 1999. "Evaluating the forecasts of risk models," Finance and Economics Discussion Series 1999-11, Board of Governors of the Federal Reserve System (U.S.).
    7. Alquier Pierre & Li Xiaoyin & Wintenberger Olivier, 2013. "Prediction of time series by statistical learning: general losses and fast rates," Dependence Modeling, De Gruyter, vol. 1(2013), pages 65-93, January.
    8. Pesaran, M. Hashem & Zaffaroni, Paolo, 2005. "Model Averaging and Value-at-Risk Based Evaluation of Large Multi-Asset Volatility Models for Risk Management," CEPR Discussion Papers 5279, C.E.P.R. Discussion Papers.
    9. Li, Rui & Reich, Brian J. & Bondell, Howard D., 2021. "Deep distribution regression," Computational Statistics & Data Analysis, Elsevier, vol. 159(C).
    10. Allayioti, Anastasia & Venditti, Fabrizio, 2024. "The role of comovement and time-varying dynamics in forecasting commodity prices," Working Paper Series 2901, European Central Bank.
    11. M. Hashem Pesaran, 2000. "Forecast Uncertainties in Macroeconometric Modelling: An Application to the UK Economy," CESifo Working Paper Series 345, CESifo.
    12. Bharat Barot, 2004. "How accurate are the Swedish forecasters on GDB-Growth, CPI-inflation and unemployment? (1993 - 2001)," Brussels Economic Review, ULB -- Universite Libre de Bruxelles, vol. 47(2), pages 249-278.
    13. Tara Sinclair & Herman O. Stekler & Warren Carnow, 2012. "A New Approach For Evaluating Economic Forecasts," Working Papers 2012-2, The George Washington University, Institute for International Economic Policy.
    14. Keller, Joachim & Glatzer, Ernst & Craig, Ben R. & Scheicher, Martin, 2003. "The Forecasting Performance of German Stock Option Densities," Discussion Paper Series 1: Economic Studies 2003,17, Deutsche Bundesbank.
    15. Francis X. Diebold & Jinyong Hahn & Anthony S. Tay, 1998. "Real-Time Multivariate Density Forecast Evaluation and Calibration: Monitoring the Risk of High-Frequency Returns on Foreign Exchange," New York University, Leonard N. Stern School Finance Department Working Paper Seires 98-079, New York University, Leonard N. Stern School of Business-.
    16. Vahidin Jeleskovic & Mirko Meloni & Zahid Irshad Younas, 2020. "Cryptocurrencies: A Copula Based Approach for Asymmetric Risk Marginal Allocations," MAGKS Papers on Economics 202034, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    17. Jones, David & Mingo, John, 1999. "Credit risk modeling and internal capital allocation processes: implications for a models-based regulatory bank capital standard," Journal of Economics and Business, Elsevier, vol. 51(2), pages 79-108, March.
    18. Sancetta, A. & Nikanrova, A., 2005. "Forecasting and Prequential Validation for Time Varying Meta-Elliptical Distributions with a Study of Commodity Futures Prices," Cambridge Working Papers in Economics 0516, Faculty of Economics, University of Cambridge.
    19. Burkhard Raunig, 2003. "Testing for Longer Horizon Predictability of Return Volatility with an Application to the German," Working Papers 86, Oesterreichische Nationalbank (Austrian Central Bank).
    20. Leopoldo Catania & Alessandra Luati & Pierluigi Vallarino, 2021. "Economic vulnerability is state dependent," CREATES Research Papers 2021-09, Department of Economics and Business Economics, Aarhus University.
    21. Valentina Corradi & Norman Swanson, 2004. "Predective Density and Conditional Confidence Interval Accuracy Tests," Departmental Working Papers 200423, Rutgers University, Department of Economics.
    22. Heinen, Andreas, 2003. "Modelling Time Series Count Data: An Autoregressive Conditional Poisson Model," MPRA Paper 8113, University Library of Munich, Germany.
    23. Stefania D'Amico, 2004. "Density Estimation and Combination under Model Ambiguity," Computing in Economics and Finance 2004 273, Society for Computational Economics.
    24. Matthew Pritsker, 2001. "The hidden dangers of historical simulation," Finance and Economics Discussion Series 2001-27, Board of Governors of the Federal Reserve System (U.S.).
    25. Guidolin, Massimo & Timmermann, Allan, 2007. "Asset allocation under multivariate regime switching," Journal of Economic Dynamics and Control, Elsevier, vol. 31(11), pages 3503-3544, November.
    26. Peter Christoffersen & Denis Pelletier, 2003. "Backtesting Value-at-Risk: A Duration-Based Approach," CIRANO Working Papers 2003s-05, CIRANO.
    27. Gourieroux, Christian & Jasiak, Joanna, 1999. "Nonlinear innovations and impulse responses," CEPREMAP Working Papers (Couverture Orange) 9906, CEPREMAP.
    28. Gabriela de Raaij & Burkhard Raunig, 2002. "Evaluating Density Forecasts with an Application to Stock Market Returns," Working Papers 59, Oesterreichische Nationalbank (Austrian Central Bank).
    29. Arrieta-Prieto, Mario & Schell, Kristen R., 2022. "Spatio-temporal probabilistic forecasting of wind power for multiple farms: A copula-based hybrid model," International Journal of Forecasting, Elsevier, vol. 38(1), pages 300-320.
    30. Guidolin, Massimo & Timmermann, Allan, 2006. "Term structure of risk under alternative econometric specifications," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 285-308.
    31. Tomás Marinozzi, 2023. "Forecasting Inflation in Argentina: A Probabilistic Approach," Ensayos Económicos, Central Bank of Argentina, Economic Research Department, vol. 1(81), pages 81-110, May.
    32. Heather M. Anderson & Chin Nam Low, 2006. "Random Walk Smooth Transition Autoregressive Models," Contributions to Economic Analysis, in: Nonlinear Time Series Analysis of Business Cycles, pages 247-281, Emerald Group Publishing Limited.
    33. Li, Fuchun, 2007. "Testing The Parametric Specification Of The Diffusion Function In A Diffusion Process," Econometric Theory, Cambridge University Press, vol. 23(2), pages 221-250, April.
    34. Valentina Corradi & Norman R. Swanson, 2003. "Bootstrap Conditional Distribution Tests In the Presence of Dynamic Misspecification," Departmental Working Papers 200311, Rutgers University, Department of Economics.
    35. Jose A. Lopez, 1999. "Methods for evaluating value-at-risk estimates," Economic Review, Federal Reserve Bank of San Francisco, pages 3-17.
    36. Michael F. Bryan & Brent Meyer & Nicholas B. Parker, 2014. "The inflation expectations of firms: what do they look like, are they accurate, and do they matter?," FRB Atlanta Working Paper 2014-27, Federal Reserve Bank of Atlanta.
    37. Barot, Bharat, 2007. "Empirical Studies in Consumption, House Prices and the Accuracy of European Growth and Inflation Forecasts," Working Papers 98, National Institute of Economic Research.
    38. Bayoumi, Tamim & Sgherri, Silvia, 2004. "Deconstructing the Art of Central Banking," CEPR Discussion Papers 4675, C.E.P.R. Discussion Papers.
    39. Clements, Michael P, 2006. "Internal consistency of survey respondents.forecasts : Evidence based on the Survey of Professional Forecasters," The Warwick Economics Research Paper Series (TWERPS) 772, University of Warwick, Department of Economics.
    40. Kreye, M.E. & Goh, Y.M. & Newnes, L.B. & Goodwin, P., 2012. "Approaches to displaying information to assist decisions under uncertainty," Omega, Elsevier, vol. 40(6), pages 682-692.
    41. Manner, H., 2007. "Estimation and model selection of copulas with an application to exchange rates," Research Memorandum 056, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    42. Lopez, Jose A. & Saidenberg, Marc R., 2000. "Evaluating credit risk models," Journal of Banking & Finance, Elsevier, vol. 24(1-2), pages 151-165, January.
    43. G. Boero & J. Smith & KF. Wallis, 2002. "The properties of some goodness-of-fit tests," Working Paper CRENoS 200209, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    44. Jean-Paul Laurent & Hassan Omidi Firouzi, 2022. "Market Risk and Volatility Weighted Historical Simulation After Basel III," Working Papers hal-03679434, HAL.
    45. Fuchun Li & Greg Tkacz, 2001. "A Consistent Bootstrap Test for Conditional Density Functions with Time-Dependent Data," Staff Working Papers 01-21, Bank of Canada.
    46. Casciaro, Gabriele & Ferrari, Francesco & Lagomarsino-Oneto, Daniele & Lira-Loarca, Andrea & Mazzino, Andrea, 2022. "Increasing the skill of short-term wind speed ensemble forecasts combining forecasts and observations via a new dynamic calibration," Energy, Elsevier, vol. 251(C).
    47. Gabriela De Raaij & Burkhard Raunig, 2005. "Evaluating density forecasts from models of stock market returns," The European Journal of Finance, Taylor & Francis Journals, vol. 11(2), pages 151-166.
    48. Jose A. Lopez, 1997. "Regulatory evaluation of value-at-risk models," Staff Reports 33, Federal Reserve Bank of New York.
    49. Jeremy Berkowitz & James M. O'Brien, 2001. "How accurate are Value-at-Risk models at commercial banks?," Finance and Economics Discussion Series 2001-31, Board of Governors of the Federal Reserve System (U.S.).
    50. Marc Saidenberg & Til Schuermann & May, "undated". "The New Basel Capital Accord and Questions for Research," Center for Financial Institutions Working Papers 03-14, Wharton School Center for Financial Institutions, University of Pennsylvania.
    51. Valentina Corradi & Norman Swanson, 2003. "The Block Bootstrap for Parameter Estimation Error In Recursive Estimation Schemes, With Applications to Predictive Evaluation," Departmental Working Papers 200313, Rutgers University, Department of Economics.
    52. Daniel F. Waggoner & Tao Zha, 1998. "Conditional forecasts in dynamic multivariate models," FRB Atlanta Working Paper 98-22, Federal Reserve Bank of Atlanta.
    53. Massimo Guidolin & Carrie Fangzhou Na, 2007. "The economic and statistical value of forecast combinations under regime switching: an application to predictable U.S. returns," Working Papers 2006-059, Federal Reserve Bank of St. Louis.
    54. Wang, Yudong & Zhang, Bing & Diao, Xundi & Wu, Chongfeng, 2015. "Commodity price changes and the predictability of economic policy uncertainty," Economics Letters, Elsevier, vol. 127(C), pages 39-42.
    55. Silvano Bordignon & Francesco Lisi, 2001. "Interval prediction for chaotic time series," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3-4), pages 117-140.
    56. Vahidin Jeleskovic & Claudio Latini & Zahid I. Younas & Mamdouh A. S. Al-Faryan, 2023. "Optimization of portfolios with cryptocurrencies: Markowitz and GARCH-Copula model approach," Papers 2401.00507, arXiv.org.
    57. Giovanni De Luca & Paola Zuccolotto, 2003. "Finite and infinite mixtures for financial durations," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3), pages 431-455.
    58. Ioannis Anagnostou & Drona Kandhai, 2019. "Risk Factor Evolution for Counterparty Credit Risk under a Hidden Markov Model," Risks, MDPI, vol. 7(2), pages 1-22, June.
    59. Massimo Guidolin & Allan Timmerman, 2005. "Optimal portfolio choice under regime switching, skew and kurtosis preferences," Working Papers 2005-006, Federal Reserve Bank of St. Louis.
    60. Mestre, Ricardo, 2007. "Are survey-based inflation expections in the euro area informative?," Working Paper Series 721, European Central Bank.
    61. Valentina Corradi & Norman R. Swanson, 2003. "A Test for Comparing Multiple Misspecified Conditional Distributions," Departmental Working Papers 200314, Rutgers University, Department of Economics.
    62. Chib, Siddhartha & Nardari, Federico & Shephard, Neil, 2002. "Markov chain Monte Carlo methods for stochastic volatility models," Journal of Econometrics, Elsevier, vol. 108(2), pages 281-316, June.
    63. Enrique Sentana & Giorgio Calzolari & Gabriele Fiorentini, 2004. "Indirect Estimation of Conditionally Heteroskedastic Factor Models," Working Papers wp2004_0409, CEMFI.
    64. Amisano, Gianni & Giacomini, Raffaella, 2007. "Comparing Density Forecasts via Weighted Likelihood Ratio Tests," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 177-190, April.
    65. Öller, Lars-Erik & Barot, Bharat, 2000. "The Accuracy of European Growth and Inflation Forecasts," Working Papers 72, National Institute of Economic Research.
    66. Alfonso Dufour & Robert F Engle, 2000. "The ACD Model: Predictability of the Time Between Concecutive Trades," ICMA Centre Discussion Papers in Finance icma-dp2000-05, Henley Business School, University of Reading.
    67. Stefania D'Amico, 2005. "Density selection and combination under model ambiguity: an application to stock returns," Finance and Economics Discussion Series 2005-09, Board of Governors of the Federal Reserve System (U.S.).

  94. Antulio N. Bomfim & Francis X. Diebold, 1997. "Bounded rationality and strategic complementarity in a macroeconomic model: policy effects, persistence, and multipliers," Working Papers 97-18, Federal Reserve Bank of Philadelphia.

    Cited by:

    1. Francois R. Velde, 2006. "Chronicles of a deflation unforetold," Working Paper Series WP-06-12, Federal Reserve Bank of Chicago.
    2. Anderlini, Luca & Canning, David, 2001. "Structural Stability Implies Robustness to Bounded Rationality," Journal of Economic Theory, Elsevier, vol. 101(2), pages 395-422, December.
    3. Ripamonti, Alexandre, 2013. "Rational Valuation Formula (RVF) and Time Variability in Asset Rates of Return," MPRA Paper 79460, University Library of Munich, Germany.
    4. Seonghwan Oh & Michael Waldman, 2005. "The Index of Leading Economic Indicators as a Source of Expectational Shocks," Eastern Economic Journal, Eastern Economic Association, vol. 31(1), pages 75-95, Winter.
    5. Beqiraj, Elton & Di Bartolomeo, Giovanni & Di Pietro, Marco, 2019. "Beliefs formation and the puzzle of forward guidance power," Journal of Macroeconomics, Elsevier, vol. 60(C), pages 20-32.
    6. Thijssen, J.J.J., 2003. "Investment under uncertainty, market evolution and coalition spillovers in a game theoretic perspective," Other publications TiSEM 672073a6-492e-4621-8d4a-0, Tilburg University, School of Economics and Management.
    7. SOOREEA, Rajeev, 2007. "Are Taylor-Based Monetary Policy Rules Forward-Looking?. An Investigation Using Superexogeneity Tests," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 7(2), pages 87-94.
    8. Tobias Rötheli, 2005. "Applied Welfare Economics with Bounded Rationality: Public Policies Toward Remote Sensing," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 11(1), pages 39-47, February.
    9. Weder, Mark, 2004. "Near-rational expectations in animal spirits models of aggregate fluctuations," Economic Modelling, Elsevier, vol. 21(2), pages 249-265, March.

  95. Francis X. Diebold, 1997. "The past, present, and future of macroeconomic forecasting," Working Papers 97-20, Federal Reserve Bank of Philadelphia.

    Cited by:

    1. Haider, Adnan & Khan, Safdar Ullah, 2008. "A Small Open Economy DSGE Model for Pakistan," MPRA Paper 12977, University Library of Munich, Germany, revised 17 Jan 2009.
    2. Fildes, Robert & Stekler, Herman, 2002. "The state of macroeconomic forecasting," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 435-468, December.
    3. KAMKOUM, Arnaud Cedric, 2023. "The Federal Reserve’s Response to the Global Financial Crisis and its Effects: An Interrupted Time-Series Analysis of the Impact of its Quantitative Easing Programs," Thesis Commons d7pvg, Center for Open Science.
    4. Hendry, David F. & Clements, Michael P., 2003. "Economic forecasting: some lessons from recent research," Economic Modelling, Elsevier, vol. 20(2), pages 301-329, March.
    5. Stekler, H.O., 2007. "The future of macroeconomic forecasting: Understanding the forecasting process," International Journal of Forecasting, Elsevier, vol. 23(2), pages 237-248.
    6. Valadkhani, Abbas, 2004. "History of macroeconometric modelling: lessons from past experience," Journal of Policy Modeling, Elsevier, vol. 26(2), pages 265-281, February.
    7. Barakchian , Seyed Mahdi, 2012. "Implications of Cointegration for Forecasting: A Review and an Empirical Analysis," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 7(1), pages 87-118, October.
    8. Andrea Kunnert, 2013. "Baubewilligungen für Wohneinheiten in Österreich: Prognose 2012/13 und regionale Entwicklung 2006/2011. Teilbericht 2," WIFO Studies, WIFO, number 67110, April.
    9. Michael Klien & Andrea Kunnert, 2018. "Baubewilligungen für neue Wohneinheiten in Österreich. Prognose Sommer 2018 und regionale Entwicklung 2012/2017," WIFO Studies, WIFO, number 62399, April.
    10. Hampel, Katharina & Kunz, Marcus & Schanne, Norbert & Wapler, Rüdiger & Weyh, Antje, 2007. "Regional employment forecasts with spatial interdependencies," IAB-Discussion Paper 200702, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    11. Tursoy, Turgut, 2013. "Structural Modelling for North Cyprus’ Economic Growth," MPRA Paper 98519, University Library of Munich, Germany.
    12. V. Pandit, 2000. "Macroeconometric Policy Modeling for India: A Review of Some Analytical Issues," Working papers 74, Centre for Development Economics, Delhi School of Economics.
    13. Heilemann, Ullrich & Stekler, Herman, 2007. "Introduction to "The future of macroeconomic forecasting"," International Journal of Forecasting, Elsevier, vol. 23(2), pages 159-165.
    14. Michael Klien & Andrea Kunnert, 2017. "Baubewilligungen für neue Wohneinheiten in Österreich. Prognose Herbst 2017," WIFO Studies, WIFO, number 65635, April.
    15. Karamé, Frédéric & Patureau, Lise & Sopraseuth, Thepthida, 2008. "Limited participation and exchange rate dynamics: Does theory meet the data?," Journal of Economic Dynamics and Control, Elsevier, vol. 32(4), pages 1041-1087, April.
    16. Lasha Kavtaradze & Manouchehr Mokhtari, 2018. "Factor Models And Time†Varying Parameter Framework For Forecasting Exchange Rates And Inflation: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 32(2), pages 302-334, April.
    17. Gonzalo Fernandez-de-Córdoba & José L. Torres, 2009. "Forecasting the Spanish economy with an Augmented VAR-DSGE model," Working Papers 2009-1, Universidad de Málaga, Department of Economic Theory, Málaga Economic Theory Research Center.
    18. V. Pandit, 2008. "Structural Modeling under Challenge," Working Papers id:1622, eSocialSciences.
    19. Francis X. Diebold & Glenn D. Rudebusch, 2001. "Five questions about business cycles," Economic Review, Federal Reserve Bank of San Francisco, pages 1-15.
    20. Stefano Siviero & Daniele Terlizzese, 2001. "Macroeconomic forecasting: Debunking a few old wives' tales," Temi di discussione (Economic working papers) 395, Bank of Italy, Economic Research and International Relations Area.
    21. Mihaela Bratu, 2012. "A Strategy to Improve the Survey of Professional Forecasters (SPF) Predictions Using Bias-Corrected-Accelerated (BCA) Bootstrap Forecast Intervals," International Journal of Synergy and Research, ToKnowPress, vol. 1(2), pages 45-59.
    22. D. Tutberidze & D. Japaridze, 2017. "Macroeconomic Forecasting Using Bayesian Vector Autoregressive Approach," Вестник Киевского национального университета имени Тараса Шевченко. Экономика., Socionet;Киевский национальный университет имени Тараса Шевченко, vol. 2(191), pages 42-49.
    23. Andrea Kunnert, 2012. "Prognose der Wohnbaubewilligungen für Wohneinheiten in Österreich 2012 und 2013. Teilbericht 1," WIFO Studies, WIFO, number 67109, April.
    24. Christian Glocker & Serguei Kaniovski, 2022. "Macroeconometric forecasting using a cluster of dynamic factor models," Empirical Economics, Springer, vol. 63(1), pages 43-91, July.
    25. Slanicay Martin, 2014. "Some Notes on Historical, Theoretical, and Empirical Background of DSGE Models," Review of Economic Perspectives, Sciendo, vol. 14(2), pages 1-20, June.
    26. Mihaela Bratu (Simionescu), 2013. "How to Improve the SPF Forecasts?," Acta Universitatis Danubius. OEconomica, Danubius University of Galati, issue 9(2), pages 153-165, April.
    27. Afshin Amiraslany & Hari S. Luitel & Gerry J. Mahar, 2019. "Structural Breaks, Biased Estimations, and Forecast Errors in a GDP Series of Canada versus the United States," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 25(2), pages 235-244, May.
    28. José Luis Torres Chacon, 2015. "Introduction to Dynamic Macroeconomic General Equilibrium Models," Vernon Press Titles in Economics, Vernon Art and Science Inc, edition 2, number 54, July.
    29. Michael Klien & Andrea Kunnert, 2014. "Baubewilligungen für Wohneinheiten in Österreich. Prognose 2014 und 2015," WIFO Studies, WIFO, number 58602, April.
    30. Thomas Cook, 2019. "Macroeconomic Indicator Forecasting with Deep Neural Networks," 2019 Meeting Papers 402, Society for Economic Dynamics.
    31. BRATU SIMIONESCU, Mihaela, 2012. "Two Quantitative Forecasting Methods For Macroeconomic Indicators In Czech Republic," Annals of Spiru Haret University, Economic Series, Universitatea Spiru Haret, vol. 3(1), pages 71-87.
    32. Francis X. Diebold & Lee E. Ohanian & Jeremy Berkowitz, 1995. "Dynamic Equilibrium Economies: A Framework for Comparing Models and Data," NBER Technical Working Papers 0174, National Bureau of Economic Research, Inc.
    33. Skrypnik, Dmitriy, 2016. "A Macroeconomic Model of the Russian Economy," MPRA Paper 93506, University Library of Munich, Germany.
    34. Panagiotelis, Anastasios & Athanasopoulos, George & Hyndman, Rob J. & Jiang, Bin & Vahid, Farshid, 2019. "Macroeconomic forecasting for Australia using a large number of predictors," International Journal of Forecasting, Elsevier, vol. 35(2), pages 616-633.
    35. Banik, Nilanjan & Biswas, Basudeb, 2012. "The curious case of Indian agriculture," MPRA Paper 38634, University Library of Munich, Germany.
    36. Willem J.H. van Groenendaal, 2011. "Energy Model and Policy Advice: The Effect of Model Choice," Chapters, in: Raymond J.G.M. Florax & Henri L.F. de Groot & Peter Mulder (ed.), Improving Energy Efficiency through Technology, chapter 11, Edward Elgar Publishing.
    37. Nicholson, William B. & Matteson, David S. & Bien, Jacob, 2017. "VARX-L: Structured regularization for large vector autoregressions with exogenous variables," International Journal of Forecasting, Elsevier, vol. 33(3), pages 627-651.
    38. Olkhov, Victor, 2016. "On Economic Space notion," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 372-381.
    39. Michael Klien & Andrea Kunnert, 2016. "Baubewilligungen für neue Wohneinheiten in Österreich. Prognose Herbst 2016," WIFO Studies, WIFO, number 65638, April.
    40. Frédéric Karamé & Lise Patureau & Thepthida Sopraseuth, 2002. "Can We Beat the Random Walk Forecasts of Out-of-Sample Exchange Rates? A Structural Approach," Computing in Economics and Finance 2002 233, Society for Computational Economics.
    41. Javier Andrés & Fernando Restoy, 2007. "Macroeconomic modelling in EMU: how relevant is the change in regime?," Working Papers 0718, Banco de España.
    42. Warne, Anders & Coenen, Günter & Christoffel, Kai, 2010. "Forecasting with DSGE models," Working Paper Series 1185, European Central Bank.
    43. Julio J. Rotemberg, 1999. "A Heuristic Method for Extracting Smooth Trends from Economic Time Series," NBER Working Papers 7439, National Bureau of Economic Research, Inc.
    44. V. Pandit, 2001. "Structural Modelling Under Challenge," Working papers 98, Centre for Development Economics, Delhi School of Economics.
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    82. Aaron Smith, 2005. "Forecasting in the presence of level shifts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(8), pages 557-574.
    83. Travis J. Berge, 2011. "Forecasting disconnected exchange rates," Research Working Paper RWP 11-12, Federal Reserve Bank of Kansas City.
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    85. Lessmann, Stefan & Coussement, Kristof & De Bock, Koen W. & Haupt, Johannes, 2018. "Targeting customers for profit: An ensemble learning framework to support marketing decision making," IRTG 1792 Discussion Papers 2018-012, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    86. Allan Timmermann & Andrew J. Patton, 2004. "Properties of Optimal Forecasts," Econometric Society 2004 North American Winter Meetings 234, Econometric Society.
    87. Matei Demetrescu, 2007. "Optimal forecast intervals under asymmetric loss," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(4), pages 227-238.
    88. Frenkel, Michael & Rülke, Jan-Christoph & Zimmermann, Lilli, 2013. "Do private sector forecasters chase after IMF or OECD forecasts?," Journal of Macroeconomics, Elsevier, vol. 37(C), pages 217-229.
    89. Clements, Michael P, 2006. "Internal consistency of survey respondents.forecasts : Evidence based on the Survey of Professional Forecasters," The Warwick Economics Research Paper Series (TWERPS) 772, University of Warwick, Department of Economics.
    90. Heike Hans-Dieter & Demetrescu Matei, 2006. "Loss Reduction in Point Estimation Problems," Stochastics and Quality Control, De Gruyter, vol. 21(2), pages 209-217, January.
    91. Batchelor, Roy & Peel, David A., 1998. "Rationality testing under asymmetric loss," Economics Letters, Elsevier, vol. 61(1), pages 49-54, October.
    92. Komunjer, Ivana & OWYANG, MICHAEL, 2007. "Multivariate Forecast Evaluation And Rationality Testing," University of California at San Diego, Economics Working Paper Series qt81w8m5sf, Department of Economics, UC San Diego.
    93. Robert Lehmann & Timo Wollmershäuser, 2019. "The Macroeconomic Projections of the German Government: A Comparison to an Independent Forecasting Institution," CESifo Working Paper Series 7460, CESifo.
    94. Fabio Busetti, 2014. "Quantile aggregation of density forecasts," Temi di discussione (Economic working papers) 979, Bank of Italy, Economic Research and International Relations Area.
    95. Capistrán Carlos, 2007. "Optimality Tests for Multi-Horizon Forecasts," Working Papers 2007-14, Banco de México.
    96. Pratiti Chatterjee & Fabio Milani, 2020. "Perceived Uncertainty Shocks, Excess Optimism-Pessimism, and Learning in the Business Cycle," CESifo Working Paper Series 8608, CESifo.
    97. Henri Karttunen, 2020. "An autoregressive model based on the generalized hyperbolic distribution," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 47(3), pages 787-816, September.
    98. Pesaran, M. Hashem & Weale, Martin, 2006. "Survey Expectations," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 14, pages 715-776, Elsevier.
    99. Timo Dimitriadis & Andrew J. Patton & Patrick W. Schmidt, 2019. "Testing Forecast Rationality for Measures of Central Tendency," Papers 1910.12545, arXiv.org, revised Jun 2023.
    100. Raffella Giacomini & Barbara Rossi, 2005. "Detecting and Predicting Forecast Breakdowns," UCLA Economics Working Papers 845, UCLA Department of Economics.
    101. Patton, Andrew J. & Timmermann, Allan, 2007. "Properties of optimal forecasts under asymmetric loss and nonlinearity," Journal of Econometrics, Elsevier, vol. 140(2), pages 884-918, October.
    102. M A Clatworthy & D Peel & P F Pope, 2005. "Are analysts' loss functions asymmetric?," Working Papers 574124, Lancaster University Management School, Economics Department.
    103. Francis X. Diebold & Jose A. Lopez, 1996. "Forecast Evaluation and Combination," NBER Technical Working Papers 0192, National Bureau of Economic Research, Inc.
    104. Nobay, A. R. & Peel, D. A., 2000. "Optimal monetary policy with a nonlinear Phillips curve," Economics Letters, Elsevier, vol. 67(2), pages 159-164, May.
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    106. George Christodoulakis & Konstantinos Stathopoulos & Nikolaos Tessaromatis, 2012. "The term structure of loss preferences and rationality in analyst earnings forecasts," Journal of Asset Management, Palgrave Macmillan, vol. 13(5), pages 310-326, October.
    107. Giacomini, Raffaella, 2002. "Comparing Density Forecasts via Weighted Likelihood Ratio Tests: Asymptotic and Bootstrap Methods," University of California at San Diego, Economics Working Paper Series qt59s2g5j5, Department of Economics, UC San Diego.
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    111. Zvi Schwartz & Timothy Webb & Jean-Pierre I van der Rest & Larissa Koupriouchina, 2021. "Enhancing the accuracy of revenue management system forecasts: The impact of machine and human learning on the effectiveness of hotel occupancy forecast combinations across multiple forecasting horizo," Tourism Economics, , vol. 27(2), pages 273-291, March.
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    118. Goodwin, Thomas & Tian, Jing, 2017. "A state space approach to evaluate multi-horizon forecasts," Working Papers 2017-15, University of Tasmania, Tasmanian School of Business and Economics.
    119. Kostas Mouratidis & Dimitris Kenourgios & Aris Samitas, 2010. "Evaluating currency crisis:A multivariate Markov switching approach," Working Papers 2010018, The University of Sheffield, Department of Economics, revised Oct 2010.
    120. Anthony Tay & Kenneth F. Wallis, 2000. "Density Forecasting: A Survey," Econometric Society World Congress 2000 Contributed Papers 0370, Econometric Society.
    121. Carlos Capistrán & Allan Timmermann, 2009. "Disagreement and Biases in Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(2‐3), pages 365-396, March.
    122. Nobay, A. Robert & Peel, David, 1998. "Optimal monetary policy in a model of asymmetric central bank preferences," LSE Research Online Documents on Economics 119138, London School of Economics and Political Science, LSE Library.
    123. Dress, Korbinian & Lessmann, Stefan & von Mettenheim, Hans-Jörg, 2018. "Residual value forecasting using asymmetric cost functions," International Journal of Forecasting, Elsevier, vol. 34(4), pages 551-565.
    124. Demetrescu, Matei, 2006. "An extension of the Gauss-Newton algorithm for estimation under asymmetric loss," Computational Statistics & Data Analysis, Elsevier, vol. 50(2), pages 379-401, January.
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    126. M A Clatworthy & D Peel & P F Pope, 2006. "Are analysts’ loss functions asymmetric?," Working Papers 574591, Lancaster University Management School, Economics Department.
    127. Brownlees, Christian T. & Gallo, Giampiero M., 2011. "Shrinkage estimation of semiparametric multiplicative error models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 365-378.
    128. Bruzda, Joanna, 2019. "Quantile smoothing in supply chain and logistics forecasting," International Journal of Production Economics, Elsevier, vol. 208(C), pages 122-139.
    129. Tian, Jing & Goodwin, Thomas, 2018. "An unobserved component modeling approach to evaluate multi-horizon forecasts," Working Papers 2018-04, University of Tasmania, Tasmanian School of Business and Economics.
    130. Bürgi, Constantin, 2017. "Bias, rationality and asymmetric loss functions," Economics Letters, Elsevier, vol. 154(C), pages 113-116.
    131. Patton, Andrew J., 2011. "Volatility forecast comparison using imperfect volatility proxies," Journal of Econometrics, Elsevier, vol. 160(1), pages 246-256, January.
    132. Zhu, Ke, 2015. "Hausman tests for the error distribution in conditionally heteroskedastic models," MPRA Paper 66991, University Library of Munich, Germany.
    133. Boyan Jovanovic & Yaw Nyarko, 1995. "A Bayesian Learning Model Fitted to a Variety of Empirical Learning Curves," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 26(1995 Micr), pages 247-305.
    134. MacDonald, Ronald & Nagayasu, Jun, 2015. "Currency forecast errors and carry trades at times of low interest rates: Evidence from survey data on the yen/dollar exchange rate," Journal of International Money and Finance, Elsevier, vol. 53(C), pages 1-19.
    135. Elena Ivona Dumitrescu & Peter Hansen, 2020. "How Should Parameter Estimation Be Tailored to the Objective?," Post-Print hal-03331109, HAL.
    136. Ulu, Yasemin, 2007. "Optimal prediction under LINLIN loss: Empirical evidence," International Journal of Forecasting, Elsevier, vol. 23(4), pages 707-715.
    137. Schorfheide, Frank, 2005. "VAR forecasting under misspecification," Journal of Econometrics, Elsevier, vol. 128(1), pages 99-136, September.
    138. Chen, Bin & Hong, Yongmiao, 2014. "A unified approach to validating univariate and multivariate conditional distribution models in time series," Journal of Econometrics, Elsevier, vol. 178(P1), pages 22-44.
    139. Wang, Jying-Nan & Yeh, Jin-Huei & Cheng, Nick Ying-Pin, 2011. "How accurate is the square-root-of-time rule in scaling tail risk: A global study," Journal of Banking & Finance, Elsevier, vol. 35(5), pages 1158-1169, May.
    140. Patton, Andrew J. & Timmermann, Allan, 2005. "Testable implications of forecast optimality," LSE Research Online Documents on Economics 6834, London School of Economics and Political Science, LSE Library.
    141. George Christodoulakis, 2006. "Generalised Rational Bias in Financial Forecasts," Annals of Finance, Springer, vol. 2(4), pages 397-405, October.
    142. María Clara Aristizábal Restrepo, 2006. "Evaluación asimétrica de una red neuronal artificial:Aplicación al caso de la inflación en Colombia," Borradores de Economia 377, Banco de la Republica de Colombia.
    143. Gonçalves Mazzeu, Joao Henrique & Ruiz Ortega, Esther & Veiga, Helena, 2015. "Model uncertainty and the forecast accuracy of ARMA models: A survey," DES - Working Papers. Statistics and Econometrics. WS ws1508, Universidad Carlos III de Madrid. Departamento de Estadística.
    144. Gneiting, Tilmann, 2011. "Quantiles as optimal point forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 197-207.
    145. Amisano, Gianni & Giacomini, Raffaella, 2007. "Comparing Density Forecasts via Weighted Likelihood Ratio Tests," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 177-190, April.
    146. Wu, Jinran & Wang, You-Gan & Tian, Yu-Chu & Burrage, Kevin & Cao, Taoyun, 2021. "Support vector regression with asymmetric loss for optimal electric load forecasting," Energy, Elsevier, vol. 223(C).
    147. Ines Fortin & Jaroslava Hlouskova, 2015. "Downside loss aversion: Winner or loser?," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 81(2), pages 181-233, April.
    148. Andrea Cipollini & Bassam Fattouh & Kostas Mouratidis, 2009. "Fiscal Readjustments In The United States: A Nonlinear Time‐Series Analysis," Economic Inquiry, Western Economic Association International, vol. 47(1), pages 34-54, January.
    149. Ulu, Yasemin, 2013. "Multivariate test for forecast rationality under asymmetric loss functions: Recent evidence from MMS survey of inflation–output forecasts," Economics Letters, Elsevier, vol. 119(2), pages 168-171.
    150. Anatolyev, Stanislav, 2006. "Kernel estimation under linear-exponential loss," Economics Letters, Elsevier, vol. 91(1), pages 39-43, April.
    151. Manfred Deistler & Klaus Neusser, 2004. "Prognose uni- und multivariater Zeitreihen," Diskussionsschriften dp0401, Universitaet Bern, Departement Volkswirtschaft.
    152. Robert Jarrow & Feng Zhao, 2006. "Downside Loss Aversion and Portfolio Management," Management Science, INFORMS, vol. 52(4), pages 558-566, April.
    153. Bollerslev, Tim & Zhang, Benjamin Y. B., 2003. "Measuring and modeling systematic risk in factor pricing models using high-frequency data," Journal of Empirical Finance, Elsevier, vol. 10(5), pages 533-558, December.
    154. Alexander, Marcus & Christakis, Nicholas A., 2008. "Bias and asymmetric loss in expert forecasts: A study of physician prognostic behavior with respect to patient survival," Journal of Health Economics, Elsevier, vol. 27(4), pages 1095-1108, July.

  97. Francis X. Diebold & Andrew Hickman & Atsushi Inoue & Til Schuermann, 1997. "Converting 1-Day Volatility to h-Day Volatitlity: Scaling by Root-h is Worse Than You Think," Center for Financial Institutions Working Papers 97-34, Wharton School Center for Financial Institutions, University of Pennsylvania.

    Cited by:

    1. Odening, Martin & Hinrichs, Jan, 2003. "Die Quantifizierung von Marktrisiken in der Tierproduktion mittels Value-at-Risk und Extreme-Value-Theory," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 52(02), pages 1-11.
    2. Wolff, Christian & Lehnert, Thorsten, 2001. "Modelling Scale-Consistent VaR with the Truncated Lévy Flight," CEPR Discussion Papers 2711, C.E.P.R. Discussion Papers.
    3. Del Brio, Esther B. & Mora-Valencia, Andrés & Perote, Javier, 2014. "VaR performance during the subprime and sovereign debt crises: An application to emerging markets," Emerging Markets Review, Elsevier, vol. 20(C), pages 23-41.
    4. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005. "Practical Volatility and Correlation Modeling for Financial Market Risk Management," PIER Working Paper Archive 05-007, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    5. Erik Kole & Thijs Markwat & Anne Opschoor & Dick van Dijk, 2017. "Forecasting Value-at-Risk under Temporal and Portfolio Aggregation," Journal of Financial Econometrics, Oxford University Press, vol. 15(4), pages 649-677.
    6. Gonzalez-Rivera, Gloria & Lee, Tae-Hwy & Mishra, Santosh, 2004. "Forecasting volatility: A reality check based on option pricing, utility function, value-at-risk, and predictive likelihood," International Journal of Forecasting, Elsevier, vol. 20(4), pages 629-645.
    7. Saadi, Samir & Rahman, Abdul, 2008. "Evidence of non-stationary bias in scaling by square root of time: Implications for Value-at-Risk," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 18(3), pages 272-289, July.
    8. Odening, Martin & Hinrichs, Jan, 2002. "Assessment Of Market Risk In Hog Production Using Value-At-Risk And Extreme Value Theory," 2002 Annual meeting, July 28-31, Long Beach, CA 19907, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    9. Mark R. Manfredo & Raymond M. Leuthold, 1998. "Agricultural Applications of Value-at-Risk Analysis: A Perspective," Finance 9805002, University Library of Munich, Germany.
    10. Peter F. Christoffersen & Francis X. Diebold, 1998. "How Relevant is Volatility Forecasting for Financial Risk Management?," NBER Working Papers 6844, National Bureau of Economic Research, Inc.
    11. Th'eophile Griveau-Billion & Ben Calderhead, 2019. "A Dynamic Bayesian Model for Interpretable Decompositions of Market Behaviour," Papers 1904.08153, arXiv.org, revised Jan 2020.
    12. Kam Fong Chan & Christopher Gan & Patricia A. McGraw, 2003. "A Hedging Strategy for New Zealand’s Exporters in Transaction Exposure to Currency Risk," Multinational Finance Journal, Multinational Finance Journal, vol. 7(1-2), pages 25-54, March-Jun.
    13. Wang, Jying-Nan & Du, Jiangze & Hsu, Yuan-Teng, 2018. "Measuring long-term tail risk: Evaluating the performance of the square-root-of-time rule," Journal of Empirical Finance, Elsevier, vol. 47(C), pages 120-138.
    14. Peter F. Christoffersen & Francis X. Diebold & Til Schuermann, 1998. "Horizon Problems and Extreme Events in Financial Risk Management," Center for Financial Institutions Working Papers 98-16, Wharton School Center for Financial Institutions, University of Pennsylvania.
    15. Kavussanos, Manolis G. & Dimitrakopoulos, Dimitris N., 2011. "Market risk model selection and medium-term risk with limited data: Application to ocean tanker freight markets," International Review of Financial Analysis, Elsevier, vol. 20(5), pages 258-268.
    16. Agnieszka Borowska & Lennart Hoogerheide & Siem Jan Koopman, 2019. "Bayesian Risk Forecasting for Long Horizons," Tinbergen Institute Discussion Papers 19-018/III, Tinbergen Institute.
    17. J. Q. Smith & António Santos, 2003. "Second Order Filter Distribution Approximations for Financial Time Series with Extreme Outlier," GEMF Working Papers 2003-03, GEMF, Faculty of Economics, University of Coimbra.
    18. Danielsson, Jon & Zigrand, Jean-Pierre, 2006. "On time-scaling of risk and the square-root-of-time rule," Journal of Banking & Finance, Elsevier, vol. 30(10), pages 2701-2713, October.
    19. Amy S. K. Wong, 2006. "Basel II and the Risk Management of Basket Options with Time-Varying Correlations," International Journal of Central Banking, International Journal of Central Banking, vol. 2(4), December.
    20. Wang, Jying-Nan & Yeh, Jin-Huei & Cheng, Nick Ying-Pin, 2011. "How accurate is the square-root-of-time rule in scaling tail risk: A global study," Journal of Banking & Finance, Elsevier, vol. 35(5), pages 1158-1169, May.
    21. Simon Fritzsch & Maike Timphus & Gregor Weiss, 2021. "Marginals Versus Copulas: Which Account For More Model Risk In Multivariate Risk Forecasting?," Papers 2109.10946, arXiv.org.

  98. Francis X. Diebold & Til Schuermann, 1996. "Exact Maximum Likelihood Estimation of Observation-Driven Econometric Models," NBER Technical Working Papers 0194, National Bureau of Economic Research, Inc.

    Cited by:

    1. Martin Browning & Mette Ejrnaes & Javier Alvarez, 2006. "Modelling income processes with lots of heterogeneity," Economics Series Working Papers 285, University of Oxford, Department of Economics.
    2. Neil Shephard & Gabriele Fiorentini & Enrique Sentana, 2003. "Likelihood-based estimation of latent generalised ARCH structures," FMG Discussion Papers dp453, Financial Markets Group.
    3. Bollerslev, Tim & Ole Mikkelsen, Hans, 1996. "Modeling and pricing long memory in stock market volatility," Journal of Econometrics, Elsevier, vol. 73(1), pages 151-184, July.
    4. Pagan, Adrian, 1996. "The econometrics of financial markets," Journal of Empirical Finance, Elsevier, vol. 3(1), pages 15-102, May.
    5. Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996. "Fractionally integrated generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 74(1), pages 3-30, September.

  99. Francis X. Diebold & Abdelhak S. Senhadji, 1996. "Deterministic vs. Stochastic Trend in U.S. GNP, Yet Again," NBER Working Papers 5481, National Bureau of Economic Research, Inc.

    Cited by:

    1. Guillaume Chevillon, 2004. ""Weak" trends for inference and forecasting in finite samples," Documents de Travail de l'OFCE 2004-12, Observatoire Francais des Conjonctures Economiques (OFCE).
    2. Prodan, Ruxandra, 2008. "Potential Pitfalls in Determining Multiple Structural Changes With an Application to Purchasing Power Parity," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 50-65, January.
    3. Foster, Neil & Stehrer, Robert, 2007. "Modeling transformation in CEECs using smooth transitions," Journal of Comparative Economics, Elsevier, vol. 35(1), pages 57-86, March.
    4. Valentina Corradi & Norman R. Swanson, 2003. "The Effect of Data Transformation on Common Cycle, Cointegration and Unit Root Tests: Monte Carlo Results and a Simple Test," Departmental Working Papers 200322, Rutgers University, Department of Economics.
    5. Tortorice, Daniel L, 2018. "The business cycle implications of fluctuating long run expectations," Journal of Macroeconomics, Elsevier, vol. 58(C), pages 266-291.
    6. Zarnowitz, Victor & Ozyildirim, Ataman, 2006. "Time series decomposition and measurement of business cycles, trends and growth cycles," Journal of Monetary Economics, Elsevier, vol. 53(7), pages 1717-1739, October.
    7. Freitas, Paulo S.A. & Rodrigues, Antonio J.L., 2006. "Model combination in neural-based forecasting," European Journal of Operational Research, Elsevier, vol. 173(3), pages 801-814, September.
    8. Junsoo Lee & John List, 2004. "Examining Trends of Criteria Air Pollutants: Are the Effects of Governmental Intervention Transitory?," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 29(1), pages 21-37, September.

  100. Francis X. Diebold & Russell L. Lamb, 1996. "Why are estimates of agricultural supply response so variable?," Finance and Economics Discussion Series 96-8, Board of Governors of the Federal Reserve System (U.S.).

    Cited by:

    1. Frank Kleibergen & Eric Zivot, 2003. "Bayesian and Classical Approaches to Instrumental Variable Regression," Working Papers UWEC-2002-21-P, University of Washington, Department of Economics.
    2. Amina Al Naabi & Shekar Bose, 2020. "Do Regulatory Measures Necessarily Affect Oman’s Seafood Export-Supply?," SAGE Open, , vol. 10(3), pages 21582440209, August.
    3. Shen, Edward Z. & Perloff, Jeffrey M., 2001. "Maximum entropy and Bayesian approaches to the ratio problem," Journal of Econometrics, Elsevier, vol. 104(2), pages 289-313, September.
    4. Roman Keeney & Thomas W. Hertel, 2008. "U.S. Market Potential For Dried Distillers Grain With Solubles," Working Papers 08-13, Purdue University, College of Agriculture, Department of Agricultural Economics.
    5. Kim, Jae H. & Fraser, Iain & Hyndman, Rob J., 2011. "Improved interval estimation of long run response from a dynamic linear model: A highest density region approach," Computational Statistics & Data Analysis, Elsevier, vol. 55(8), pages 2477-2489, August.
    6. Tobias, Justin & Zellner, Arnold, 1998. "Further Results on Bayesian Method of Moments Analysis of the Multiple Regression Model," CUDARE Working Papers 198659, University of California, Berkeley, Department of Agricultural and Resource Economics.
    7. Keeney, Roman & Hertel, Thomas W., 2008. "Yield Response To Prices: Implications For Policy Modeling," Working papers 45969, Purdue University, Department of Agricultural Economics.
    8. Stigler, Matthieu M., 2018. "Supply response at the field-level: disentangling area and yield effects," 2018 Annual Meeting, August 5-7, Washington, D.C. 274343, Agricultural and Applied Economics Association.
    9. Arnold Zellner, 2003. "Some Recent Developments in Econometric Inference," Econometric Reviews, Taylor & Francis Journals, vol. 22(2), pages 203-215.
    10. Lamb, Russell L., 2000. "Food crops, exports, and the short-run policy response of agriculture in Africa," Agricultural Economics, Blackwell, vol. 22(3), pages 271-298, April.
    11. Traoré, Fousseini, 2013. "Estimating the supply elasticity of cotton in Mali with the Nerlove Model: A bayesian method of moments approach," Review of Agricultural and Environmental Studies - Revue d'Etudes en Agriculture et Environnement (RAEStud), Institut National de la Recherche Agronomique (INRA), vol. 94(3).
    12. Demont, Matty & Tollens, Eric, 2001. "Uncertainties Of Estimating The Welfare Effects Of Agricultural Biotechnology In The European Union," Working Papers 31828, Katholieke Universiteit Leuven, Centre for Agricultural and Food Economics.
    13. Hee Mok Park & Puneet Manchanda, 2015. "When Harry Bet with Sally: An Empirical Analysis of Multiple Peer Effects in Casino Gambling Behavior," Marketing Science, INFORMS, vol. 34(2), pages 179-194, March.
    14. Psaradakis, Zacharias & Sola, Martin, 1998. "Finite-sample properties of the maximum likelihood estimator in autoregressive models with Markov switching," Journal of Econometrics, Elsevier, vol. 86(2), pages 369-386, June.
    15. Anbes Tenaye, 2020. "New Evidence Using a Dynamic Panel Data Approach: Cereal Supply Response in Smallholder Agriculture in Ethiopia," Economies, MDPI, vol. 8(3), pages 1-24, July.
    16. Ball, V. Eldon & Moss, Charles B. & Erickson, Kenneth W. & Nehring, Richard F., 2003. "Modeling Supply Response In A Multiproduct Framework Revisited: The Nexus Of Empirics And Economics," 2003 Annual meeting, July 27-30, Montreal, Canada 21981, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    17. Zellner, Arnold, 1998. "The finite sample properties of simultaneous equations' estimates and estimators Bayesian and non-Bayesian approaches," Journal of Econometrics, Elsevier, vol. 83(1-2), pages 185-212.
    18. Andres Ramirez-Hassan & Manuel Correa-Giraldo, 2018. "Focused econometric estimation for noisy and small datasets: A Bayesian Minimum Expected Loss estimator approach," Papers 1809.06996, arXiv.org.

  101. Francis X. Diebold & Jose A. Lopez, 1995. "Modeling volatility dynamics," Research Paper 9522, Federal Reserve Bank of New York.

    Cited by:

    1. Bodart, Vincent & Reding, Paul, 1999. "Exchange rate regime, volatility and international correlations on bond and stock markets," Journal of International Money and Finance, Elsevier, vol. 18(1), pages 133-151, January.
    2. Tim Bollerslev, 2008. "Glossary to ARCH (GARCH)," CREATES Research Papers 2008-49, Department of Economics and Business Economics, Aarhus University.
    3. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Clara Vega, 2003. "Micro Effects of Macro Announcements: Real-Time Price Discovery in Foreign Exchange," American Economic Review, American Economic Association, vol. 93(1), pages 38-62, March.
    4. He, Changli & Teräsvirta, Timo, 1997. "Properties of Moments of a Family of GARCH Processes," SSE/EFI Working Paper Series in Economics and Finance 198, Stockholm School of Economics.
    5. Eric Ghysels & Joann Jasiak, 1997. "GARCH for Irregularly Spaced Data: The ACD-GARCH Model," CIRANO Working Papers 97s-06, CIRANO.
    6. Ghassan, Hassan Belkacem & AlHajhoj, Hassan Rafdan, 2016. "Long run dynamic volatilities between OPEC and non-OPEC crude oil prices," Applied Energy, Elsevier, vol. 169(C), pages 384-394.
    7. Nour Meddahi & Eric Renault, 2000. "Temporal Aggregation of Volatility Models," CIRANO Working Papers 2000s-22, CIRANO.
    8. Peter Christoffersen & Redouane Elkamhi & Bruno Feunou & Kris Jacobs, 2009. "Option Valuation with Conditional Heteroskedasticity and Non-Normality," CIRANO Working Papers 2009s-32, CIRANO.
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  104. Francis X. Diebold & David Neumark & Daniel Polsky, 1994. "Job Stability in the United States," NBER Working Papers 4859, National Bureau of Economic Research, Inc.

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    1. Jung, Philip & Kuhn, Moritz, 2012. "Earnings Losses and Labor Mobility over the Lifecycle," IZA Discussion Papers 6835, Institute of Labor Economics (IZA).
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    4. Henry S. Farber, 1996. "The Changing Face of Job Loss in the United States, 1981-1993," NBER Working Papers 5596, National Bureau of Economic Research, Inc.
    5. Henry S. Farber, 2007. "Is the Company Man an Anachronism? Trends in Long Term Employment in the U.S., 1973-2006," Working Papers 1039, Princeton University, Department of Economics, Industrial Relations Section..
    6. Henry S. Farber, 2007. "Job Loss and the Decline in Job Security in the United States," Working Papers 1041, Princeton University, Department of Economics, Industrial Relations Section..
    7. Moreno, Ramon & Trehan, Bharat, 1997. "Location and the Growth of Nations," Journal of Economic Growth, Springer, vol. 2(4), pages 399-418, December.
    8. Bergemann, Annette & Mertens, Antje, 2000. "Job stability trends, layoffs and quits: An empirical analysis for West Germany," SFB 373 Discussion Papers 2001,102, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    9. Raven S. Molloy & Christopher L. Smith & Abigail Wozniak, 2020. "Changing Stability in U.S. Employment Relationships: A Tale of Two Tails," Finance and Economics Discussion Series 2020-017, Board of Governors of the Federal Reserve System (U.S.).
    10. Givord, Pauline & Maurin, Eric, 2004. "Changes in job security and their causes: An empirical analysis for France, 1982-2002," European Economic Review, Elsevier, vol. 48(3), pages 595-615, June.
    11. Henry S. Farber, 2008. "Employment Insecurity: The Decline in Worker-Firm Attachment in the United States," Working Papers 1068, Princeton University, Department of Economics, Industrial Relations Section..
    12. Pierre Brochu, 2007. "Estimating Labour Market Transitions and Continuations using Repeated Cross Sectional Data," Working Papers 0703E, University of Ottawa, Department of Economics.
    13. Ann Huff Stevens, 2005. "The More Things Change, The More They Stay the Same: Trends in Long-term Employment in the United States, 1969-2002," NBER Working Papers 11878, National Bureau of Economic Research, Inc.
    14. Marianne Bertrand, 1999. "From the Invisible Handshake to the Invisible Hand? How Import Competition Changes the Employment Relationship," NBER Working Papers 6900, National Bureau of Economic Research, Inc.
    15. Luke Ignaczak & Marcel Voia, 2009. "A Nonparametric Analysis Of Canadian Employment Patterns," Carleton Economic Papers 09-01, Carleton University, Department of Economics.
    16. Guo, Rufei & Zhang, Junsen & Zhang, Ning, 2022. "How does birth endowment affect individual resilience to an adolescent adversity?," Journal of Economic Behavior & Organization, Elsevier, vol. 196(C), pages 251-265.
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    19. Peter F. Orazem & Marvin L. Bouillon & Benjamin M. Doran, 2004. "Long‐Term Attachments and Long‐Run Firm Rates of Return," Southern Economic Journal, John Wiley & Sons, vol. 71(2), pages 314-333, October.
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    22. Mertens, Antje, 1999. "Job stability trends and labor market (re-)entry in West Germany 1984 - 1997," SFB 373 Discussion Papers 1999,60, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    23. Kandel, Eugene & Pearson, Neil D., 2001. "Flexibility versus Commitment in Personnel Management," Journal of the Japanese and International Economies, Elsevier, vol. 15(4), pages 515-556, December.
    24. Cynthia Bansak & Steven Raphael, 2006. "Have Employment Relationships in the United States Become Less Stable?," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 12(3), pages 342-357, August.
    25. Jacob Mincer & Stephan Danninger, 2000. "Technology, Unemployment, and Inflation," NBER Working Papers 7817, National Bureau of Economic Research, Inc.
    26. Mary C. Daly & Greg J. Duncan, 1997. "Earnings mobility and instability, 1969-1995," Working Papers in Applied Economic Theory 97-06, Federal Reserve Bank of San Francisco.
    27. Statt, A.L., 1998. "Great Prospects: Employer Provided Training as a Credible Screening Device," Working Papers Series 9802, University of Stirling, Division of Economics.
    28. Dale Belman & David I. Levine, 2004. "Size, Skill and Sorting," LABOUR, CEIS, vol. 18(4), pages 515-561, December.
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    30. Fligstein, Neil & Shin, Taek-Jin, 2003. "The shareholder value society: A review of the changes in working conditions and inequality in the U.S., 1976-2000," Institute for Research on Labor and Employment, Working Paper Series qt0z85d717, Institute of Industrial Relations, UC Berkeley.
    31. John M. Fitzgerald, 1999. "Job Instability and Earnings and Income Consequences: Evidence from SIPP: 1983-1995," JCPR Working Papers 99, Northwestern University/University of Chicago Joint Center for Poverty Research.
    32. Hoang, Ha & Rascher, Dan, 1999. "The NBA, Exit Discrimination, and Career Earnings," MPRA Paper 3542, University Library of Munich, Germany.
    33. Henry S. Farber, 2008. "Job Loss and the Decline in Job Security in the United States," Working Papers 1055, Princeton University, Department of Economics, Center for Economic Policy Studies..
    34. Simon Burgess, 1999. "The Reallocation of Labour: An International Comparison Using Job Tenure," CEP Discussion Papers dp0416, Centre for Economic Performance, LSE.
    35. Panigo, Demian & Naticchioni, Paolo, 2004. "Employment protection, job-tenure and short term mobility wage gains," CEPREMAP Working Papers (Couverture Orange) 0402, CEPREMAP.
    36. Peter AUER & Sandrine CAZES, 2000. "The resilience of the long-term employment relationship: Evidence from the industrialized countries," International Labour Review, International Labour Organization, vol. 139(4), pages 379-408, December.
    37. Xiao, Hongyu & Wu, Andy & Kim, Jaeho, 2021. "Commuting and innovation: Are closer inventors more productive?," Journal of Urban Economics, Elsevier, vol. 121(C).
    38. Carlos García-Serrano & Juan F. Jimeno, "undated". "Labour reallocation and labour market institutions: Evidence from Spain," Working Papers 98-07, FEDEA.
    39. Henry S. Farber, 2010. "Job Loss and the Decline in Job Security in the United States," NBER Chapters, in: Labor in the New Economy, pages 223-262, National Bureau of Economic Research, Inc.
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    44. Alicia H. Munnell & Kelly Haverstick & Geoffrey Sanzenbacher, 2006. "Job Tenure and Pension Coverage," Working Papers, Center for Retirement Research at Boston College wp2006-18, Center for Retirement Research, revised Oct 2006.
    45. Paul Gregg & Jonathan Wadsworth, 2002. "Job tenure in Britain, 1975–2000. Is a job for life or just for Christmas?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 64(2), pages 111-134, May.
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    47. Robert Hill & Kezia Lilenstein & Amy Thornton, 2020. "Job spells in an emerging market: Evidence from apartheid and post-apartheid South Africa," WIDER Working Paper Series wp-2020-27, World Institute for Development Economic Research (UNU-WIDER).
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  105. Francis X. Diebold & Roberto S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.

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    1. De Leon, Marycruz & Fullerton, Thomas M., Jr. & Kelley, Brian W., 2009. "Tolls, Exchange Rates, and Borderplex International Bridge Traffic," MPRA Paper 19861, University Library of Munich, Germany.
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    3. Frédérick Demers & Annie De Champlain, 2005. "Forecasting Core Inflation in Canada: Should We Forecast the Aggregate or the Components?," Staff Working Papers 05-44, Bank of Canada.
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    6. Özen, Kadir & Yıldırım, Dilem, 2021. "Application of bagging in day-ahead electricity price forecasting and factor augmentation," Energy Economics, Elsevier, vol. 103(C).
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    8. Norman R. Swanson & Nii Ayi Armah, 2011. "Predictive Inference Under Model Misspecification with an Application to Assessing the Marginal Predictive Content of Money for Output," Departmental Working Papers 201103, Rutgers University, Department of Economics.
    9. Jose A. Lopez & Christian Walter, 2000. "Is implied correlation worth calculating? Evidence from foreign exchange options and historical data," Working Paper Series 2000-02, Federal Reserve Bank of San Francisco.
    10. Arratibel, Olga & Leiner-Killinger, Nadine & Kamps, Christophe, 2009. "Inflation forecasting in the new EU Member States," Working Paper Series 1015, European Central Bank.
    11. Gergely Ganics & Barbara Rossi & Tatevik Sekhposyan, 2019. "From fixed-event to fixed-horizon density forecasts: Obtaining measures of multi-horizon uncertainty from survey density forecasts," Economics Working Papers 1689, Department of Economics and Business, Universitat Pompeu Fabra.
    12. Adam J. Check & Anna K Nolan & Tyler C. Schipper, 2019. "Forecasting GDP Growth using Disaggregated GDP Revisions," Economics Bulletin, AccessEcon, vol. 39(4), pages 2580-2588.
    13. Lucio Sarno & Giorgio Valente, 2009. "Exchange Rates and Fundamentals: Footloose or Evolving Relationship?," Journal of the European Economic Association, MIT Press, vol. 7(4), pages 786-830, June.
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    18. Galvão, Ana Beatriz & Giraitis, Liudas & Kapetanios, George & Petrova, Katerina, 2016. "A time varying DSGE model with financial frictions," Journal of Empirical Finance, Elsevier, vol. 38(PB), pages 690-716.
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    21. Claudio, João C. & Heinisch, Katja & Holtemöller, Oliver, 2019. "Nowcasting East German GDP growth: A MIDAS approach," IWH Discussion Papers 24/2019, Halle Institute for Economic Research (IWH).
    22. Antonio Rubia & Trino-Manuel Ñíguez, 2006. "Forecasting the conditional covariance matrix of a portfolio under long-run temporal dependence," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(6), pages 439-458.
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    25. Robert Lehmann & Antje Weyh, 2016. "Forecasting Employment in Europe: Are Survey Results Helpful?," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 12(1), pages 81-117, September.
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    28. Athanasopoulos, George & Guillen, Osmani Teixeira Carvalho & Issler, João Victor & Vahid, Farshid, 2011. "Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 713, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    29. Leal, Teresa & Pérez, Javier J. & Tujula, Mika & Vidal, Jean-Pierre, 2007. "Fiscal forecasting: lessons from the literature and challenges," Working Paper Series 843, European Central Bank.
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    33. Galvão, Ana Beatriz, 2013. "Changes in predictive ability with mixed frequency data," International Journal of Forecasting, Elsevier, vol. 29(3), pages 395-410.
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    39. Goodness C. Aye & Stephen M. Miller & Rangan Gupta & Mehmet Balcilar, 2013. "Forecasting the US Real Private Residential Fixed Investment Using Large Number of Predictors," Working Papers 201348, University of Pretoria, Department of Economics.
    40. D'Agostino, Antonello & McQuinn, Kieran & Whelan, Karl, 2010. "Are Some Forecasters Really Better Than Others?," Research Technical Papers 5/RT/10, Central Bank of Ireland.
    41. Adam Clements & Yin Liao, 2014. "The role in index jumps and cojumps in forecasting stock index volatility: Evidence from the Dow Jones index," NCER Working Paper Series 101, National Centre for Econometric Research.
    42. Lu, Xin & Qiu, Jing & Lei, Gang & Zhu, Jianguo, 2022. "Scenarios modelling for forecasting day-ahead electricity prices: Case studies in Australia," Applied Energy, Elsevier, vol. 308(C).
    43. Granziera, Eleonora & Sekhposyan, Tatevik, 2019. "Predicting relative forecasting performance: An empirical investigation," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1636-1657.
    44. Theologos Dergiades & Apostolos Dasilas, 2010. "Modelling and forecasting mobile telecommunication services: the case of Greece," Applied Economics Letters, Taylor & Francis Journals, vol. 17(18), pages 1823-1828.
    45. Güneş Kamber & James Morley & Benjamin Wong, 2017. "Intuitive and Reliable Estimates of the Output Gap from a Beveridge-Nelson Filter," Reserve Bank of New Zealand Discussion Paper Series DP2017/01, Reserve Bank of New Zealand.
    46. Fildes, Robert & Stekler, Herman, 2002. "The state of macroeconomic forecasting," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 435-468, December.
    47. Jichang Dong & Wei Dai & Ying Liu & Lean Yu & Jie Wang, 2019. "Forecasting Chinese Stock Market Prices using Baidu Search Index with a Learning-Based Data Collection Method," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(05), pages 1605-1629, September.
    48. Kim, Jae H. & Wong, Kevin & Athanasopoulos, George & Liu, Shen, 2011. "Beyond point forecasting: Evaluation of alternative prediction intervals for tourist arrivals," International Journal of Forecasting, Elsevier, vol. 27(3), pages 887-901, July.
    49. Gaglianone, Wagner Piazza & Guillén, Osmani Teixeira de Carvalho & Figueiredo, Francisco Marcos Rodrigues, 2018. "Estimating inflation persistence by quantile autoregression with quantile-specific unit roots," Economic Modelling, Elsevier, vol. 73(C), pages 407-430.
    50. Olivier Bonroy & Jean-Philippe Gervais & Bruno Larue, 2007. "Are exports a monotonic function of exchange rate volatility? Evidence from disaggregated pork exports," Canadian Journal of Economics, Canadian Economics Association, vol. 40(1), pages 127-154, February.
    51. Massimiliano Marcellino, "undated". "Further Results on MSFE Encompassing," Working Papers 143, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    52. Tae-Hwy Lee & Weiping Yang, 2012. "Money–Income Granger-Causality in Quantiles," Advances in Econometrics, in: 30th Anniversary Edition, pages 385-409, Emerald Group Publishing Limited.
    53. Longo, Luigi & Riccaboni, Massimo & Rungi, Armando, 2022. "A neural network ensemble approach for GDP forecasting," Journal of Economic Dynamics and Control, Elsevier, vol. 134(C).
    54. Aaron J. Amburgey & Michael W. McCracken, 2023. "On the real‐time predictive content of financial condition indices for growth," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(2), pages 137-163, March.
    55. Kim Chung-Han, 2000. "Balassa-Samuelson Theory and Predictability of the US/UK Real Exchange Rate," International Economic Journal, Taylor & Francis Journals, vol. 14(3), pages 101-121.
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    57. Christiane Baumeister & Pierre Guérin, 2020. "A Comparison of Monthly Global Indicators for Forecasting Growth," CESifo Working Paper Series 8656, CESifo.
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    59. Matteo Bonato & Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2020. "Investor Happiness and Predictability of the Realized Volatility of Oil Price," Working Papers 202009, University of Pretoria, Department of Economics.
    60. Andrea Carriero & Todd E. Clark & Marcellino Massimiliano, 2020. "Nowcasting Tail Risks to Economic Activity with Many Indicators," Working Papers 20-13R2, Federal Reserve Bank of Cleveland, revised 22 Sep 2020.
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    62. Atsushi Inoue & Lutz Kilian & Fatma Burcu Kiraz, 2009. "Do Actions Speak Louder Than Words? Household Expectations of Inflation Based on Micro Consumption Data," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(7), pages 1331-1363, October.
    63. Foroni, Claudia & Guérin, Pierre & Marcellino, Massimiliano, 2018. "Using low frequency information for predicting high frequency variables," International Journal of Forecasting, Elsevier, vol. 34(4), pages 774-787.
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    66. Chalamandaris, Georgios & Tsekrekos, Andrianos E., 2010. "Predictable dynamics in implied volatility surfaces from OTC currency options," Journal of Banking & Finance, Elsevier, vol. 34(6), pages 1175-1188, June.
    67. Isabel Figuerola‐Ferretti & Alejandro Rodríguez & Eduardo Schwartz, 2021. "Oil price analysts' forecasts," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(9), pages 1351-1374, September.
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    2801. Guillermo Benavides Perales & Israel Felipe Mora Cuevas, 2008. "Parametric vs. non-parametric methods for estimating option implied risk-neutral densities: the case of the exchange rate Mexican peso – US dollar," Ensayos Revista de Economia, Universidad Autonoma de Nuevo Leon, Facultad de Economia, vol. 0(1), pages 33-52, May.
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    2821. Li, Tenghui & Liu, Xiaolei & Lin, Zi & Morrison, Rory, 2022. "Ensemble offshore Wind Turbine Power Curve modelling – An integration of Isolation Forest, fast Radial Basis Function Neural Network, and metaheuristic algorithm," Energy, Elsevier, vol. 239(PD).
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    Cited by:

    1. Lisa A. Kramer & Mark J. Kamstra & Maurice D. Levi, 2000. "Losing Sleep at the Market: The Daylight Saving Anomaly," American Economic Review, American Economic Association, vol. 90(4), pages 1005-1011, September.
    2. Lubos Pastor & Robert F. Stambaugh, "undated". "The Equity Premium and Structural Breaks," Rodney L. White Center for Financial Research Working Papers 11-00, Wharton School Rodney L. White Center for Financial Research.
    3. Bernard, Jean-Thomas & Idoudi, Nadhem & Khalaf, Lynda & Yelou, Clement, 2007. "Finite sample multivariate structural change tests with application to energy demand models," Journal of Econometrics, Elsevier, vol. 141(2), pages 1219-1244, December.
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    1. Ginburgh, V. & Michel, P., 1992. "Optimal Policy Business Cycle," Papiers d'Economie Mathématique et Applications 92-01, Université Panthéon-Sorbonne (Paris 1).
    2. GINSBURGH, V. & MICHEL, Ph., 1998. "Optimal policy business cycles," LIDAM Reprints CORE 1311, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

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    4. Amélie Charles & Olivier Darné & Claude Diebolt & Laurent Ferrara, 2012. "A new monthly chronology of the US industrial cycles in the prewar economy," Working Papers 12-02, Association Française de Cliométrie (AFC).
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    6. Olivier Jean Blanchard, 2000. "The automatic fiscal stabilizers: quietly doing their thing - commentary," Economic Policy Review, Federal Reserve Bank of New York, issue Apr, pages 69-74.
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    8. Enrique López Enciso, 2019. "Dos tradiciones en la medición del ciclo: historia general y desarrollos en Colombia," Tiempo y Economía, Universidad de Bogotá Jorge Tadeo Lozano, vol. 6(1), pages 77-142, February.
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    1. Claessens, Stijn & Kose, M. Ayhan & Terrones, Marco E., 2012. "How do business and financial cycles interact?," Journal of International Economics, Elsevier, vol. 87(1), pages 178-190.
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    7. Nadal De Simone, Francisco & Clarke, Sean, 2007. "Asymmetry in business fluctuations: International evidence on Friedman's plucking model," Journal of International Money and Finance, Elsevier, vol. 26(1), pages 64-85, February.
    8. Francis X. Diebold & Glenn D. Rudebusch, 1994. "Measuring Business Cycles: A Modern Perspective," NBER Working Papers 4643, National Bureau of Economic Research, Inc.
    9. Vítor Castro & Rodrigo Martins, 2018. "Economic and political drivers of the duration of credit booms," NIPE Working Papers 15/2018, NIPE - Universidade do Minho.
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    13. Vitor Castro, 2015. "The Portuguese business cycle: chronology and duration dependence," Empirical Economics, Springer, vol. 49(1), pages 325-342, August.
    14. Luca Agnello & Vítor Castro & Ricardo M. Sousa, 2018. "The Legacy and the Tyranny of Time: Exit and Re‐Entry of Sovereigns to International Capital Markets," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(8), pages 1969-1994, December.
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    25. Giuseppe Vita & Livio Ferrante, 2021. "Is legislation grease or sand to economic growth? An econometric analysis using data from Italian regions before and after the 2008 crisis," European Journal of Law and Economics, Springer, vol. 51(3), pages 541-561, June.
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    44. Taamouti, Abderrahim, 2012. "Moments of multivariate regime switching with application to risk-return trade-off," Journal of Empirical Finance, Elsevier, vol. 19(2), pages 292-308.
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    46. Billio Monica & Casarin Roberto, 2011. "Beta Autoregressive Transition Markov-Switching Models for Business Cycle Analysis," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(4), pages 1-32, September.
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    2. Chan Guk Huh, 1998. "Forecasting industrial production using models with business cycle asymmetry," Economic Review, Federal Reserve Bank of San Francisco, pages 29-41.
    3. Francis X. Diebold, 2012. "Comparing Predictive Accuracy, Twenty Years Later: A Personal Perspective on the Use and Abuse of Diebold-Mariano Tests," PIER Working Paper Archive 12-035, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    4. Tazwell S. Rowe & Roy H. Webb, 1995. "An index of leading indicators for inflation," Economic Quarterly, Federal Reserve Bank of Richmond, issue Spr, pages 75-96.
    5. Meyer-Gohde, Alexander & Shabalina, Ekaterina, 2022. "Estimation and forecasting using mixed-frequency DSGE models," IMFS Working Paper Series 175, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS).
    6. Havranek, Tomas & Zeynalov, Ayaz, 2018. "Forecasting Tourist Arrivals: Google Trends Meets Mixed Frequency Data," MPRA Paper 90205, University Library of Munich, Germany.
    7. Lin, Wen-Ling, 1995. "Market closure and predictability of intradaily stock returns in the United States and Japan," Journal of Empirical Finance, Elsevier, vol. 2(1), pages 19-44, March.
    8. Gerdesmeier Dieter & Roffia Barbara & Reimers Hans-Eggert, 2017. "Forecasting Euro Area Inflation Using Single-Equation and Multivariate VAR–Models," Folia Oeconomica Stetinensia, Sciendo, vol. 17(2), pages 19-34, December.

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    1. Ingolf Dittmann, 2000. "Residual‐Based Tests For Fractional Cointegration: A Monte Carlo Study," Journal of Time Series Analysis, Wiley Blackwell, vol. 21(6), pages 615-647, November.
    2. OlaOluwa S. Yaya & Ahamuefula E. Ogbonna & Robert Mudida & Nuruddeen Abu, 2021. "Market efficiency and volatility persistence of cryptocurrency during pre‐ and post‐crash periods of Bitcoin: Evidence based on fractional integration," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 1318-1335, January.
    3. Baillie, Richard T & Bollerslev, Tim, 1994. "Cointegration, Fractional Cointegration, and Exchange Rate Dynamics," Journal of Finance, American Finance Association, vol. 49(2), pages 737-745, June.
    4. Luis A. Gil-Alana & James Payne & David Loomis, 2010. "Does energy consumption by the US electric power secto exhibit long memory behaviour?," Faculty Working Papers 04/10, School of Economics and Business Administration, University of Navarra.
    5. Luis A. Gil-Alana & Rangan Gupta, 2013. "Persistence and Cycles in Historical Oil Prices Data," Working Papers 201375, University of Pretoria, Department of Economics.
    6. Galán-Gutiérrez, Juan Antonio & Martín-García, Rodrigo, 2021. "Cointegration between the structure of copper futures prices and Brexit," Resources Policy, Elsevier, vol. 71(C).
    7. Uwe Hassler & Matei Demetrescu & Adina Tarcolea, 2011. "Asymptotic normal tests for integration in panels with cross-dependent units," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(2), pages 187-204, June.
    8. Juan Infante & Marta Rio & Luis A. Gil-Alana, 2023. "Measuring Persistence in the US Equity Gender Diversity Index," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 167(1), pages 175-182, June.
    9. Joseph Ross, 2021. "Stationarity Statistics on Rolling Windows," Computational Economics, Springer;Society for Computational Economics, vol. 57(2), pages 655-691, February.
    10. Luis A. Gil-Alana & Juncal Cunado & Rangan Gupta, 2015. "Persistence, Mean-Reversion and Non-Linearities in Infant Mortality Rates," Working Papers 201574, University of Pretoria, Department of Economics.
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    12. João Ricardo Faria & Juan Carlos Cuestas & Luis Gil-Alana & Estefania Mourelle, 2021. "Self-employment by gender in the EU: convergence and clusters," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 48(3), pages 717-741, August.
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    43. Chevillon, Guillaume & Mavroeidis, Sophocles, 2011. "Learning generates Long Memory," ESSEC Working Papers WP1113, ESSEC Research Center, ESSEC Business School.
    44. Christian Fischer & Luis Gil-Alana, 2009. "The nature of the relationship between international tourism and international trade: the case of German imports of Spanish wine," Applied Economics, Taylor & Francis Journals, vol. 41(11), pages 1345-1359.
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    49. Martin-Valmayor, Miguel A. & Gil-Alana, Luis A. & Infante, Juan, 2023. "Energy prices in Europe. Evidence of persistence across markets," Resources Policy, Elsevier, vol. 82(C).
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    1. Quoreshi, Shahiduzzaman, 2006. "Time Series Modelling Of High Frequency Stock Transaction Data," Umeå Economic Studies 675, Umeå University, Department of Economics.
    2. Quoreshi, Shahiduzzaman, 2006. "LongMemory, Count Data, Time Series Modelling for Financial Application," Umeå Economic Studies 673, Umeå University, Department of Economics.
    3. Mohamed Boutahar, 2002. "General Autoregressive Models with Long-Memory Noise," Statistical Inference for Stochastic Processes, Springer, vol. 5(3), pages 321-333, October.

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    1. E. Skordilis & R. Moghaddass, 2017. "A condition monitoring approach for real-time monitoring of degrading systems using Kalman filter and logistic regression," International Journal of Production Research, Taylor & Francis Journals, vol. 55(19), pages 5579-5596, October.
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    2. João Victor Issler & Hilton Hostalacio Notini & Claudia Fontoura Rodrigues, 2013. "Constructing coincident and leading indices of economic activity for the Brazilian economy," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2012(2), pages 43-65.
    3. Travis J. Berge & Damjan Pfajfar, 2019. "Duration Dependence, Monetary Policy Asymmetries, and the Business Cycle," Finance and Economics Discussion Series 2019-020, Board of Governors of the Federal Reserve System (U.S.).
    4. Paul Cashin & C John McDermott & Alasdair Scott, 1999. "Booms and slumps in world commodity prices," Reserve Bank of New Zealand Discussion Paper Series G99/8, Reserve Bank of New Zealand.
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    8. Vítor Castro, 2010. "The duration of business cycle expansions and contractions: Are there change-points in duration dependence?," NIPE Working Papers 24/2010, NIPE - Universidade do Minho.
    9. Vitor Castro, 2015. "The Portuguese business cycle: chronology and duration dependence," Empirical Economics, Springer, vol. 49(1), pages 325-342, August.
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    71. de Bruijn, L.P. & Franses, Ph.H.B.F., 2015. "Stochastic levels and duration dependence in US unemployment," Econometric Institute Research Papers EI2015-20, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
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    1. Richard Rosen, 2002. "What Goes Up Must Come Down? Asymmetries and Persistence in Bank Deposit Rates," Journal of Financial Services Research, Springer;Western Finance Association, vol. 21(3), pages 173-193, June.
    2. Barry Scholnick, 1999. "Interest Rate Asymmetries in Long-Term Loan and Deposit Markets," Journal of Financial Services Research, Springer;Western Finance Association, vol. 16(1), pages 5-26, September.

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    1. Danny Quah, 1987. "What Do We Learn from Unit Roots in Macroeconomic Time Series?," NBER Working Papers 2450, National Bureau of Economic Research, Inc.
    2. Cochran, Steven J. & DeFina, Robert H., 1996. "Predictability in real exchange rates: Evidence from parametric hazard models," International Review of Economics & Finance, Elsevier, vol. 5(2), pages 125-147.
    3. Abderrezak, Ali, 1998. "On the Duration of Growth Cycles: An International Study," International Review of Economics & Finance, Elsevier, vol. 7(3), pages 343-355.

  130. Francis X. Diebold & Glenn D. Rudebusch, 1987. "Scoring the leading indicators," Special Studies Papers 206, Board of Governors of the Federal Reserve System (U.S.).

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    1. Hashmat Khan & Santosh Upadhayaya, 2017. "Does Business Confidence Matter for Investment?," Carleton Economic Papers 17-13, Carleton University, Department of Economics, revised 20 Mar 2019.
    2. Jens J. Krüger, 2021. "A Wavelet Evaluation of Some Leading Business Cycle Indicators for the German Economy," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(3), pages 293-319, December.
    3. Knedlik, Tobias & von Schweinitz, Gregor, 2011. "Macroeconomic Imbalances as Indicators for Debt Crises in Europe," IWH Discussion Papers 12/2011, Halle Institute for Economic Research (IWH).
    4. Layton, Allan P. & Katsuura, Masaki, 2001. "Comparison of regime switching, probit and logit models in dating and forecasting US business cycles," International Journal of Forecasting, Elsevier, vol. 17(3), pages 403-417.
    5. Reinhart, Carmen & Goldstein, Morris & Kaminsky, Graciela, 2000. "Assessing financial vulnerability, an early warning system for emerging markets: Introduction," MPRA Paper 13629, University Library of Munich, Germany.
    6. Marcelle Chauvet, 2001. "The Brazilian Economic Fluctuations," Anais do XXIX Encontro Nacional de Economia [Proceedings of the 29th Brazilian Economics Meeting] 033, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    7. João Victor Issler & Hilton Hostalacio Notini & Claudia Fontoura Rodrigues, 2013. "Constructing coincident and leading indices of economic activity for the Brazilian economy," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2012(2), pages 43-65.
    8. Ferriani, Fabrizio, 2010. "Informed and uninformed traders at work: evidence from the French market," MPRA Paper 24487, University Library of Munich, Germany.
    9. Michael P. Clements & David I. Harvey, 2010. "Forecast encompassing tests and probability forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(6), pages 1028-1062.
    10. Zeynep Senyuz, 2011. "Factor analysis of permanent and transitory dynamics of the US economy and the stock market," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(6), pages 975-998, September.
    11. Heun, Michael & Schlink, Torsten, 2004. "Early warning systems of financial crises: implementation of a currency crisis model for Uganda," Frankfurt School - Working Paper Series 59, Frankfurt School of Finance and Management.
    12. Carriero, Andrea & Marcellino, Massimiliano, 2007. "A comparison of methods for the construction of composite coincident and leading indexes for the UK," International Journal of Forecasting, Elsevier, vol. 23(2), pages 219-236.
    13. James H. Stock & Mark W. Watson, 1989. "New Indexes of Coincident and Leading Economic Indicators," NBER Chapters, in: NBER Macroeconomics Annual 1989, Volume 4, pages 351-409, National Bureau of Economic Research, Inc.
    14. Shyh-Wei Chen, 2007. "Using Regional Cycles to Measure National Business Cycles in the U.S. with the Markov Switching Panel Model," Economics Bulletin, AccessEcon, vol. 3(46), pages 1-12.
    15. Lota D. Tamini & Jean‐Philippe Gervais, 2005. "Developing Economic Indexes for the Quebec Hog/Pork Industry," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 53(1), pages 1-23, March.
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    3. Wang, Yudong & Hao, Xianfeng, 2023. "Forecasting the real prices of crude oil: What is the role of parameter instability?," Energy Economics, Elsevier, vol. 117(C).
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    5. Hsiao, Cheng & Wan, Shui Ki, 2014. "Is there an optimal forecast combination?," Journal of Econometrics, Elsevier, vol. 178(P2), pages 294-309.
    6. Pennings, Clint L.P. & van Dalen, Jan & Rook, Laurens, 2019. "Coordinating judgmental forecasting: Coping with intentional biases," Omega, Elsevier, vol. 87(C), pages 46-56.
    7. Colino, Evelyn V. & Irwin, Scott H. & Garcia, Philip, 2009. "Do Composite Procedures Really Improve the Accuracy of Outlook Forecasts?," 2009 Conference, April 20-21, 2009, St. Louis, Missouri 53052, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    8. Luis F. Melo Velandia & Rubén A. Loaiza Maya & Mauricio Villamizar-Villegas, 2014. "Bayesian Combination for Inflation Forecasts: The Effects of a Prior Based on Central Banks’ Estimates," Borradores de Economia 853, Banco de la Republica de Colombia.
    9. Roccazzella, Francesco & Gambetti, Paolo & Vrins, Frédéric, 2021. "Optimal and robust combination of forecasts via constrained optimization and shrinkage," LIDAM Reprints LFIN 2021014, Université catholique de Louvain, Louvain Finance (LFIN).
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    11. Yang Zhao & Charalampos Stasinakis & Georgios Sermpinis & Filipa Da Silva Fernandes, 2019. "Revisiting Fama–French factors' predictability with Bayesian modelling and copula‐based portfolio optimization," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 24(4), pages 1443-1463, October.
    12. Xi Wu & Adam Blake, 2023. "Does the combination of models with different explanatory variables improve tourism demand forecasting performance?," Tourism Economics, , vol. 29(8), pages 2032-2056, December.
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      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
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Articles

  1. Diebold, Francis X. & Göbel, Maximilian, 2022. "A benchmark model for fixed-target Arctic sea ice forecasting," Economics Letters, Elsevier, vol. 215(C).
    See citations under working paper version above.
  2. Diebold, Francis X. & Rudebusch, Glenn D., 2022. "Probability assessments of an ice-free Arctic: Comparing statistical and climate model projections," Journal of Econometrics, Elsevier, vol. 231(2), pages 520-534.
    See citations under working paper version above.
  3. Diebold, Francis X. & Göbel, Maximilian & Goulet Coulombe, Philippe & Rudebusch, Glenn D. & Zhang, Boyuan, 2021. "Optimal combination of Arctic sea ice extent measures: A dynamic factor modeling approach," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1509-1519.
    See citations under working paper version above.
  4. Diebold, Francis X. & Shin, Minchul, 2019. "Machine learning for regularized survey forecast combination: Partially-egalitarian LASSO and its derivatives," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1679-1691.
    See citations under working paper version above.
  5. Mert Demirer & Francis X. Diebold & Laura Liu & Kamil Yilmaz, 2018. "Estimating global bank network connectedness," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(1), pages 1-15, January.
    See citations under working paper version above.
  6. Ross Askanazi & Francis X. Diebold & Frank Schorfheide & Minchul Shin, 2018. "On the Comparison of Interval Forecasts," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(6), pages 953-965, November.
    See citations under working paper version above.
  7. Diebold, Francis X. & Schorfheide, Frank & Shin, Minchul, 2017. "Real-time forecast evaluation of DSGE models with stochastic volatility," Journal of Econometrics, Elsevier, vol. 201(2), pages 322-332.
    See citations under working paper version above.
  8. Francis X. Diebold & Minchul Shin, 2017. "Assessing point forecast accuracy by stochastic error distance," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 588-598, October.
    See citations under working paper version above.
  9. Aruoba, S. Borağan & Diebold, Francis X. & Nalewaik, Jeremy & Schorfheide, Frank & Song, Dongho, 2016. "Improving GDP measurement: A measurement-error perspective," Journal of Econometrics, Elsevier, vol. 191(2), pages 384-397.
    See citations under working paper version above.
  10. Francis X. Diebold & Kamil Yilmaz, 2016. "Trans-Atlantic Equity Volatility Connectedness: U.S. and European Financial Institutions, 2004–2014," Journal of Financial Econometrics, Oxford University Press, vol. 14(1), pages 81-127.

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    3. Schwaab, Bernd & Koopman, Siem Jan & Lucas, André & Nucera, Federico, 2016. "The information in systemic risk rankings," Working Paper Series 1875, European Central Bank.
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    5. Mensi, Walid & Shafiullah, Muhammad & Vo, Xuan Vinh & Kang, Sang Hoon, 2021. "Volatility spillovers between strategic commodity futures and stock markets and portfolio implications: Evidence from developed and emerging economies," Resources Policy, Elsevier, vol. 71(C).
    6. Ji, Qiang & Bahloul, Walid & Geng, Jiang-Bo & Gupta, Rangan, 2020. "Trading behaviour connectedness across commodity markets: Evidence from the hedgers’ sentiment perspective," Research in International Business and Finance, Elsevier, vol. 52(C).
    7. Thiem, Christopher, 2018. "Cross-category spillovers of economic policy uncertainty," Ruhr Economic Papers 744, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    8. Borjigin, Sumuya & Gao, Ting & Sun, Yafei & An, Biao, 2020. "For evil news rides fast, while good news baits later?—A network based analysis in Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 551(C).
    9. Honghai Yu & Wangyu Chu & Yu’ang Ding & Xuezhou Zhao, 2021. "Risk contagion of global stock markets under COVID‐19:A network connectedness method," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(4), pages 5745-5782, December.
    10. Mensi, Walid & Sensoy, Ahmet & Aslan, Aylin & Kang, Sang Hoon, 2019. "High-frequency asymmetric volatility connectedness between Bitcoin and major precious metals markets," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    11. Jozef Baruník & Evžen Kocenda & Lukáš Vácha, 2015. "Asymmetric Connectedness on the U.S. Stock Market: Bad and Good Volatility Spillover," CESifo Working Paper Series 5305, CESifo.
    12. Baik, Hyeoncheol & Han, Sumin & Joo, Sunghoon & Lee, Kangbok, 2022. "A bank's optimal capital ratio: A time-varying parameter model to the partial adjustment framework," Journal of Banking & Finance, Elsevier, vol. 142(C).
    13. Gloria Gonzalez-Rivera & Joao Henrique Mazzeu & Esther Ruiz & Helena Veiga, 2017. "A Bootstrap Approach for Generalized Autocontour Testing. Implications for VIX Forecast Densities," Working Papers 201709, University of California at Riverside, Department of Economics.
    14. David E. Allen & Michael McAleer & Robert Powell & Abhay K. Singh, 2017. "Volatility spillover and multivariate volatility impulse response analysis of GFC news events," Applied Economics, Taylor & Francis Journals, vol. 49(33), pages 3246-3262, July.
    15. Billio, Monica & Casarin, Roberto & Rossini, Luca, 2019. "Bayesian nonparametric sparse VAR models," Journal of Econometrics, Elsevier, vol. 212(1), pages 97-115.
    16. Bouri, Elie & Lucey, Brian & Roubaud, David, 2020. "Dynamics and determinants of spillovers across the option-implied volatilities of US equities," The Quarterly Review of Economics and Finance, Elsevier, vol. 75(C), pages 257-264.
    17. Mensi, Walid & Hammoudeh, Shawkat & Rehman, Mobeen Ur & Al-Maadid, Alanoud Ali S. & Hoon Kang, Sang, 2020. "Dynamic risk spillovers and portfolio risk management between precious metals and global foreign exchange markets," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    18. Everett Grant, 2018. "The Double-Edged Sword of Global Integration: Robustness, Fragility \& Contagion in the International Firm Network," 2018 Meeting Papers 506, Society for Economic Dynamics.
    19. Honghai Yu & Wencong Sun & Xiangting Ye & Libing Fang, 2019. "Measuring the increasing connectedness of Chinese assets with global assets: using a variance decompositions method," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(5), pages 1261-1290, March.
    20. Ji, Qiang & Bouri, Elie & Lau, Chi Keung Marco & Roubaud, David, 2019. "Dynamic connectedness and integration in cryptocurrency markets," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 257-272.
    21. Boido, Claudio & Aliano, Mauro, 2023. "Digital art and non-fungible-token: Bubble or revolution?," Finance Research Letters, Elsevier, vol. 52(C).
    22. Naeem, Muhammad Abubakr & Peng, Zhe & Suleman, Mouhammed Tahir & Nepal, Rabindra & Shahzad, Syed Jawad Hussain, 2020. "Time and frequency connectedness among oil shocks, electricity and clean energy markets," Energy Economics, Elsevier, vol. 91(C).
    23. Kashif Hamid & Rana Shahid Imdad Akash & Muhammad Mudassar Ghafoor, 2019. "Testing of Volatility Spillovers Dynamics and Network Connectedness between Islamic Indices of Regional Stock Markets," Global Regional Review, Humanity Only, vol. 4(1), pages 128-137, March.
    24. Mensi, Walid & Hammoudeh, Shawkat & Shahzad, Syed Jawad Hussain & Al-Yahyaee, Khamis Hamed & Shahbaz, Muhammad, 2017. "Oil and foreign exchange market tail dependence and risk spillovers for MENA, emerging and developed countries: VMD decomposition based copulas," Energy Economics, Elsevier, vol. 67(C), pages 476-495.
    25. Maitra, Debasish & Rehman, Mobeen Ur & Dash, Saumya Ranjan & Kang, Sang Hoon, 2021. "Oil price volatility and the logistics industry: Dynamic connectedness with portfolio implications," Energy Economics, Elsevier, vol. 102(C).
    26. Nektarios Aslanidis & Aurelio F. Bariviera & Alejandro Perez-Laborda, 2020. "Are cryptocurrencies becoming more interconnected?," Papers 2009.14561, arXiv.org.
    27. Hsu, Chih-Hsiang & Lee, Hsiu-Chuan & Lien, Donald, 2020. "Stock market uncertainty, volatility connectedness of financial institutions, and stock-bond return correlations," International Review of Economics & Finance, Elsevier, vol. 70(C), pages 600-621.
    28. Julián Andrada-Félix & Adrian Fernandez-Perez & Simón Sosvilla-Rivero, 2018. "Fear connectedness among asset classes," Applied Economics, Taylor & Francis Journals, vol. 50(39), pages 4234-4249, August.
    29. Mensi, Walid & Boubaker, Ferihane Zaraa & Al-Yahyaee, Khamis Hamed & Kang, Sang Hoon, 2018. "Dynamic volatility spillovers and connectedness between global, regional, and GIPSI stock markets," Finance Research Letters, Elsevier, vol. 25(C), pages 230-238.
    30. Cao, Li & Jiang, Junhua & Piljak, Vanja, 2023. "Did mega-regional trade agreements reshuffle the financial influence of the US, China, and Japan in ASEAN? Evidence from the volatility-spillover effects," Research in International Business and Finance, Elsevier, vol. 65(C).
    31. Buncic, Daniel & Gisler, Katja I.M., 2016. "Global equity market volatility spillovers: A broader role for the United States," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1317-1339.
    32. Sheheryar Malik & Ms. TengTeng Xu, 2017. "Interconnectedness of Global Systemically-Important Banks and Insurers," IMF Working Papers 2017/210, International Monetary Fund.
    33. Mensi, Walid & Hammoudeh, Shawkat & Al-Jarrah, Idries Mohammad Wanas & Sensoy, Ahmet & Kang, Sang Hoon, 2017. "Dynamic risk spillovers between gold, oil prices and conventional, sustainability and Islamic equity aggregates and sectors with portfolio implications," Energy Economics, Elsevier, vol. 67(C), pages 454-475.
    34. Andrada-Félix, Julián & Fernandez-Perez, Adrian & Sosvilla-Rivero, Simón, 2020. "Distant or close cousins: Connectedness between cryptocurrencies and traditional currencies volatilities," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 67(C).
    35. Boakye, Robert Owusu & Mensah, Lord Kwaku & Kang, Sang Hoon & Osei, Kofi Acheampong, 2023. "Foreign exchange market return spillovers and connectedness among African countries," International Review of Financial Analysis, Elsevier, vol. 86(C).
    36. Mensi, Walid & Shafiullah, Muhammad & Vo, Xuan Vinh & Kang, Sang Hoon, 2022. "Asymmetric spillovers and connectedness between crude oil and currency markets using high-frequency data," Resources Policy, Elsevier, vol. 77(C).
    37. Dungey, Mardi & Harvey, John & Volkov, Vladimir, 2017. "The changing international network of sovereign debt and financial institutions," Working Papers 2017-04, University of Tasmania, Tasmanian School of Business and Economics.
    38. Nishimura, Yusaku & Sun, Bianxia, 2018. "The intraday volatility spillover index approach and an application in the Brexit vote," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 55(C), pages 241-253.
    39. Dimitris Korobilis & Kamil Yilmaz, 2018. "Measuring Dynamic Connectedness with Large Bayesian VAR Models," Koç University-TUSIAD Economic Research Forum Working Papers 1802, Koc University-TUSIAD Economic Research Forum.
    40. Antonakakis, Nikolaos & Gabauer, David, 2017. "Refined Measures of Dynamic Connectedness based on TVP-VAR," MPRA Paper 78282, University Library of Munich, Germany.
    41. Lin, Sihan & Chen, Shoudong, 2021. "Dynamic connectedness of major financial markets in China and America," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 646-656.
    42. Rosenkranz, Peter & Melchor, Monica, 2022. "Asia’s financial interconnectedness: Evolution, implications, and insights from past crises," Economic Analysis and Policy, Elsevier, vol. 76(C), pages 685-707.
    43. Gonçalves Mazzeu, Joao Henrique & González-Rivera, Gloria & Ruiz Ortega, Esther & Veiga, Helena, 2016. "A Bootstrap Approach for Generalized Autocontour Testing," DES - Working Papers. Statistics and Econometrics. WS 23457, Universidad Carlos III de Madrid. Departamento de Estadística.
    44. Mardi Dungey & Marius Matei & Matteo Luciani & David Veredas, 2017. "Surfing through the GFC: Systemic Risk in Australia," The Economic Record, The Economic Society of Australia, vol. 93(300), pages 1-19, March.
    45. Maitra, Debasish & Guhathakurta, Kousik & Kang, Sang Hoon, 2021. "The good, the bad and the ugly relation between oil and commodities: An analysis of asymmetric volatility connectedness and portfolio implications," Energy Economics, Elsevier, vol. 94(C).
    46. Yizhuo Zhang & Rui Chen & Ding Ma, 2020. "A Weighted and Directed Perspective of Global Stock Market Connectedness: A Variance Decomposition and GERGM Framework," Sustainability, MDPI, vol. 12(11), pages 1-23, June.
    47. Chen, Sihong & Wu, Ximing, 2016. "Comovements and Volatility Spillover in Commodity Markets," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235686, Agricultural and Applied Economics Association.
    48. Niţoi, Mihai & Pochea, Maria Miruna, 2022. "The nexus between bank connectedness and investors’ sentiment," Finance Research Letters, Elsevier, vol. 44(C).
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    50. Christopher Thiem, 2020. "Cross-Category, Trans-Pacific Spillovers of Policy Uncertainty and Financial Market Volatility," Open Economies Review, Springer, vol. 31(2), pages 317-342, April.
    51. Mensi, Walid & Aslan, Aylin & Vo, Xuan Vinh & Kang, Sang Hoon, 2023. "Time-frequency spillovers and connectedness between precious metals, oil futures and financial markets: Hedge and safe haven implications," International Review of Economics & Finance, Elsevier, vol. 83(C), pages 219-232.
    52. Caporale, Guglielmo Maria & Kang, Woo-Young & Spagnolo, Fabio & Spagnolo, Nicola, 2021. "Cyber-attacks, spillovers and contagion in the cryptocurrency markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    53. Okorie, David Iheke & Lin, Boqiang, 2023. "Cryptocurrency spectrum and 2020 pandemic: Contagion analysis," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 29-38.
    54. Mensi, Walid & Al-Yahyaee, Khamis Hamed & Wanas Al-Jarrah, Idries Mohammad & Vo, Xuan Vinh & Kang, Sang Hoon, 2021. "Does volatility connectedness across major cryptocurrencies behave the same at different frequencies? A portfolio risk analysis," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 96-113.
    55. Li, Xingyi & Gan, Kai & Zhou, Qi, 2023. "Dynamic volatility connectedness among cryptocurrencies and China's financial assets in standard times and during the COVID-19 pandemic," Finance Research Letters, Elsevier, vol. 51(C).
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    85. Zhang, Weiping & Zhuang, Xintian & Lu, Yang, 2020. "Spatial spillover effects and risk contagion around G20 stock markets based on volatility network," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    86. Mensi, Walid & Al Rababa'a, Abdel Razzaq & Vo, Xuan Vinh & Kang, Sang Hoon, 2021. "Asymmetric spillover and network connectedness between crude oil, gold, and Chinese sector stock markets," Energy Economics, Elsevier, vol. 98(C).
    87. Zhang, Wenting & He, Xie & Hamori, Shigeyuki, 2022. "Volatility spillover and investment strategies among sustainability-related financial indexes: Evidence from the DCC-GARCH-based dynamic connectedness and DCC-GARCH t-copula approach," International Review of Financial Analysis, Elsevier, vol. 83(C).
    88. Guhathakurta, Kousik & Dash, Saumya Ranjan & Maitra, Debasish, 2020. "Period specific volatility spillover based connectedness between oil and other commodity prices and their portfolio implications," Energy Economics, Elsevier, vol. 85(C).
    89. Genc, Ismail H., 2022. "Are Indian Subcontinent remittance markets connected to each other?," Journal of Asian Economics, Elsevier, vol. 80(C).
    90. Clements, A.E. & Liao, Y., 2020. "Firm-specific information and systemic risk," Economic Modelling, Elsevier, vol. 90(C), pages 480-493.
    91. Lundgren, Amanda Ivarsson & Milicevic, Adriana & Uddin, Gazi Salah & Kang, Sang Hoon, 2018. "Connectedness network and dependence structure mechanism in green investments," Energy Economics, Elsevier, vol. 72(C), pages 145-153.
    92. Chung, Chien-Ping & Liao, Tzu-Hsiang & Lee, Hsiu-Chuan, 2021. "Volatility spillovers of A- and B-shares for the Chinese stock market and its impact on the Chinese index returns," Pacific-Basin Finance Journal, Elsevier, vol. 65(C).
    93. Mensi, Walid & Nekhili, Ramzi & Vo, Xuan Vinh & Suleman, Tahir & Kang, Sang Hoon, 2021. "Asymmetric volatility connectedness among U.S. stock sectors," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    94. Arı, Yakup, 2022. "USD/TRY and foreign banks in Turkey: Evidence by TVP-VAR," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 67, pages 5-26.
    95. Steve Hyun & Jimin Lee & Jong-Min Kim & Chulhee Jun, 2019. "What Coins Lead in the Cryptocurrency Market: Using Copula and Neural Networks Models," JRFM, MDPI, vol. 12(3), pages 1-14, August.
    96. Ling, Yu-Xiu & Xie, Chi & Wang, Gang-Jin, 2022. "Interconnectedness between convertible bonds and underlying stocks in the Chinese capital market: A multilayer network perspective," Emerging Markets Review, Elsevier, vol. 52(C).

  11. Diebold, Francis X. & Shin, Minchul, 2015. "Assessing point forecast accuracy by stochastic loss distance," Economics Letters, Elsevier, vol. 130(C), pages 37-38.

    Cited by:

    1. Hitesh Doshi & Kris Jacobs & Rui Liu, 2021. "Information in the Term Structure: A Forecasting Perspective," Management Science, INFORMS, vol. 67(8), pages 5255-5277, August.
    2. Norman R. Swanson & Weiqi Xiong, 2018. "Big data analytics in economics: What have we learned so far, and where should we go from here?," Canadian Journal of Economics, Canadian Economics Association, vol. 51(3), pages 695-746, August.
    3. Emilian Dobrescu, 2014. "Attempting to Quantify the Accuracy of Complex Macroeconomic Forecasts," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 5-21, December.
    4. Jin, Sainan & Corradi, Valentina & Swanson, Norman R., 2017. "Robust Forecast Comparison," Econometric Theory, Cambridge University Press, vol. 33(6), pages 1306-1351, December.
    5. Valentina Corradi & Sainan Jin & Norman R. Swanson, 2023. "Robust forecast superiority testing with an application to assessing pools of expert forecasters," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(4), pages 596-622, June.
    6. Yen, Yu-Min & Yen, Tso-Jung, 2021. "Testing forecast accuracy of expectiles and quantiles with the extremal consistent loss functions," International Journal of Forecasting, Elsevier, vol. 37(2), pages 733-758.

  12. Francis X. Diebold, 2015. "Comparing Predictive Accuracy, Twenty Years Later: A Personal Perspective on the Use and Abuse of Diebold-Mariano Tests," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(1), pages 1-1, January.
    See citations under working paper version above.
  13. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    See citations under working paper version above.
  14. Francis X. Diebold & Georg Strasser, 2013. "On the Correlation Structure of Microstructure Noise: A Financial Economic Approach," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 80(4), pages 1304-1337.
    See citations under working paper version above.
  15. Chen, Fei & Diebold, Francis X. & Schorfheide, Frank, 2013. "A Markov-switching multifractal inter-trade duration model, with application to US equities," Journal of Econometrics, Elsevier, vol. 177(2), pages 320-342.
    See citations under working paper version above.
  16. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    See citations under working paper version above.
  17. S. Borağan Aruoba & Francis X. Diebold & M. Ayhan Kose & Marco E. Terrones, 2011. "Globalization, the Business Cycle, and Macroeconomic Monitoring," NBER International Seminar on Macroeconomics, University of Chicago Press, vol. 7(1), pages 245-286.
    See citations under working paper version above.
  18. Christensen, Jens H.E. & Diebold, Francis X. & Rudebusch, Glenn D., 2011. "The affine arbitrage-free class of Nelson-Siegel term structure models," Journal of Econometrics, Elsevier, vol. 164(1), pages 4-20, September.
    See citations under working paper version above.
  19. S. Boragan Aruoba & Francis X. Diebold, 2010. "Real-Time Macroeconomic Monitoring: Real Activity, Inflation, and Interactions," American Economic Review, American Economic Association, vol. 100(2), pages 20-24, May.
    See citations under working paper version above.
  20. FrancisX. Diebold & Kamil Yilmaz, 2009. "Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets," Economic Journal, Royal Economic Society, vol. 119(534), pages 158-171, January.
    See citations under working paper version above.
  21. Francis X. Diebold / Kamil Yilmaz, 2009. "Equity Market Spillovers in the Americas," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 12(2), pages 55-65, August.

    Cited by:

    1. Tihana Škrinjarić, 2019. "Time Varying Spillovers between the Online Search Volume and Stock Returns: Case of CESEE Markets," IJFS, MDPI, vol. 7(4), pages 1-30, October.
    2. Asai, Manabu & Brugal, Ivan, 2013. "Forecasting volatility via stock return, range, trading volume and spillover effects: The case of Brazil," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 202-213.
    3. Habibi, Hamidreza & Mohammadi, Hassan, 2022. "Return and volatility spillovers across the Western and MENA countries," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
    4. Prasad, Nalin & Grant, Andrew & Kim, Suk-Joong, 2018. "Time varying volatility indices and their determinants: Evidence from developed and emerging stock markets," International Review of Financial Analysis, Elsevier, vol. 60(C), pages 115-126.
    5. Mauricio Calani C., 2012. "Spillovers of the Credit Default Swap Market," Working Papers Central Bank of Chile 678, Central Bank of Chile.
    6. Iwanicz-Drozdowska, Małgorzata & Rogowicz, Karol & Kurowski, Łukasz & Smaga, Paweł, 2021. "Two decades of contagion effect on stock markets: Which events are more contagious?," Journal of Financial Stability, Elsevier, vol. 55(C).
    7. Favero, Carlo A., 2013. "Modelling and forecasting government bond spreads in the euro area: A GVAR model," Journal of Econometrics, Elsevier, vol. 177(2), pages 343-356.
    8. Bayraci, Selcuk & Demiralay, Sercan, 2013. "Conditional Autoregregressive Range (CARR) Based Volatility Spillover Index For the Eurozone Markets," MPRA Paper 51909, University Library of Munich, Germany.
    9. Arčabić, Vladimir & Škrinjarić, Tihana, 2021. "Sharing is caring: Spillovers and synchronization of business cycles in the European Union," Economic Modelling, Elsevier, vol. 96(C), pages 25-39.
    10. Yavas, Burhan F. & Malladi, Rama K., 2020. "Foreign direct investment and financial markets influences: Results from the United States," The North American Journal of Economics and Finance, Elsevier, vol. 53(C).
    11. Yen-Hsien Lee & Ting-Huei Liao & Ya-Ling Huang & Tzu-Ling Huang, 2015. "Dynamic Spillovers between Oil and Stock Markets: New Approaches at Spillover Index," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 6(2), pages 178-189, April.
    12. Awartani, Basel & Maghyereh, Aktham Issa, 2013. "Dynamic spillovers between oil and stock markets in the Gulf Cooperation Council Countries," Energy Economics, Elsevier, vol. 36(C), pages 28-42.
    13. Lidija Dedi & Burhan F. Yavas, 2016. "Return and volatility spillovers in equity markets: An investigation using various GARCH methodologies," Cogent Economics & Finance, Taylor & Francis Journals, vol. 4(1), pages 1266788-126, December.
    14. Kamil Yilmaz, 2009. "Return and Volatility Spillovers among the East Asian Equity Markets," Koç University-TUSIAD Economic Research Forum Working Papers 0907, Koc University-TUSIAD Economic Research Forum.
    15. Fowowe, Babajide & Shuaibu, Mohammed, 2016. "Dynamic spillovers between Nigerian, South African and international equity markets," International Economics, Elsevier, vol. 148(C), pages 59-80.
    16. Shakya, Shishir & Li, Bingxin & Etienne, Xiaoli, 2022. "Shale revolution, oil and gas prices, and drilling activities in the United States," Energy Economics, Elsevier, vol. 108(C).
    17. Zornitsa Todorova, 2020. "Network Risk in the European Sovereign CDS Market," The Review of Finance and Banking, Academia de Studii Economice din Bucuresti, Romania / Facultatea de Finante, Asigurari, Banci si Burse de Valori / Catedra de Finante, vol. 12(2), pages 137-154, December.
    18. Corradi, Valentina & Distaso, Walter & Fernandes, Marcelo, 2012. "International market links and volatility transmission," Journal of Econometrics, Elsevier, vol. 170(1), pages 117-141.
    19. Mehmet Balcilar & Rangan Gupta & Duc Khuong Nguyen & Mark E. Wohar, 2018. "Causal effects of the United States and Japan on Pacific-Rim stock markets: nonparametric quantile causality approach," Applied Economics, Taylor & Francis Journals, vol. 50(53), pages 5712-5727, November.
    20. Chen, Hongyi & Funke, Michael & Tsang, Andrew, 2016. "The diffusion and dynamics of producer prices, deflationary pressure across Asian countries, and the role of China," BOFIT Discussion Papers 11/2016, Bank of Finland Institute for Emerging Economies (BOFIT).
    21. Tihana Škrinjarić & Zrinka Orlović, 2020. "Economic Policy Uncertainty and Stock Market Spillovers: Case of Selected CEE Markets," Mathematics, MDPI, vol. 8(7), pages 1-33, July.
    22. Panda, Ajaya Kumar & Panda, Pradiptarathi & Nanda, Swagatika & Parad, Atul, 2021. "Information bias and its spillover effect on return volatility: A study on stock markets in the Asia-Pacific region," Pacific-Basin Finance Journal, Elsevier, vol. 69(C).
    23. Yavas, Burhan F. & Dedi, Lidija, 2016. "An investigation of return and volatility linkages among equity markets: A study of selected European and emerging countries," Research in International Business and Finance, Elsevier, vol. 37(C), pages 583-596.
    24. Zheng, Yao & Osmer, Eric, 2021. "Housing price dynamics: The impact of stock market sentiment and the spillover effect," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 854-867.
    25. Zhou, Xiangyi & Zhang, Weijin & Zhang, Jie, 2012. "Volatility spillovers between the Chinese and world equity markets," Pacific-Basin Finance Journal, Elsevier, vol. 20(2), pages 247-270.
    26. Farid, Saqib & Naeem, Muhammad Abubakr & Paltrinieri, Andrea & Nepal, Rabindra, 2022. "Impact of COVID-19 on the quantile connectedness between energy, metals and agriculture commodities," Energy Economics, Elsevier, vol. 109(C).
    27. Zhang, Bing & Wang, Peijie, 2014. "Return and volatility spillovers between china and world oil markets," Economic Modelling, Elsevier, vol. 42(C), pages 413-420.
    28. Luo, Jiawen & Marfatia, Hardik A. & Ji, Qiang & Klein, Tony, 2023. "Co-volatility and asymmetric transmission of risks between the global oil and China's futures markets," Energy Economics, Elsevier, vol. 117(C).
    29. Zhang, Weiping & Zhuang, Xintian & Lu, Yang, 2020. "Spatial spillover effects and risk contagion around G20 stock markets based on volatility network," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    30. Genc, Ismail H., 2022. "Are Indian Subcontinent remittance markets connected to each other?," Journal of Asian Economics, Elsevier, vol. 80(C).

  22. Campbell, Sean D. & Diebold, Francis X., 2009. "Stock Returns and Expected Business Conditions: Half a Century of Direct Evidence," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(2), pages 266-278.
    See citations under working paper version above.
  23. Aruoba, S. BoraÄŸan & Diebold, Francis X. & Scotti, Chiara, 2009. "Real-Time Measurement of Business Conditions," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 417-427.
    See citations under working paper version above.
  24. Jens H. E. Christensen & Francis X. Diebold & Glenn D. Rudebusch, 2009. "An arbitrage-free generalized Nelson--Siegel term structure model," Econometrics Journal, Royal Economic Society, vol. 12(3), pages 33-64, November.
    See citations under working paper version above.
  25. Diebold, Francis X. & Li, Canlin & Yue, Vivian Z., 2008. "Global yield curve dynamics and interactions: A dynamic Nelson-Siegel approach," Journal of Econometrics, Elsevier, vol. 146(2), pages 351-363, October.
    See citations under working paper version above.
  26. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2007. "Roughing It Up: Including Jump Components in the Measurement, Modeling, and Forecasting of Return Volatility," The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 701-720, November.
    See citations under working paper version above.
  27. Andersen, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Vega, Clara, 2007. "Real-time price discovery in global stock, bond and foreign exchange markets," Journal of International Economics, Elsevier, vol. 73(2), pages 251-277, November.
    See citations under working paper version above.
  28. Peter F. Christoffersen & Francis X. Diebold, 2006. "Financial Asset Returns, Direction-of-Change Forecasting, and Volatility Dynamics," Management Science, INFORMS, vol. 52(8), pages 1273-1287, August.
    See citations under working paper version above.
  29. Diebold, Francis X. & Rudebusch, Glenn D. & Borag[caron]an Aruoba, S., 2006. "The macroeconomy and the yield curve: a dynamic latent factor approach," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 309-338.
    See citations under working paper version above.
  30. Diebold, Francis X. & Li, Canlin, 2006. "Forecasting the term structure of government bond yields," Journal of Econometrics, Elsevier, vol. 130(2), pages 337-364, February.
    See citations under working paper version above.
  31. Michael W. Brandt & Francis X. Diebold, 2006. "A No-Arbitrage Approach to Range-Based Estimation of Return Covariances and Correlations," The Journal of Business, University of Chicago Press, vol. 79(1), pages 61-74, January.
    See citations under working paper version above.
  32. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Jin Wu, 2005. "A Framework for Exploring the Macroeconomic Determinants of Systematic Risk," American Economic Review, American Economic Association, vol. 95(2), pages 398-404, May.
    See citations under working paper version above.
  33. Francis X. Diebold & Monika Piazzesi & Glenn D. Rudebusch, 2005. "Modeling Bond Yields in Finance and Macroeconomics," American Economic Review, American Economic Association, vol. 95(2), pages 415-420, May.
    See citations under working paper version above.
  34. Sean D. Campbell & Francis X. Diebold, 2005. "Weather Forecasting for Weather Derivatives," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 6-16, March.
    See citations under working paper version above.
  35. Gene Amromin & Steven A. Sharpe, 2005. "From the horse’s mouth: gauging conditional expected stock returns from investor surveys," Proceedings, Board of Governors of the Federal Reserve System (U.S.).

    Cited by:

    1. Didier, Tatiana & Lowenkron, Alexandre, 2012. "The current account as a dynamic portfolio choice problem," Journal of the Japanese and International Economies, Elsevier, vol. 26(4), pages 518-541.

  36. Francis X. Diebold, 2004. "The Nobel Memorial Prize for Robert F. Engle," Scandinavian Journal of Economics, Wiley Blackwell, vol. 106(2), pages 165-185, June.
    See citations under working paper version above.
  37. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Clara Vega, 2003. "Micro Effects of Macro Announcements: Real-Time Price Discovery in Foreign Exchange," American Economic Review, American Economic Association, vol. 93(1), pages 38-62, March.
    See citations under working paper version above.
  38. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2003. "Modeling and Forecasting Realized Volatility," Econometrica, Econometric Society, vol. 71(2), pages 579-625, March.
    See citations under working paper version above.
  39. Diebold, Francis X., 2003. "The Et Interview: Professor Robert F. Engle, January 2003," Econometric Theory, Cambridge University Press, vol. 19(6), pages 1159-1193, December.

    Cited by:

    1. Peter Hans Matthews, 2004. "Paradise Lost and Found? The Econometric Contributions of Clive W.J. Granger and Robert F. Engle," Middlebury College Working Paper Series 0416, Middlebury College, Department of Economics.
    2. Goutsmedt, Aurélien & Truc, Alexandre, 2023. "An Independent European Macroeconomics? A History of European Macroeconomics through the Lens of the European Economic Review," SocArXiv cn7am, Center for Open Science.
    3. Francis X. Diebold, 2004. "The Nobel Memorial Prize for Robert F. Engle," Scandinavian Journal of Economics, Wiley Blackwell, vol. 106(2), pages 165-185, June.
    4. Degiannakis, Stavros & Livada, Alexandra & Panas, Epaminondas, 2008. "Rolling-sampled parameters of ARCH and Levy-stable models," MPRA Paper 80464, University Library of Munich, Germany.
    5. Shuping Shi & Jun Yu, 2023. "Volatility Puzzle: Long Memory or Antipersistency," Management Science, INFORMS, vol. 69(7), pages 3861-3883, July.
    6. Masih, Mansur & Algahtani, Ibrahim & De Mello, Lurion, 2010. "Price dynamics of crude oil and the regional ethylene markets," Energy Economics, Elsevier, vol. 32(6), pages 1435-1444, November.

  40. Sassan Alizadeh & Michael W. Brandt & Francis X. Diebold, 2002. "Range‐Based Estimation of Stochastic Volatility Models," Journal of Finance, American Finance Association, vol. 57(3), pages 1047-1091, June.

    Cited by:

    1. Hau, Harald, 2002. "The Role of Transaction Costs for Financial Volatility: Evidence from the Paris Bourse," CEPR Discussion Papers 3651, C.E.P.R. Discussion Papers.
    2. Phuong Pham, Thu & Joakim Westerholm, P., 2013. "An international trend in market design: Endogenous effects of limit order book transparency on volatility, spreads, depth and volume," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 27(C), pages 202-223.
    3. Narayan, Paresh Kumar & Mishra, Sagarika & Sharma, Susan Sunila & Liu, Ruipeng, 2013. "Determinants of stock price bubbles," Working Papers fe_2013_06, Deakin University, Department of Economics.
    4. Suraj Kumar & Krishna Prasanna, 2019. "Global Financial Crisis: Dynamics of Liquidity Risk in Emerging Asia," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 18(3), pages 339-362, December.
    5. Yin-Wong Cheung, 2007. "An empirical model of daily highs and lows," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 12(1), pages 1-20.
    6. Petri Kyröläinen, 2008. "Day trading and stock price volatility," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 32(1), pages 75-89, January.
    7. Li, Hongquan & Hong, Yongmiao, 2011. "Financial volatility forecasting with range-based autoregressive volatility model," Finance Research Letters, Elsevier, vol. 8(2), pages 69-76, June.
    8. Uwe Helmes & Julia Henker & Thomas Henker & Tom Smith, 2017. "Effect of the ban on short selling on market prices and volatility," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 57(3), pages 727-757, September.
    9. Alicia Garcia-Herrero & Eric Girardin, 2013. "China's Monetary Policy Communication: Money Markets not only Listen, They also Understand," Working Papers 022013, Hong Kong Institute for Monetary Research.
    10. Hendershott, Terrence & Moulton, Pamela C., 2011. "Automation, speed, and stock market quality: The NYSE's Hybrid," Journal of Financial Markets, Elsevier, vol. 14(4), pages 568-604, November.
    11. Yuta Kurose, 2021. "Stochastic volatility model with range-based correction and leverage," Papers 2110.00039, arXiv.org, revised Oct 2021.
    12. Mert Demirer & Francis X. Diebold & Laura Liu & Kamil Yilmaz, 2015. "Estimating Global Bank Network Connectedness," PIER Working Paper Archive 15-025, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 25 Jul 2015.
    13. Junni L. Zhang & Wolfgang Karl Hardle & Cathy Y. Chen & Elisabeth Bommes, 2020. "Distillation of News Flow into Analysis of Stock Reactions," Papers 2009.10392, arXiv.org.
    14. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
    15. Matteo Barigozzi & Christian Brownlees, 2013. "Nets: Network Estimation for Time Series," Working Papers 723, Barcelona School of Economics.
    16. Manabu Asai & Michael McAleer, 2013. "Leverage and Feedback Effects on Multifactor Wishart Stochastic Volatility for Option Pricing," KIER Working Papers 840, Kyoto University, Institute of Economic Research.
    17. Cathy W. S. Chen & Richard Gerlach & Bruce B. K. Hwang & Michael McAleer, 2011. "Forecasting Value-at-Risk Using Nonlinear Regression Quantiles and the Intra-day Range," KIER Working Papers 775, Kyoto University, Institute of Economic Research.
    18. Fabrizio Cipollini & Giampiero M. Gallo & Edoardo Otranto, 2019. "Realized Volatility Forecasting: Robustness to Measurement Errors," Econometrics Working Papers Archive 2019_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    19. Chris Bardgett & Elise Gourier & Markus Leippold, 2016. "Inferring Volatility Dynamics and Risk Premia from the S&P 500 and VIX markets," Working Papers 780, Queen Mary University of London, School of Economics and Finance.
    20. Matteo Luciani & David Veredas, 2012. "A model for vast panels of volatilities," Working Papers 1230, Banco de España.
    21. Kumar, Dilip, 2015. "Sudden changes in extreme value volatility estimator: Modeling and forecasting with economic significance analysis," Economic Modelling, Elsevier, vol. 49(C), pages 354-371.
    22. Luca Rossi, 2020. "Indicators of uncertainty: a brief user’s guide," Questioni di Economia e Finanza (Occasional Papers) 564, Bank of Italy, Economic Research and International Relations Area.
    23. Dilip Kumar, 2016. "Sudden changes in crude oil price volatility: an application of extreme value volatility estimator," American Journal of Finance and Accounting, Inderscience Enterprises Ltd, vol. 4(3/4), pages 215-234.
    24. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2002. "Parametric and Nonparametric Volatility Measurement," Center for Financial Institutions Working Papers 02-27, Wharton School Center for Financial Institutions, University of Pennsylvania.
    25. Miao, Ke & Phillips, Peter C.B. & Su, Liangjun, 2023. "High-dimensional VARs with common factors," Journal of Econometrics, Elsevier, vol. 233(1), pages 155-183.
    26. Alfred Lehar & Christine Parlour & Marius Zoican, 2023. "Fragmentation and optimal liquidity supply on decentralized exchanges," Papers 2307.13772, arXiv.org, revised Feb 2024.
    27. Lazar, Emese & Xue, Xiaohan, 2020. "Forecasting risk measures using intraday data in a generalized autoregressive score framework," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1057-1072.
    28. Bertrand Maillet & Jean-Philippe Médecin & Thierry Michel, 2009. "High Watermarks of Market Risks," Post-Print halshs-00425585, HAL.
    29. Bin Gu & Prabhudev Konana & Rajagopal Raghunathan & Hsuanwei Michelle Chen, 2014. "Research Note —The Allure of Homophily in Social Media: Evidence from Investor Responses on Virtual Communities," Information Systems Research, INFORMS, vol. 25(3), pages 604-617, September.
    30. Degiannakis, Stavros & Xekalaki, Evdokia, 2007. "Assessing the Performance of a Prediction Error Criterion Model Selection Algorithm in the Context of ARCH Models," MPRA Paper 96324, University Library of Munich, Germany.
    31. Zheng, Tingguo & Zuo, Haomiao, 2013. "Reexamining the time-varying volatility spillover effects: A Markov switching causality approach," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 643-662.
    32. Diebold, Francis X. & Yilmaz, Kamil, 2015. "Financial and Macroeconomic Connectedness: A Network Approach to Measurement and Monitoring," OUP Catalogue, Oxford University Press, number 9780199338306.
    33. Gustavo Peralta, 2016. "The Nature of Volatility Spillovers across the International Capital Markets," CNMV Working Papers CNMV Working Papers no. 6, CNMV- Spanish Securities Markets Commission - Research and Statistics Department.
    34. Arısoy, Yakup Eser & Altay-Salih, Aslıhan & Akdeniz, Levent, 2015. "Aggregate volatility expectations and threshold CAPM," The North American Journal of Economics and Finance, Elsevier, vol. 34(C), pages 231-253.
    35. Asai, Manabu & Brugal, Ivan, 2013. "Forecasting volatility via stock return, range, trading volume and spillover effects: The case of Brazil," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 202-213.
    36. Francis X. Diebold / Kamil Yilmaz, 2009. "Equity Market Spillovers in the Americas," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 12(2), pages 55-65, August.
    37. Naomi Boyd & Bingxin Li & Rui Liu, 2022. "Risk premia in the term structure of crude oil futures: long-run and short-run volatility components," Review of Quantitative Finance and Accounting, Springer, vol. 58(4), pages 1505-1533, May.
    38. Michael W. Brandt & Francis X. Diebold, 2006. "A No-Arbitrage Approach to Range-Based Estimation of Return Covariances and Correlations," The Journal of Business, University of Chicago Press, vol. 79(1), pages 61-74, January.
    39. Degiannakis, Stavros & Livada, Alexandra, 2013. "Realized Volatility or Price Range: Evidence from a discrete simulation of the continuous time diffusion process," MPRA Paper 80489, University Library of Munich, Germany.
    40. Chang, Chuang-Chang & Hsieh, Pei-Fang & Wang, Yaw-Huei, 2010. "Information content of options trading volume for future volatility: Evidence from the Taiwan options market," Journal of Banking & Finance, Elsevier, vol. 34(1), pages 174-183, January.
    41. Habibi, Hamidreza & Mohammadi, Hassan, 2022. "Return and volatility spillovers across the Western and MENA countries," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
    42. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005. "Practical Volatility and Correlation Modeling for Financial Market Risk Management," PIER Working Paper Archive 05-007, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
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    1. Allen, P. Geoffrey & Morzuch, Bernard J., 2006. "Twenty-five years of progress, problems, and conflicting evidence in econometric forecasting. What about the next 25 years?," International Journal of Forecasting, Elsevier, vol. 22(3), pages 475-492.
    2. Taylor, James W., 2004. "Volatility forecasting with smooth transition exponential smoothing," International Journal of Forecasting, Elsevier, vol. 20(2), pages 273-286.

  44. Andersen T. G & Bollerslev T. & Diebold F. X & Labys P., 2001. "The Distribution of Realized Exchange Rate Volatility," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 42-55, March.

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    1. Eric Hillebrand & Gunther Schnabl & Yasemin Ulu, 2006. "Japanese Foreign Exchange Intervention and the Yen/Dollar Exchange Rate: A Simultaneous Equations Approach Using Realized Volatility," CESifo Working Paper Series 1766, CESifo.
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    3. Per Frederiksen & Morten Orregaard Nielsen, 2008. "Bias-Reduced Estimation of Long-Memory Stochastic Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 6(4), pages 496-512, Fall.
    4. Takaishi, Tetsuya, 2018. "Bias correction in the realized stochastic volatility model for daily volatility on the Tokyo Stock Exchange," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 500(C), pages 139-154.
    5. Wu, Zhen-Xing & Gau, Yin-Feng, 2022. "Informativeness of trades around macroeconomic announcements in the foreign exchange market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 78(C).
    6. Audrino, Francesco & Fengler, Matthias, 2013. "Are classical option pricing models consistent with observed option second-order moments? Evidence from high-frequency data," Economics Working Paper Series 1311, University of St. Gallen, School of Economics and Political Science.
    7. Nielsen, Morten Ørregaard & Frederiksen, Per, 2008. "Finite sample accuracy and choice of sampling frequency in integrated volatility estimation," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 265-286, March.
    8. Chen, Xiaohong & Hansen, Lars Peter & Carrasco, Marine, 2008. "Nonlinearity and Temporal Dependence," Working Papers 48, Yale University, Department of Economics.
    9. Ralf Becker & Adam Clements, 2007. "Are combination forecasts of S&P 500 volatility statistically superior?," NCER Working Paper Series 17, National Centre for Econometric Research.
    10. Adam Clements & Yin Liao, 2014. "The role in index jumps and cojumps in forecasting stock index volatility: Evidence from the Dow Jones index," NCER Working Paper Series 101, National Centre for Econometric Research.
    11. Mattiussi, V. & Iori, G., 2006. "Currency futures volatility during the 1997 East Asian crisis: an application of Fourier analysis," Working Papers 06/09, Department of Economics, City University London.
    12. Morten Ø. Nielsen & Per Houmann Frederiksen, 2005. "Finite Sample Comparison Of Parametric, Semiparametric, And Wavelet Estimators Of Fractional Integration," Working Paper 1189, Economics Department, Queen's University.
    13. Degiannakis, Stavros & Floros, Christos, 2014. "Intra-Day Realized Volatility for European and USA Stock Indices," MPRA Paper 64940, University Library of Munich, Germany, revised Jan 2015.
    14. Pawel Janus & Siem Jan Koopman & André Lucas, 2011. "Long Memory Dynamics for Multivariate Dependence under Heavy Tails," Tinbergen Institute Discussion Papers 11-175/2/DSF28, Tinbergen Institute.
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    16. Chen, Richard Y. & Mykland, Per A., 2017. "Model-free approaches to discern non-stationary microstructure noise and time-varying liquidity in high-frequency data," Journal of Econometrics, Elsevier, vol. 200(1), pages 79-103.
    17. Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2019. "Forecasting Realized Oil-Price Volatility: The Role of Financial Stress and Asymmetric Loss," Working Papers 201903, University of Pretoria, Department of Economics.
    18. Beyer, Deborah B. & Fan, Zaifeng S., 2023. "The calming effects of conflict: The impact of partisan conflict on market volatility," International Review of Financial Analysis, Elsevier, vol. 85(C).
    19. Woerner Jeannette H. C., 2003. "Variational sums and power variation: a unifying approach to model selection and estimation in semimartingale models," Statistics & Risk Modeling, De Gruyter, vol. 21(1/2003), pages 47-68, January.
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    21. Degiannakis, Stavros & Floros, Christos, 2013. "Modeling CAC40 volatility using ultra-high frequency data," Research in International Business and Finance, Elsevier, vol. 28(C), pages 68-81.
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    866. Pascual, Lorenzo & Romo, Juan & Ruiz, Esther, 2006. "Bootstrap prediction for returns and volatilities in GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 50(9), pages 2293-2312, May.
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    868. Kumar, Satish & Trück, Stefan, 2014. "Unbiasedness and risk premiums in the Indian currency futures market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 29(C), pages 13-32.
    869. Zhang, Yiting & Lee, Gladys Hui Ting & Wong, Jian Cheng & Kok, Jun Liang & Prusty, Manamohan & Cheong, Siew Ann, 2011. "Will the US economy recover in 2010? A minimal spanning tree study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(11), pages 2020-2050.
    870. Haugom, Erik & Lien, Gudbrand & Veka, Steinar & Westgaard, Sjur, 2014. "Covariance estimation using high-frequency data: Sensitivities of estimation methods," Economic Modelling, Elsevier, vol. 43(C), pages 416-425.
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    874. Chen, Ying & Härdle, Wolfgang & Spokoiny, Vladimir, 2010. "GHICA -- Risk analysis with GH distributions and independent components," Journal of Empirical Finance, Elsevier, vol. 17(2), pages 255-269, March.
    875. Yu‐Sheng Lai, 2023. "Optimal futures hedging by using realized semicovariances: The information contained in signed high‐frequency returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(5), pages 677-701, May.
    876. Chen, Haiqiang & Gu, Ming & Ni, Bo, 2023. "How price limit affects the market efficiency in a short-sale constrained market? Evidence from a quasi-natural experiment," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 22-39.
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  45. Francis X. Diebold & Glenn D. Rudebusch, 2001. "Five questions about business cycles," Economic Review, Federal Reserve Bank of San Francisco, pages 1-15.

    Cited by:

    1. Harding, Don, 2008. "Detecting and forecasting business cycle turning points," MPRA Paper 33583, University Library of Munich, Germany.
    2. Thierry Aimar & Francis Bismans & Claude Diebolt, 2010. "Le cycle économique : une synthèse," Revue Française d'Économie, Programme National Persée, vol. 24(4), pages 3-65.
    3. Thierry Aimar & Francis Bismans & Claude Diebolt, 2012. "Economic Cycles: A Synthesis," Working Papers 12-11, Association Française de Cliométrie (AFC).
    4. Viv. B Hall & McDermott C. John, 2004. "Regional Business Cycles in New Zealand: Do they exist? What might drive them?," ERSA conference papers ersa04p200, European Regional Science Association.
    5. Filis, George, 2010. "Macro economy, stock market and oil prices: Do meaningful relationships exist among their cyclical fluctuations?," Energy Economics, Elsevier, vol. 32(4), pages 877-886, July.
    6. Kalli, Maria & Griffin, Jim E., 2018. "Bayesian nonparametric vector autoregressive models," Journal of Econometrics, Elsevier, vol. 203(2), pages 267-282.
    7. Peiro, Amado, 2005. "Economic comovements in European countries," Journal of Policy Modeling, Elsevier, vol. 27(5), pages 575-584, July.
    8. Juergen Bierbaumer-Polly, 2012. "Regional and Sectoral Business Cycles - Key Features for the Austrian economy," EcoMod2012 4074, EcoMod.
    9. Sergey Smirnov, 2011. "Those Unpredictable Recessions," HSE Working papers WP BRP 02/EC/2011, National Research University Higher School of Economics.
    10. Prakash Loungani & Bharat Trehan, 2002. "Predicting when the economy will turn," FRBSF Economic Letter, Federal Reserve Bank of San Francisco, issue mar15.
    11. Robert Krol & Shirley Svorny, 2007. "Budget Rules and State Business Cycles," Public Finance Review, , vol. 35(4), pages 530-544, July.
    12. Aleksandra Gaweł, 2004. "The Business Cycle Dependent Fluctuation of Employment in Sectors in Polish Economy," Ekonomia journal, Faculty of Economic Sciences, University of Warsaw, vol. 12.

  46. Andersen, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Ebens, Heiko, 2001. "The distribution of realized stock return volatility," Journal of Financial Economics, Elsevier, vol. 61(1), pages 43-76, July.

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    1. Eric Hillebrand & Gunther Schnabl & Yasemin Ulu, 2006. "Japanese Foreign Exchange Intervention and the Yen/Dollar Exchange Rate: A Simultaneous Equations Approach Using Realized Volatility," CESifo Working Paper Series 1766, CESifo.
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    5. Audrino, Francesco & Fengler, Matthias, 2013. "Are classical option pricing models consistent with observed option second-order moments? Evidence from high-frequency data," Economics Working Paper Series 1311, University of St. Gallen, School of Economics and Political Science.
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    7. Nielsen, Morten Ørregaard & Frederiksen, Per, 2008. "Finite sample accuracy and choice of sampling frequency in integrated volatility estimation," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 265-286, March.
    8. Tim Bollerslev & Michael Gibson & Hao Zhou, 2007. "Dynamic Estimation of Volatility Risk Premia and Investor Risk Aversion from Option-Implied and Realized Volatilities," CREATES Research Papers 2007-16, Department of Economics and Business Economics, Aarhus University.
    9. Gu, Chen & Kurov, Alexander & Wolfe, Marketa Halova, 2018. "Relief Rallies after FOMC Announcements as a Resolution of Uncertainty," Journal of Empirical Finance, Elsevier, vol. 49(C), pages 1-18.
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    12. Manabu Asai & Michael McAleer & Marcelo C. Medeiros, 2011. "Modelling and Forecasting Noisy Realized Volatility," KIER Working Papers 758, Kyoto University, Institute of Economic Research.
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    22. Olkhov, Victor, 2021. "Three Remarks On Asset Pricing," MPRA Paper 109238, University Library of Munich, Germany.
    23. Alicia Garcia-Herrero & Eric Girardin, 2013. "China's Monetary Policy Communication: Money Markets not only Listen, They also Understand," Working Papers 022013, Hong Kong Institute for Monetary Research.
    24. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2000. "Exchange Rate Returns Standardized by Realized Volatility are (Nearly) Gaussian," NBER Working Papers 7488, National Bureau of Economic Research, Inc.
    25. Zhongjun Qu, 2010. "A Test Against Spurious Long Memory," Boston University - Department of Economics - Working Papers Series WP2010-051, Boston University - Department of Economics.
    26. Xekalaki, Evdokia & Degiannakis, Stavros, 2005. "Evaluating volatility forecasts in option pricing in the context of a simulated options market," Computational Statistics & Data Analysis, Elsevier, vol. 49(2), pages 611-629, April.
    27. Tim Bollerslev & Uta Kretschmer & Christian Pigorsch & George Tauchen, 2010. "A Discrete-Time Model for Daily S&P500 Returns and Realized Variations: Jumps and Leverage Effects," Working Papers 10-06, Duke University, Department of Economics.
    28. Hung, Jui-Cheng & Liu, Hung-Chun & Yang, J. Jimmy, 2020. "Improving the realized GARCH’s volatility forecast for Bitcoin with jump-robust estimators," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
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    30. Sourafel Girma & Sandra Lancheros & Alejandro Riaño, 2015. "Global Engagement and Returns Volatility," CESifo Working Paper Series 5650, CESifo.
    31. Thijs Benschop & Brenda López Cabrera, 2017. "Realized volatility of CO2 futures," SFB 649 Discussion Papers SFB649DP2017-025, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    32. Kim Christensen & Mathias Siggaard & Bezirgen Veliyev, 2021. "A machine learning approach to volatility forecasting," CREATES Research Papers 2021-03, Department of Economics and Business Economics, Aarhus University.
    33. Charoenwong, Charlie & Ding, David K. & Wang, Ping, 2013. "Short sales constraint and SEO pricing," International Review of Financial Analysis, Elsevier, vol. 29(C), pages 107-118.
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    1. Niyibizi, Bart & Brorsen, Wade & Park, Eunchun, 2018. "Using Bayesian Kriging for Spatial Smoothing of Trends in the Means and Variances of Crop Yield Densities," 2018 Annual Meeting, August 5-7, Washington, D.C. 274403, Agricultural and Applied Economics Association.
    2. Thi Huyen Tran & Robert Ślepaczuk, 2022. "Quantile regression analysis to predict GDP distribution using data from the US and UK," Working Papers 2022-30, Faculty of Economic Sciences, University of Warsaw.
    3. Felix Wick & Ulrich Kerzel & Martin Hahn & Moritz Wolf & Trapti Singhal & Daniel Stemmer & Jakob Ernst & Michael Feindt, 2021. "Demand Forecasting of Individual Probability Density Functions with Machine Learning," SN Operations Research Forum, Springer, vol. 2(3), pages 1-39, September.
    4. Bratu, Mihaela, 2013. "The Assessment And Improvement Of The Accuracy For The Forecast Intervals," Working Papers of Macroeconomic Modelling Seminar 132602, Institute for Economic Forecasting.
    5. TAKEDA Yosuke, 2014. "Quantifying the Beauty Contest: Density Inflation-Forecasts of Professional Japanese Forecasters," ESRI Discussion paper series 309, Economic and Social Research Institute (ESRI).

  54. Christoffersen, Peter F & Diebold, Francis X, 1998. "Cointegration and Long-Horizon Forecasting," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(4), pages 450-458, October.
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  55. Francis X. Diebold & Lee E. Ohanian & Jeremy Berkowitz, 1998. "Dynamic Equilibrium Economies: A Framework for Comparing Models and Data," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(3), pages 433-451.
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    1. Jeremy Berkowitz & Lutz Kilian, 2000. "Recent developments in bootstrapping time series," Econometric Reviews, Taylor & Francis Journals, vol. 19(1), pages 1-48.
    2. Assenmacher-Wesche, Katrin & Gerlach, Stefan, 2008. "Money growth, output gaps and inflation at low and high frequency: Spectral estimates for Switzerland," Journal of Economic Dynamics and Control, Elsevier, vol. 32(2), pages 411-435, February.
    3. Schüler, Yves S. & Hiebert, Paul P. & Peltonen, Tuomas A., 2020. "Financial cycles: Characterisation and real-time measurement," Journal of International Money and Finance, Elsevier, vol. 100(C).
    4. Lovcha, Yuliya & Pérez Laborda, Àlex, 2013. "Hours worked - Productivity puzzle: identification in fractional integration settings," Working Papers 2072/211796, Universitat Rovira i Virgili, Department of Economics.
    5. Benati, Luca & Goodhart, Charles, 2007. "Investigating time-variation in the marginal predictive power of the yield spread," Working Paper Series 802, European Central Bank.
    6. Luca Benati, 2018. "Money and Credit: A Long-Term View," Diskussionsschriften dp1811, Universitaet Bern, Departement Volkswirtschaft.
    7. Lovcha, Yuliya & Perez-Laborda, Alejandro, 2018. "Monetary policy shocks, inflation persistence, and long memory," Journal of Macroeconomics, Elsevier, vol. 55(C), pages 117-127.
    8. Francis X. Diebold & Lee E. Ohanian & Jeremy Berkowitz, 1995. "Dynamic Equilibrium Economies: A Framework for Comparing Models and Data," NBER Technical Working Papers 0174, National Bureau of Economic Research, Inc.
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    11. Lovcha, Yuliya & Pérez Laborda, Àlex, 2016. "Structural shocks and dinamic elasticities in a long memory model of the US gasoline retail market," Working Papers 2072/261538, Universitat Rovira i Virgili, Department of Economics.
    12. Lovcha, Yuliya & Pérez Laborda, Alejandro, 2016. "Frequency-Domain Estimation as an Alternative to Pre-Filtering External Cycles in Structural VAR Analysis," Working Papers 2072/290743, Universitat Rovira i Virgili, Department of Economics.
    13. Christiane Baumeister & Luca Benati, 2012. "Unconventional Monetary Policy and the Great Recession: Estimating the Macroeconomic Effects of a Spread Compression at the Zero Lower Bound," Staff Working Papers 12-21, Bank of Canada.
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    18. Adam Cagliarini & Fiona Price, 2017. "Exploring the Link between the Macroeconomic and Financial Cycles," RBA Annual Conference Volume (Discontinued), in: Jonathan Hambur & John Simon (ed.),Monetary Policy and Financial Stability in a World of Low Interest Rates, Reserve Bank of Australia.
    19. Benati, Luca & Mumtaz, Haroon, 2007. "U.S. evolving macroeconomic dynamics: a structural investigation," Working Paper Series 746, European Central Bank.
    20. Benati, Luca, 2009. "Long run evidence on money growth and inflation," Working Paper Series 1027, European Central Bank.
    21. Yuliya Lovcha & Alejandro Perez-Laborda & Luis Gil-Alana, 2018. "On the invertibility of seasonally adjusted series," Computational Statistics, Springer, vol. 33(1), pages 443-465, March.
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    26. Luca Benati & Peter N. Ireland, 2017. "Money-Multiplier Shocks," Boston College Working Papers in Economics 933, Boston College Department of Economics.
    27. Hangyong Lee and Jin Lee, 2019. "Inflation Co-Movement in the ASEAN Countries," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 44(4), pages 135-152, December.
    28. Gonzalo Camba-Mendez & George Kapetanios, 2005. "Statistical Tests of the Rank of a Matrix and Their Applications in Econometric Modelling," Working Papers 541, Queen Mary University of London, School of Economics and Finance.
    29. Bollerslev, Tim & Wright, Jonathan H., 2000. "Semiparametric estimation of long-memory volatility dependencies: The role of high-frequency data," Journal of Econometrics, Elsevier, vol. 98(1), pages 81-106, September.

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    1. Leopoldo Catania & Nima Nonejad, 2016. "Density Forecasts and the Leverage Effect: Some Evidence from Observation and Parameter-Driven Volatility Models," Papers 1605.00230, arXiv.org, revised Nov 2016.
    2. Clements, Michael P., 2008. "Explanations of the inconsistencies in survey respondents'forecasts," The Warwick Economics Research Paper Series (TWERPS) 870, University of Warwick, Department of Economics.
    3. Gergely Ganics & Barbara Rossi & Tatevik Sekhposyan, 2019. "From fixed-event to fixed-horizon density forecasts: Obtaining measures of multi-horizon uncertainty from survey density forecasts," Economics Working Papers 1689, Department of Economics and Business, Universitat Pompeu Fabra.
    4. Lee, Tae-Hwy & Long, Xiangdong, 2009. "Copula-based multivariate GARCH model with uncorrelated dependent errors," Journal of Econometrics, Elsevier, vol. 150(2), pages 207-218, June.
    5. Markku Lanne, 2009. "Properties of Market-Based and Survey Macroeconomic Forecasts for Different Data Releases," Economics Bulletin, AccessEcon, vol. 29(3), pages 2231-2240.
    6. Delle Monache, Davide & Petrella, Ivan, 2017. "Adaptive models and heavy tails with an application to inflation forecasting," International Journal of Forecasting, Elsevier, vol. 33(2), pages 482-501.
    7. Memmel, Christoph & Wehn, Carsten, 2005. "The supervisor's portfolio: the market price risk of German banks from 2001 to 2003 - Analysis and models for risk aggregation," Discussion Paper Series 2: Banking and Financial Studies 2005,02, Deutsche Bundesbank.
    8. Fildes, Robert & Stekler, Herman, 2002. "The state of macroeconomic forecasting," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 435-468, December.
    9. Luc Bauwens & Pierre Giot & Joachim Grammig & David Veredas, 2000. "A Comparison of Financial Duration Models via Density Forecasts," Econometric Society World Congress 2000 Contributed Papers 0810, Econometric Society.
    10. Charles Goodhart & Miguel Segoviano, 2009. "Banking Stability Measures," FMG Discussion Papers dp627, Financial Markets Group.
    11. Hendry, David F. & Clements, Michael P., 2003. "Economic forecasting: some lessons from recent research," Economic Modelling, Elsevier, vol. 20(2), pages 301-329, March.
    12. Clive G. Bowsher, 2005. "Modelling Security Market Events in Continuous Time: Intensity Based, Multivariate Point Process Models," Economics Papers 2005-W26, Economics Group, Nuffield College, University of Oxford.
    13. Ivanova, Vesela & Puigvert Gutiérrez, Josep Maria, 2014. "Interest rate forecasts, state price densities and risk premium from Euribor options," Journal of Banking & Finance, Elsevier, vol. 48(C), pages 210-223.
    14. Antonello D'Agostino & Domenico Giannone & Michele Lenza & Michele Modugno, 2015. "Nowcasting Business Cycles: a Bayesian Approach to Dynamic Heterogeneous Factor Models," Finance and Economics Discussion Series 2015-66, Board of Governors of the Federal Reserve System (U.S.).
    15. Campbell, Sean D. & Diebold, Francis X., 2004. "Weather forecasting for weather derivatives," CFS Working Paper Series 2004/10, Center for Financial Studies (CFS).
    16. Thijs Benschopa & Brenda López Cabrera, 2014. "Volatility Modelling of CO2 Emission Allowance Spot Prices with Regime-Switching GARCH Models," SFB 649 Discussion Papers SFB649DP2014-050, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    17. Gian Luigi Mazzi & James Mitchell & Gaetana Montana, 2014. "Density Nowcasts and Model Combination: Nowcasting Euro-Area GDP Growth over the 2008–09 Recession," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(2), pages 233-256, April.
    18. Li, Xiao-Ming & Rose, Lawrence C., 2009. "The tail risk of emerging stock markets," Emerging Markets Review, Elsevier, vol. 10(4), pages 242-256, December.
    19. Degiannakis, Stavros & Floros, Christos, 2013. "Modeling CAC40 volatility using ultra-high frequency data," Research in International Business and Finance, Elsevier, vol. 28(C), pages 68-81.
    20. Niguez, Trino-Manuel & Perote, Javier, 2004. "Forecasting the density of asset returns," LSE Research Online Documents on Economics 6845, London School of Economics and Political Science, LSE Library.
    21. GIOT, Pierre & PETITJEAN, Mikael, 2005. "Dynamic asset allocation between stocks and bonds using the Bond-Equity Yield Ratio," LIDAM Discussion Papers CORE 2005010, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    22. Dr Silvia Lui & Dr Martin Weale & Dr. James Mitchell, 2009. "The utility of expectational data: Firm-level evidence using matched qualitative-quantitative UK surveys," National Institute of Economic and Social Research (NIESR) Discussion Papers 343, National Institute of Economic and Social Research.
    23. Philippe J. Deschamps, 2008. "Comparing smooth transition and Markov switching autoregressive models of US unemployment," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(4), pages 435-462.
    24. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2000. "Exchange Rate Returns Standardized by Realized Volatility are (Nearly) Gaussian," NBER Working Papers 7488, National Bureau of Economic Research, Inc.
    25. Tim Bollerslev & Uta Kretschmer & Christian Pigorsch & George Tauchen, 2010. "A Discrete-Time Model for Daily S&P500 Returns and Realized Variations: Jumps and Leverage Effects," Working Papers 10-06, Duke University, Department of Economics.
    26. Rossi, Barbara & Sekhposyan, Tatevik, 2013. "Conditional predictive density evaluation in the presence of instabilities," Journal of Econometrics, Elsevier, vol. 177(2), pages 199-212.
    27. Markus Heinrich & Magnus Reif, 2018. "Forecasting using mixed-frequency VARs with time-varying parameters," ifo Working Paper Series 273, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    28. Ross Askanazi & Francis X. Diebold & Frank Schorfheide & Minchul Shin, 2018. "On the Comparison of Interval Forecasts," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(6), pages 953-965, November.
    29. Cortes, Fabio & Lindner, Peter & Malik, Sheheryar & Segoviano, Miguel, 2018. "A comprehensive multi-sector tool for analysis of Systemic Risk and Interconnectedness (SyRIN)," LSE Research Online Documents on Economics 118928, London School of Economics and Political Science, LSE Library.
    30. Clements, Michael P., 2014. "Probability distributions or point predictions? Survey forecasts of US output growth and inflation," International Journal of Forecasting, Elsevier, vol. 30(1), pages 99-117.
    31. Hua, Zhongsheng & Zhang, Bin, 2008. "Improving density forecast by modeling asymmetric features: An application to S&P500 returns," European Journal of Operational Research, Elsevier, vol. 185(2), pages 716-725, March.
    32. Wolters, Maik H., 2013. "Evaluating point and density forecasts of DSGE models," Economics Working Papers 2013-03, Christian-Albrechts-University of Kiel, Department of Economics.
    33. Francesco Ravazzolo & Shaun P. Vahey, 2010. "Forecast densities for economic aggregates from disaggregate ensembles," Working Paper 2010/02, Norges Bank.
    34. HEINEN, Andréas & RENGIFO, Erick, 2004. "Multivariate reduced rank regression in non-Gaussian contexts, using copulas," LIDAM Discussion Papers CORE 2004032, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    35. Laura Liu, 2020. "Density Forecasts in Panel Data Models: A Semiparametric Bayesian Perspective," CAEPR Working Papers 2020-003, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
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    583. Lan Bai & Xiafei Li & Yu Wei & Guiwu Wei, 2022. "Does crude oil futures price really help to predict spot oil price? New evidence from density forecasting," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 3694-3712, July.
    584. Roberta Cardani & Alessia Paccagnini & Stefania Villa, 2015. "Forecasting in a DSGE Model with Banking Intermediation: Evidence from the US," Working Papers 292, University of Milano-Bicocca, Department of Economics, revised Feb 2015.
    585. Rémillard, Bruno & Papageorgiou, Nicolas & Soustra, Frédéric, 2012. "Copula-based semiparametric models for multivariate time series," Journal of Multivariate Analysis, Elsevier, vol. 110(C), pages 30-42.
    586. Azam, Kazim, 2014. "Dependence Analysis between Foreign Exchange Rates: A Semi-Parametric Copula Approach," The Warwick Economics Research Paper Series (TWERPS) 1052, University of Warwick, Department of Economics.
    587. Anthony Garratt & Ivan Petrella, 2022. "Commodity prices and inflation risk," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(2), pages 392-414, March.
    588. Segoviano, Miguel & Espinoza, Raphael, 2017. "Consistent measures of systemic risk," LSE Research Online Documents on Economics 118947, London School of Economics and Political Science, LSE Library.
    589. Tim Oliver Berg & Steffen Henzel, 2014. "Point and Density Forecasts for the Euro Area Using Bayesian VARs," CESifo Working Paper Series 4711, CESifo.
    590. Egorov, Alexei V. & Hong, Yongmiao & Li, Haitao, 2006. "Validating forecasts of the joint probability density of bond yields: Can affine models beat random walk?," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 255-284.
    591. Polanski, Arnold & Stoja, Evarist & Zhang, Ren, 2013. "Multidimensional risk and risk dependence," Journal of Banking & Finance, Elsevier, vol. 37(8), pages 3286-3294.
    592. Kaeck, Andreas & Rodrigues, Paulo & Seeger, Norman J., 2018. "Model Complexity and Out-of-Sample Performance: Evidence from S&P 500 Index Returns," Journal of Economic Dynamics and Control, Elsevier, vol. 90(C), pages 1-29.
    593. Caraiani, Petre, 2016. "The role of money in DSGE models: a forecasting perspective," Journal of Macroeconomics, Elsevier, vol. 47(PB), pages 315-330.
    594. Ganggang Xu & Marc G. Genton, 2017. "Tukey -and- Random Fields," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(519), pages 1236-1249, July.
    595. Miguel Segoviano, 2006. "Conditional Probabilty of Default Methodolgy," FMG Discussion Papers dp558, Financial Markets Group.
    596. Sebastian Ankargren & Måns Unosson & Yukai Yang, 2018. "A mixed-frequency Bayesian vector autoregression with a steady-state prior," CREATES Research Papers 2018-32, Department of Economics and Business Economics, Aarhus University.
    597. Jalal, Amine & Rockinger, Michael, 2008. "Predicting tail-related risk measures: The consequences of using GARCH filters for non-GARCH data," Journal of Empirical Finance, Elsevier, vol. 15(5), pages 868-877, December.
    598. Fabian Krüger & Sebastian Lerch & Thordis Thorarinsdottir & Tilmann Gneiting, 2021. "Predictive Inference Based on Markov Chain Monte Carlo Output," International Statistical Review, International Statistical Institute, vol. 89(2), pages 274-301, August.
    599. Kohns, David & Potjagailo, Galina, 2023. "Flexible Bayesian MIDAS: time‑variation, group‑shrinkage and sparsity," Bank of England working papers 1025, Bank of England.
    600. Francisco Alonso & Roberto Blanco & Gonzalo Rubio, 2006. "Option-implied preferences adjustments, density forecasts, and the equity risk premium," Working Papers 0630, Banco de España.
    601. Liu, Li & Wang, Yudong & Yang, Li, 2018. "Predictability of crude oil prices: An investor perspective," Energy Economics, Elsevier, vol. 75(C), pages 193-205.
    602. Zhongxian Men & Adam W. Kolkiewicz & Tony S. Wirjanto, 2013. "Bayesian Inference of Asymmetric Stochastic Conditional Duration Models," Working Paper series 28_13, Rimini Centre for Economic Analysis.
    603. Bochmann, Paul & Hiebert, Paul & Schüler, Yves S. & Segoviano, Miguel, 2022. "Latent fragility: conditioning banks’ joint probability of default on the financial cycle," Working Paper Series 2698, European Central Bank.
    604. Mauro Bernardi & Leopoldo Catania, 2016. "Portfolio Optimisation Under Flexible Dynamic Dependence Modelling," Papers 1601.05199, arXiv.org.
    605. Kevin Dowd, 2004. "FOMC Forecasts of Macroeconomic Risks," Occasional Papers 12, Industrial Economics Division, revised 10 Jan 2004.
    606. P. Schanbacher, 2014. "Measuring and adjusting for overconfidence," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 37(2), pages 423-452, October.
    607. Marcella Lucchetta & Mr. Gianni De Nicolo, 2012. "Systemic Real and Financial Risks: Measurement, Forecasting, and Stress Testing," IMF Working Papers 2012/058, International Monetary Fund.
    608. Bladt, Martin & McNeil, Alexander J., 2022. "Time series copula models using d-vines and v-transforms," Econometrics and Statistics, Elsevier, vol. 24(C), pages 27-48.
    609. Durham, Garland B., 2007. "SV mixture models with application to S&P 500 index returns," Journal of Financial Economics, Elsevier, vol. 85(3), pages 822-856, September.
    610. Mr. Tobias Adrian & Andrea Deghi & Mitsuru Katagiri & Mr. Sohaib Shahid & Nico Valckx, 2020. "Predicting Downside Risks to House Prices and Macro-Financial Stability," IMF Working Papers 2020/011, International Monetary Fund.
    611. Cobb, Marcus P A, 2017. "Aggregate Density Forecasting from Disaggregate Components Using Large VARs," MPRA Paper 76849, University Library of Munich, Germany.
    612. Jondeau, Eric & Rockinger, Michael, 2006. "The Copula-GARCH model of conditional dependencies: An international stock market application," Journal of International Money and Finance, Elsevier, vol. 25(5), pages 827-853, August.
    613. Arroyo, Javier & Maté, Carlos, 2009. "Forecasting histogram time series with k-nearest neighbours methods," International Journal of Forecasting, Elsevier, vol. 25(1), pages 192-207.
    614. Alexander, Marcus & Christakis, Nicholas A., 2008. "Bias and asymmetric loss in expert forecasts: A study of physician prognostic behavior with respect to patient survival," Journal of Health Economics, Elsevier, vol. 27(4), pages 1095-1108, July.
    615. Chiang, Min-Hsien & Wang, Li-Min, 2011. "Volatility contagion: A range-based volatility approach," Journal of Econometrics, Elsevier, vol. 165(2), pages 175-189.
    616. Tong, Bin & Wu, Chongfeng & Zhou, Chunyang, 2013. "Modeling the co-movements between crude oil and refined petroleum markets," Energy Economics, Elsevier, vol. 40(C), pages 882-897.
    617. Mawuli Segnon & Stelios Bekiros, 2019. "Forecasting Volatility in Cryptocurrency Markets," CQE Working Papers 7919, Center for Quantitative Economics (CQE), University of Muenster.
    618. Patton, Andrew J, 2001. "Estimation of Copula Models for Time Series of Possibly Different Length," University of California at San Diego, Economics Working Paper Series qt3fc1c8hw, Department of Economics, UC San Diego.
    619. Katarzyna Bien-Barkowska, 2011. "Distribution Choice for the Asymmetric ACD Models," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 11, pages 55-72.
    620. McAdam, Peter & Warne, Anders, 2020. "Density forecast combinations: the real-time dimension," Working Paper Series 2378, European Central Bank.
    621. Semeyutin, Artur & O’Neill, Robert, 2019. "A brief survey on the choice of parameters for: “Kernel density estimation for time series data”," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    622. Min-Hsien Chiang & Ray Yeutien Chou & Li-Min Wang, 2016. "Outlier Detection in the Lognormal Logarithmic Conditional Autoregressive Range Model," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(1), pages 126-144, February.

  58. Francis X. Diebold, 1998. "The Past, Present, and Future of Macroeconomic Forecasting," Journal of Economic Perspectives, American Economic Association, vol. 12(2), pages 175-192, Spring.
    See citations under working paper version above.
  59. Diebold, Francis X & Neumark, David & Polsky, Daniel, 1997. "Job Stability in the United States," Journal of Labor Economics, University of Chicago Press, vol. 15(2), pages 206-233, April.
    See citations under working paper version above.
  60. Diebold, Francis X. & Lamb, Russell L., 1997. "Why are estimates of agricultural supply response so variable?," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 357-373.
    See citations under working paper version above.
  61. Christoffersen, Peter F. & Diebold, Francis X., 1997. "Optimal Prediction Under Asymmetric Loss," Econometric Theory, Cambridge University Press, vol. 13(6), pages 808-817, December.
    See citations under working paper version above.
  62. Bomfim, Antulio N & Diebold, Francis X, 1997. "Bonded Rationality and Strategic Complementarity in a Macroeconomic Model: Policy Effects, Persistence and Multipliers," Economic Journal, Royal Economic Society, vol. 107(444), pages 1358-1374, September.
    See citations under working paper version above.
  63. Diebold, Francis X & Rudebusch, Glenn D, 1996. "Measuring Business Cycles: A Modern Perspective," The Review of Economics and Statistics, MIT Press, vol. 78(1), pages 67-77, February.
    See citations under working paper version above.
  64. Koehler, Anne & Diebold, Francis X. & Giogianni, Lorenzo & Inoue, Atsushi, 1996. "Software review," International Journal of Forecasting, Elsevier, vol. 12(2), pages 309-315, June.

    Cited by:

    1. Julie Tam & Heather Kirkham, 2000. "Automatic Fiscal Stabilisers: Implications for New Zealand," Treasury Working Paper Series 01/10, New Zealand Treasury, revised 2001.

  65. Diebold, Francis X & Senhadji, Abdelhak S, 1996. "The Uncertain Unit Root in Real GNP: Comment," American Economic Review, American Economic Association, vol. 86(5), pages 1291-1298, December.

    Cited by:

    1. Fang, WenShwo & Miller, Stephen M., 2009. "Modeling the volatility of real GDP growth: The case of Japan revisited," Japan and the World Economy, Elsevier, vol. 21(3), pages 312-324, August.
    2. Michelacci, C. & Zaffaroni, P., 2000. "(Fractional) Beta Convergence," Papers 383, Banca Italia - Servizio di Studi.
    3. Chris Murray & Charles Nelson, 1998. "The Uncertain Trend in U.S. GDP," Discussion Papers in Economics at the University of Washington 0074, Department of Economics at the University of Washington.
    4. WenShwo Fang & Stephen M. Miller, 2012. "Output Growth and Its Volatility: The Gold Standard through the Great Moderation," Working papers 2012-11, University of Connecticut, Department of Economics.
    5. Junsoo Lee & John A. List & Mark Strazicich, 2005. "Nonrenewable Resource Prices: Deterministic or Stochastic Trends?," NBER Working Papers 11487, National Bureau of Economic Research, Inc.
    6. Shelley, Gary L. & Wallace, Frederick H., 2011. "Further evidence regarding nonlinear trend reversion of real GDP and the CPI," Economics Letters, Elsevier, vol. 112(1), pages 56-59, July.
    7. Chevillon, Guillaume, 2013. "Robust Cointegration Testing in the Presence of Weak Trends, with an Application to the Human Origin of Global Warming," ESSEC Working Papers WP1320, ESSEC Research Center, ESSEC Business School.
    8. Ghulam Ghouse & Saud Ahmad Khan & Atiq Ur Rehman & Muhammad Ishaq Bhatti, 2021. "ARDL as an Elixir Approach to Cure for Spurious Regression in Nonstationary Time Series," Mathematics, MDPI, vol. 9(22), pages 1-15, November.
    9. Laura Mayoral, 2005. "The persistence of inflation in OECD countries: A fractionally integrated approach," Economics Working Papers 958, Department of Economics and Business, Universitat Pompeu Fabra, revised Oct 2005.
    10. Bruce E. Hansen, 1999. "The Grid Bootstrap And The Autoregressive Model," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 594-607, November.
    11. Francis X. Diebold & Glenn D. Rudebusch, 2001. "Five questions about business cycles," Economic Review, Federal Reserve Bank of San Francisco, pages 1-15.
    12. Ghoshray, A., 2018. "The Dynamic Properties of Natural Resource Prices," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277210, International Association of Agricultural Economists.
    13. Noriega, Antonio E. & Soria, Luis M. & Velázquez, Ramón, 2008. "International evidence on stochastic and deterministic monetary neutrality," Economic Modelling, Elsevier, vol. 25(6), pages 1261-1275, November.
    14. Gary B. Magee, 2004. "The Importance of Being British? Imperial Factors and the Growth of British Exports, 1870-1960," Department of Economics - Working Papers Series 923, The University of Melbourne.
    15. Francis X. Diebold & Lutz Kilian, 1999. "Unit Root Tests are Useful for Selecting Forecasting Models," New York University, Leonard N. Stern School Finance Department Working Paper Seires 99-063, New York University, Leonard N. Stern School of Business-.
    16. Juan J. Dolado & Jesús Gonzalo & Laura Mayoral, 2005. "What is What? A Simple Time-Domain Test of Long-memory vs. Structural Breaks," Working Papers 258, Barcelona School of Economics.
    17. Rahman, Abdul & Saadi, Samir, 2008. "Random walk and breaking trend in financial series: An econometric critique of unit root tests," Review of Financial Economics, Elsevier, vol. 17(3), pages 204-212, August.
    18. Horváth, Lajos & Liu, Zhenya & Rice, Gregory & Wang, Shixuan, 2020. "Sequential monitoring for changes from stationarity to mild non-stationarity," Journal of Econometrics, Elsevier, vol. 215(1), pages 209-238.
    19. Vougas, Dimitrios V., 2007. "Is the trend in post-WW II US real GDP uncertain or non-linear?," Economics Letters, Elsevier, vol. 94(3), pages 348-355, March.
    20. Michelacci, C., 1999. "Cross-Sectional Heterogeneity and the Persistence of Aggregate Fluctuations," Papers 9906, Centro de Estudios Monetarios Y Financieros-.
    21. Francis X. Diebold & Lutz Kilian, 1997. "Measuring Predictability: Theory and Macroeconomic Applications," NBER Technical Working Papers 0213, National Bureau of Economic Research, Inc.
    22. Surajit Deb, 2003. "Terms of Trade and Supply Response of Indian Agriculture: Analysis in Cointegration Framework," Working papers 115, Centre for Development Economics, Delhi School of Economics.
    23. Atiq-ur-Rehman, Atiq-ur-Rehman & Zaman, Asad, 2009. "Impact of Model Specification Decisions on Unit Root Tests," MPRA Paper 19963, University Library of Munich, Germany.
    24. Gordon de Brouwer & James O'Regan, 1997. "Evaluating Simple Monetary-policy Rules for Australia," RBA Annual Conference Volume (Discontinued), in: Philip Lowe (ed.),Monetary Policy and Inflation Targeting, Reserve Bank of Australia.
    25. Scott E. Harrington & Tong Yu, 2003. "Do Property‐Casualty Insurance Underwriting Margins Have Unit Roots?," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 70(4), pages 715-733, December.
    26. Caner, M. & Kilian, L., 2001. "Size distortions of tests of the null hypothesis of stationarity: evidence and implications for the PPP debate," Journal of International Money and Finance, Elsevier, vol. 20(5), pages 639-657, October.
    27. Noriega Antonio E. & Ventosa-Santaulària Daniel, 2010. "Spurious Long-Horizon Regression in Econometrics," Working Papers 2010-06, Banco de México.
    28. Atiq-ur-Rehman, Atiq-ur-Rehman & Zaman, Asad, 2008. "Model specification, observational equivalence and performance of unit root tests," MPRA Paper 13489, University Library of Munich, Germany.
    29. Valerie Cerra & Antonio Fatás & Sweta C. Saxena, 2023. "Hysteresis and Business Cycles," Journal of Economic Literature, American Economic Association, vol. 61(1), pages 181-225, March.
    30. Kim, Jae & Choi, In, 2015. "Unit Roots in Economic and Financial Time Series: A Re-Evaluation based on Enlightened Judgement," MPRA Paper 68411, University Library of Munich, Germany.
    31. Ahsan ul Haq Satti & Wasim Shahid Malik, 2017. "The Unreliability of Output-Gap Estimates in Real Time," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 56(3), pages 193-219.
    32. Kuo, Biing-Shen & Mikkola, Anne, 1999. "Re-examining long-run purchasing power parity," Journal of International Money and Finance, Elsevier, vol. 18(2), pages 251-266, February.
    33. Antonio E. Noriega & Araceli Ramírez-Zamora, 1999. "Unit roots and multiple structural breaks in real output," Estudios Económicos, El Colegio de México, Centro de Estudios Económicos, vol. 14(2), pages 163-188.
    34. Olivier Darné & Amélie Charles, 2012. "A note on the uncertain trend in US real GNP: Evidence from robust unit root tests," Economics Bulletin, AccessEcon, vol. 32(3), pages 2399-2406.
    35. Bruno Coric & Blanka Peric Skrabic, 2020. "Income Tax Evasion: Recovery from Economic Disasters," CERGE-EI Working Papers wp676, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    36. Osman, Mohammad & Louis, Rosmy & Balli, Faruk, 2008. "Which Output Gap Measure Matters for the Arab Gulf Cooperation Council Countries (AGCC): The Overall GDP Output Gap or the Non-Oil Sector Output Gap?," MPRA Paper 11612, University Library of Munich, Germany.
    37. James H. Stock & Mark W. Watson, 1998. "Business Cycle Fluctuations in U.S. Macroeconomic Time Series," NBER Working Papers 6528, National Bureau of Economic Research, Inc.
    38. Abadir, Karim M. & Caggiano, Giovanni & Talmain, Gabriel, 2013. "Nelson–Plosser revisited: The ACF approach," Journal of Econometrics, Elsevier, vol. 175(1), pages 22-34.
    39. Noriega, Antonio E., 2004. "Long-run monetary neutrality and the unit-root hypothesis: further international evidence," The North American Journal of Economics and Finance, Elsevier, vol. 15(2), pages 179-197, August.
    40. Abdelhak S. Senhadji, 2000. "How Significant are Departures from Certainty Equivalence? Some Analytical and Empirical Results," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 3(3), pages 597-617, July.
    41. Darné, Olivier, 2009. "The uncertain unit root in real GNP: A re-examination," Journal of Macroeconomics, Elsevier, vol. 31(1), pages 153-166, March.
    42. Charles Nelson & Jeremy Piger & Eric Zivot, 1999. "Unit Root Tests in the Presence of Markov Regime-Switching," Discussion Papers in Economics at the University of Washington 0040, Department of Economics at the University of Washington.
    43. Noriega Antonio E. & Rodríguez-Pérez Cid Alonso, 2011. "Stationarity, structural breaks, and economic growth in Mexico: 1895-2008," Working Papers 2011-11, Banco de México.
    44. Camacho, Maximo, 2011. "Markov-switching models and the unit root hypothesis in real US GDP," Economics Letters, Elsevier, vol. 112(2), pages 161-164, August.
    45. Noriega, Antonio E. & de Alba, Enrique, 2001. "Stationarity and structural breaks -- evidence from classical and Bayesian approaches," Economic Modelling, Elsevier, vol. 18(4), pages 503-524, December.
    46. Kim, Chang-Jin & Kim, Jaeho, 2013. "The `Pile-up Problem' in Trend-Cycle Decomposition of Real GDP: Classical and Bayesian Perspectives," MPRA Paper 51118, University Library of Munich, Germany.
    47. Bernd Süssmuth, 2002. "National and Supranational Business Cycles (1960-2000): A multivariate description of central G7 and EURO15 NIPA aggregates," CESifo Working Paper Series 658, CESifo.
    48. Claudio Michelacci, 1999. "Cross-Sectional Heterogeneity and the Persistence of Aggregate Fluctuations," Working Papers wp1999_9906, CEMFI.
    49. Beechey, Meredith & Österholm, Pär, 2008. "Revisiting the uncertain unit root in GDP and CPI: Testing for non-linear trend reversion," Economics Letters, Elsevier, vol. 100(2), pages 221-223, August.
    50. Daniel K. Benjamin, 2010. "Armen Alchian on Evolution, Information, and Cost: The Surprising Implications of Scarcity," Chapters, in: Ross B. Emmett (ed.), The Elgar Companion to the Chicago School of Economics, chapter 14, Edward Elgar Publishing.
    51. Chevillon, Guillaume, 2007. "Inference in the Presence of Stochastic and Deterministic Trends," ESSEC Working Papers DR 07021, ESSEC Research Center, ESSEC Business School.
    52. R. Velazquez & A.E. Noriega & L.M. Soria, 2004. "International Evidence on Monetary Neutrality Under Broken Trend Stationary Models," Econometric Society 2004 Latin American Meetings 57, Econometric Society.
    53. González-Rivera, Gloria & Rodríguez Caballero, Carlos Vladimir & Ruiz Ortega, Esther, 2023. "Modelling intervals of minimum/maximum temperatures in the Iberian Peninsula," DES - Working Papers. Statistics and Econometrics. WS 37968, Universidad Carlos III de Madrid. Departamento de Estadística.
    54. Fleissig, Adrian R. & Strauss, Jack, 1999. "Is OECD real per capita GDP trend or difference stationary? Evidence from panel unit root tests," Journal of Macroeconomics, Elsevier, vol. 21(4), pages 673-689.
    55. Moisa Altar & Ciprian Necula & Gabriel Bobeica, 2009. "A Robust Assessment of the Romanian Business Cycle," Advances in Economic and Financial Research - DOFIN Working Paper Series 28, Bucharest University of Economics, Center for Advanced Research in Finance and Banking - CARFIB.
    56. Hemert, Otto van, 2005. "Optimal intergenerational risk sharing," LSE Research Online Documents on Economics 24660, London School of Economics and Political Science, LSE Library.
    57. Laura Mayoral, 2005. "Further evidence on the statistical properties of real GNP," Economics Working Papers 955, Department of Economics and Business, Universitat Pompeu Fabra, revised Feb 2006.
    58. Erik Hjalmarsson & Pär Österholm, 2007. "A residual-based cointegration test for near unit root variables," International Finance Discussion Papers 907, Board of Governors of the Federal Reserve System (U.S.).
    59. Taiji Harashima, 2005. "The Cause of the Great Inflation: Interactions between the Government and the Monetary Policymakers," Macroeconomics 0510026, University Library of Munich, Germany, revised 17 Nov 2005.
    60. Huang, Yu-Lieh & Huang, Chao-Hsi, 2015. "Uncertain Effects Of Shocks Vs. Uncertain Unit Root: An Alternative View Of U.S. Real Gdp," Hitotsubashi Journal of Economics, Hitotsubashi University, vol. 56(1), pages 117-134, June.
    61. Jae H. Kim & In Choi, 2017. "Unit Roots in Economic and Financial Time Series: A Re-Evaluation at the Decision-Based Significance Levels," Econometrics, MDPI, vol. 5(3), pages 1-23, September.
    62. Wagatha, Matthias, 2007. "Integration, Kointegration und die Langzeitprognose von Kreditausfallzyklen [Integration, Cointegration and Long-Horizont Forecasting of Credit-Default-Cycles]," MPRA Paper 8602, University Library of Munich, Germany.
    63. Giakas, Konstantinos, 2023. "Hysteresis, financial frictions and monetary policy," The Journal of Economic Asymmetries, Elsevier, vol. 27(C).
    64. Schüler, Yves S., 2018. "Detrending and financial cycle facts across G7 countries: mind a spurious medium term!," Working Paper Series 2138, European Central Bank.
    65. Pohl, Walter & Schmedders, Karl & Wilms, Ole, 2016. "Asset prices with non-permanent shocks to consumption," Journal of Economic Dynamics and Control, Elsevier, vol. 69(C), pages 152-178.
    66. Deb, Surajit, 2004. "Terms of Trade and Investment Behaviour in Indian Agriculture: A Cointegration Analysis," Indian Journal of Agricultural Economics, Indian Society of Agricultural Economics, vol. 59(2), pages 1-22.
    67. Ventosa-Santaulària, Daniel & Noriega, Antonio E., 2015. "Long-run monetary neutrality under stochastic and deterministic trends," Economic Modelling, Elsevier, vol. 47(C), pages 372-382.
    68. Laura Mayoral, 2003. "Further Evidence on the Uncertain (Fractional) Unit Root in Real GNP," Working Papers 82, Barcelona School of Economics.

  66. Christoffersen, Peter F & Diebold, Francis X, 1996. "Further Results on Forecasting and Model Selection under Asymmetric Loss," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(5), pages 561-571, Sept.-Oct.
    See citations under working paper version above.
  67. Diebold, Francis X. & Lindner, Peter, 1996. "Fractional integration and interval prediction," Economics Letters, Elsevier, vol. 50(3), pages 305-313, March.

    Cited by:

    1. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 1999. "The Distribution of Exchange Rate Volatility," Center for Financial Institutions Working Papers 99-08, Wharton School Center for Financial Institutions, University of Pennsylvania.
    2. Luis Gil-Alana & Antonio Moreno, 2007. "Uncovering the U.S. Term Premium: An Alternative Route," Faculty Working Papers 12/07, School of Economics and Business Administration, University of Navarra.
    3. Barkoulas, John T. & Baum, Christopher F. & Chakraborty, Atreya, 2001. "Waves and persistence in merger and acquisition activity," Economics Letters, Elsevier, vol. 70(2), pages 237-243, February.
    4. Pérez, Ana & Ruiz Ortega, Esther, 2001. "Modelos de memoria larga para series económicas y financieras," DES - Documentos de Trabajo. Estadística y Econometría. DS ds010101, Universidad Carlos III de Madrid. Departamento de Estadística.
    5. Baillie, Richard T. & Kongcharoen, Chaleampong & Kapetanios, George, 2012. "Prediction from ARFIMA models: Comparisons between MLE and semiparametric estimation procedures," International Journal of Forecasting, Elsevier, vol. 28(1), pages 46-53.
    6. Eisinga, Rob & Franses, Philip Hans & Ooms, Marius, 1999. "Forecasting long memory left-right political orientations," International Journal of Forecasting, Elsevier, vol. 15(2), pages 185-199, April.
    7. John Barkoulas & Christopher F. Baum, 2003. "Long-Memory Forecasting of U.S. Monetary Indices," Boston College Working Papers in Economics 558, Boston College Department of Economics.
    8. Nakamura, Richard, 2004. "To Merge And Acquire When The Times Are Good? The Influence Of Macro Factors On The Japanese M&A Pattern," EIJS Working Paper Series 197, Stockholm School of Economics, The European Institute of Japanese Studies.
    9. John T. Barkoulas & Christopher F. Baum & Nickolaos Travlos, 1996. "Long Memory in the Greek Stock Market," Boston College Working Papers in Economics 356., Boston College Department of Economics.
    10. Francis X. Diebold & Jose A. Lopez, 1996. "Forecast Evaluation and Combination," NBER Technical Working Papers 0192, National Bureau of Economic Research, Inc.
    11. Papailias, Fotis & Fruet Dias, Gustavo, 2015. "Forecasting long memory series subject to structural change: A two-stage approach," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1056-1066.
    12. M. Chudý & S. Karmakar & W. B. Wu, 2020. "Long-term prediction intervals of economic time series," Empirical Economics, Springer, vol. 58(1), pages 191-222, January.
    13. Nakamura, H. Richard, 2002. "Mapping Out the Japanese Mergers & Acquisitions Patterns - The Influence of Macro Factors on M & As," EIJS Working Paper Series 164, Stockholm School of Economics, The European Institute of Japanese Studies.
    14. Town, R.J., "undated". "Merger," Instructional Stata datasets for econometrics merger, Boston College Department of Economics.

  68. Diebold, Francis X. & Chen, Celia, 1996. "Testing structural stability with endogenous breakpoint A size comparison of analytic and bootstrap procedures," Journal of Econometrics, Elsevier, vol. 70(1), pages 221-241, January.
    See citations under working paper version above.
  69. Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-263, July.
    See citations under working paper version above.
  70. Cheung, Yin-Wong & Diebold, Francis X., 1994. "On maximum likelihood estimation of the differencing parameter of fractionally-integrated noise with unknown mean," Journal of Econometrics, Elsevier, vol. 62(2), pages 301-316, June.
    See citations under working paper version above.
  71. Diebold, Francis X & Gardeazabal, Javier & Yilmaz, Kamil, 1994. "On Cointegration and Exchange Rate Dynamics," Journal of Finance, American Finance Association, vol. 49(2), pages 727-735, June.
    See citations under working paper version above.
  72. Diebold, Francis X., 1993. "Discussion : The effect of seasonal adjustment filters on tests for a unit root," Journal of Econometrics, Elsevier, vol. 55(1-2), pages 99-103.

    Cited by:

    1. Daniel, Betty C., 1997. "International interdependence of national growth rates: A structural trends anakysis," Journal of Monetary Economics, Elsevier, vol. 40(1), pages 73-96, September.
    2. Stephen Pollock, 2014. "Econometric Filters," Discussion Papers in Economics 14/07, Division of Economics, School of Business, University of Leicester.
    3. Josef Arlt, 2023. "The problem of annual inflation rate indicator," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 2772-2788, July.

  73. Francis X. Diebold, 1993. "Are long expansions followed by short contractions?," Business Review, Federal Reserve Bank of Philadelphia, issue Jul, pages 3-11.

    Cited by:

    1. Abderrezak, Ali, 1998. "On the Duration of Growth Cycles: An International Study," International Review of Economics & Finance, Elsevier, vol. 7(3), pages 343-355.

  74. Diebold, Francis X & Rudebusch, Glenn D, 1992. "Have Postwar Economic Fluctuations Been Stabilized?," American Economic Review, American Economic Association, vol. 82(4), pages 993-1005, September.
    See citations under working paper version above.
  75. Diebold, Francis X., 1992. "Forecasting, Structural Time Series Models and the Kalman Filter, Andrew C. Harvey Cambridge University Press, 1939 - Fore Casting, Structural Time Series Models and The Kalman FilterAdrew C. Harvey C," Econometric Theory, Cambridge University Press, vol. 8(2), pages 293-299, June.

    Cited by:

    1. Diebold, Giorgianni, & Inoue, "undated". "Stamp 5.0: A Review," Home Pages _058, University of Pennsylvania.
    2. Koehler, Anne & Diebold, Francis X. & Giogianni, Lorenzo & Inoue, Atsushi, 1996. "Software review," International Journal of Forecasting, Elsevier, vol. 12(2), pages 309-315, June.

  76. Diebold, Francis X. & Rudebusch, Glenn D., 1991. "On the power of Dickey-Fuller tests against fractional alternatives," Economics Letters, Elsevier, vol. 35(2), pages 155-160, February.
    See citations under working paper version above.
  77. Francis X. Diebold & Glenn D. Rudebusch, 1991. "Shorter recessions and longer expansions," Business Review, Federal Reserve Bank of Philadelphia, issue Nov, pages 13-20.

    Cited by:

    1. Gross, Marco, 2022. "Beautiful cycles: A theory and a model implying a curious role for interest," Economic Modelling, Elsevier, vol. 106(C).

  78. Diebold, Francis X & Husted, Steven & Rush, Mark, 1991. "Real Exchange Rates under the Gold Standard," Journal of Political Economy, University of Chicago Press, vol. 99(6), pages 1252-1271, December.
    See citations under working paper version above.
  79. Diebold, Francis X & Rudebusch, Glenn D, 1991. "Is Consumption Too Smooth? Long Memory and the Deaton Paradox," The Review of Economics and Statistics, MIT Press, vol. 73(1), pages 1-9, February.
    See citations under working paper version above.
  80. Diebold, Francis X. & Pauly, Peter, 1990. "The use of prior information in forecast combination," International Journal of Forecasting, Elsevier, vol. 6(4), pages 503-508, December.
    See citations under working paper version above.
  81. Diebold, Francis X & Rudebusch, Glenn D, 1990. "A Nonparametric Investigation of Duration Dependence in the American Business Cycle," Journal of Political Economy, University of Chicago Press, vol. 98(3), pages 596-616, June.
    See citations under working paper version above.
  82. Diebold, Francis X. & Nason, James A., 1990. "Nonparametric exchange rate prediction?," Journal of International Economics, Elsevier, vol. 28(3-4), pages 315-332, May.
    See citations under working paper version above.
  83. Diebold, Francis X & Sharpe, Steven A, 1990. "Post-deregulation Bank-Deposit-Rate Pricing: The Multivariate Dynamics," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(3), pages 281-291, July.

    Cited by:

    1. Charles M. Kahn & George Pennacchi & Ben Sopranzetti, 1996. "Bank deposit rate clustering: theory and empirical evidence," Working Papers (Old Series) 9604, Federal Reserve Bank of Cleveland.
    2. Itamar Drechsler & Alexi Savov & Philipp Schnabl, 2016. "The Deposits Channel of Monetary Policy," NBER Working Papers 22152, National Bureau of Economic Research, Inc.
    3. Francis X. Diebold & Canlin Li, 2002. "Forecasting the Term Structure of Government Bond Yields," Center for Financial Institutions Working Papers 02-34, Wharton School Center for Financial Institutions, University of Pennsylvania.
    4. Bredin, Don & Fitzpatrick, Trevor & O'Reilly, Gerard, 2001. "Retail Interest Rate Pass-Through: The Irish Experience," Research Technical Papers 6/RT/01, Central Bank of Ireland.
    5. Alfaro, Rodrigo & Becerra, Juan Sebastian & Sagner, Andres, 2010. "Estimación de la estructura de tasas utilizando el modelo Dinámico Nelson Siegel: resultados para Chile y EEUU [The Dynamic Nelson-Siegel model: empirical results for Chile and US]," MPRA Paper 25912, University Library of Munich, Germany, revised 23 Jun 2010.
    6. Francis X. Diebold, 2004. "The Nobel Memorial Prize for Robert F. Engle," Scandinavian Journal of Economics, Wiley Blackwell, vol. 106(2), pages 165-185, June.
    7. Yasuo Nishiyama, 2007. "Are Banks Risk-Averse?," Eastern Economic Journal, Eastern Economic Association, vol. 33(4), pages 471-490, Fall.
    8. Rodrigo Fuentes & Solange Berstein, 2004. "Concentration and Price Rigidity: Evidence for the deposit Market in Chile," Econometric Society 2004 Latin American Meetings 67, Econometric Society.
    9. John C. Driscoll & Ruth A. Judson, 2013. "Sticky deposit rates," Finance and Economics Discussion Series 2013-80, Board of Governors of the Federal Reserve System (U.S.).
    10. James Gilkeson & John List & Craig Ruff, 1999. "Evidence of Early Withdrawal in Time Deposit Portfolios," Journal of Financial Services Research, Springer;Western Finance Association, vol. 15(2), pages 103-122, March.
    11. Vladimir Yankov, 2014. "In Search of a Risk-free Asset," Finance and Economics Discussion Series 2014-108, Board of Governors of the Federal Reserve System (U.S.).
    12. Koont, Naz & Santos, Tano & Zingales, Luigi, 2023. "Destabilizing digital "bank walks"," Working Papers 328, The University of Chicago Booth School of Business, George J. Stigler Center for the Study of the Economy and the State.
    13. Birge, John R. & Júdice, Pedro, 2013. "Long-term bank balance sheet management: Estimation and simulation of risk-factors," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 4711-4720.
    14. Scholnick, Barry, 1996. "Asymmetric adjustment of commercial bank interest rates: evidence from Malaysia and Singapore," Journal of International Money and Finance, Elsevier, vol. 15(3), pages 485-496, June.
    15. Guo, Lin, 2003. "Inferring market information from the price and quantity of S&L deposits," Journal of Banking & Finance, Elsevier, vol. 27(11), pages 2177-2202, November.
    16. Ambrogio Cesa-Bianchi & Alessandro Rebucci, 2016. "Does Easing Monetary Policy Increase Financial Instability?," NBER Working Papers 22283, National Bureau of Economic Research, Inc.
    17. Hsu-Ling Chang & Chi-Wei Su, 2010. "The Lending-Deposit Rate Relationship in Eastern European Countries: Evidence from the Rank Test for Non-linear Cointegration," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 60(6), pages 534-544, December.
    18. Thompson, Mark A., 2006. "Asymmetric adjustment in the prime lending-deposit rate spread," Review of Financial Economics, Elsevier, vol. 15(4), pages 323-329.
    19. Michael J. Dueker, 2000. "Are prime rate changes asymmetric?," Review, Federal Reserve Bank of St. Louis, vol. 82(Sep), pages 33-40.
    20. Roger Craine, 1996. "Fairly Priced Deposit Insurance and Bank Charter Policy," Finance 9605002, University Library of Munich, Germany.
    21. Richard Sheehan, 2013. "Valuing Core Deposits," Journal of Financial Services Research, Springer;Western Finance Association, vol. 43(2), pages 197-220, April.
    22. Chu V. Nguyen, & Muhammad Mahboob Ali, & Alexandru Mircea Nedelea, 2017. "The Behaviors Of Lending, Deposit Rates And Intermediation Premium Of Pakistani Banks With Different Types Of Ownership Structures," EcoForum, "Stefan cel Mare" University of Suceava, Romania, Faculty of Economics and Public Administration - Economy, Business Administration and Tourism Department., vol. 6(1), pages 1-49, January.
    23. Guo, Lin & Prezas, Alexandros P., 2019. "Market monitoring and influence: evidence from deposit pricing and liability composition from 1986 to 2013," Journal of Financial Stability, Elsevier, vol. 43(C), pages 146-166.
    24. Raquel Lago-González & Vicente Salas-Fumás, 2005. "Market power and bank interest rate adjustments," Working Papers 0539, Banco de España.
    25. Gerlach, Jeffrey R. & Mora, Nada & Uysal, Pinar, 2018. "Bank funding costs in a rising interest rate environment," Journal of Banking & Finance, Elsevier, vol. 87(C), pages 164-186.
    26. Su, Chi Wei & Chang, Hsu Ling, 2010. "Asymmetric Adjustment in the Lending-Deposit Rate Spread: Evidence from Eastern European Countries," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 165-175, July.
    27. Gary B. Gorton, 2019. "The Regulation of Private Money," NBER Working Papers 25891, National Bureau of Economic Research, Inc.
    28. Nishiyama, Yasuo, 2011. "The term structure of CD rates and monetary policy transmission," Journal of Banking & Finance, Elsevier, vol. 35(1), pages 82-94, January.
    29. Sjölander, Pär, 2013. "A ridge bootstrap method for analyzing APT effects on the mortgage loan market," Economic Modelling, Elsevier, vol. 30(C), pages 844-855.
    30. Blöchlinger, Andreas, 2015. "Identifying, valuing and hedging of embedded options in non-maturity deposits," Journal of Banking & Finance, Elsevier, vol. 50(C), pages 34-51.

  84. Diebold, Francis X & Rudebusch, Glenn D, 1989. "Scoring the Leading Indicators," The Journal of Business, University of Chicago Press, vol. 62(3), pages 369-391, July.
    See citations under working paper version above.
  85. Diebold, Francis X. & Rudebusch, Glenn D., 1989. "Long memory and persistence in aggregate output," Journal of Monetary Economics, Elsevier, vol. 24(2), pages 189-209, September.
    See citations under working paper version above.
  86. Diebold, Francis X, 1989. "Structural Time Series Analysis and Modelling Package: A Review," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 4(2), pages 195-204, April-Jun.

    Cited by:

    1. Diebold, Giorgianni, & Inoue, "undated". "Stamp 5.0: A Review," Home Pages _058, University of Pennsylvania.
    2. Koehler, Anne & Diebold, Francis X. & Giogianni, Lorenzo & Inoue, Atsushi, 1996. "Software review," International Journal of Forecasting, Elsevier, vol. 12(2), pages 309-315, June.
    3. Patrick Wilson & Simon Stevenson & Ralf Zurbruegg, 2007. "Foreign Property Shocks and the Impact on Domestic Securitized Real Estate Markets: An Unobserved Components Approach," The Journal of Real Estate Finance and Economics, Springer, vol. 34(3), pages 407-424, April.

  87. Diebold, Francis X., 1989. "State space modeling of time series : A review essay," Journal of Economic Dynamics and Control, Elsevier, vol. 13(4), pages 597-612, October.
    See citations under working paper version above.
  88. Diebold, Francis X & Nerlove, Marc, 1989. "The Dynamics of Exchange Rate Volatility: A Multivariate Latent Factor Arch Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 4(1), pages 1-21, Jan.-Mar..
    See citations under working paper version above.
  89. Diebold, Francis X., 1989. "Forecast combination and encompassing: Reconciling two divergent literatures," International Journal of Forecasting, Elsevier, vol. 5(4), pages 589-592.
    See citations under working paper version above.
  90. Diebold, Francis X., 1988. "Testing for bubbles, reflecting barriers and other anomalies," Journal of Economic Dynamics and Control, Elsevier, vol. 12(1), pages 63-70, March.

    Cited by:

    1. Jean-Pierre Laffargue & Sanvi Avouyi-Dovi, 1992. "Anticipations stabilisatrices dans un système de serpent monétaire. Théorie et application au système monétaire européen," Revue Économique, Programme National Persée, vol. 43(6), pages 1107-1128.
    2. Li, Minqiang, 2010. "A damped diffusion framework for financial modeling and closed-form maximum likelihood estimation," Journal of Economic Dynamics and Control, Elsevier, vol. 34(2), pages 132-157, February.

  91. Diebold, Francis X. & Pauly, Peter, 1988. "Endogenous risk in a portfolio-balance rational-expectations model of the Deutschemark-Dollar rate," European Economic Review, Elsevier, vol. 32(1), pages 27-53, January.

    Cited by:

    1. Malliaropulos, Dimitrios, 1997. "A multivariate GARCH model of risk premia in foreign exchange markets," Economic Modelling, Elsevier, vol. 14(1), pages 61-79, January.
    2. Richard Meese & Andrew K. Rose, 1989. "An empirical assessment of non-linearities in models of exchange rate determination," International Finance Discussion Papers 367, Board of Governors of the Federal Reserve System (U.S.).
    3. Morley, Bruce & Pentecost, Eric J., 1998. "Asset pricing and foreign exchange risk: econometric evidence for the G-7," Journal of International Money and Finance, Elsevier, vol. 17(2), pages 317-329, April.
    4. Rude, James & Surry, Yves, 2013. "Canadian Hog Supply Respose: A Provincial Level Analysis," Working Papers 148590, Structure and Performance of Agriculture and Agri-products Industry (SPAA).
    5. Alexakis, Panayotis & Apergis, Nicholas, 1996. "ARCH effects and cointegration: Is the foreign exchange market efficient?," Journal of Banking & Finance, Elsevier, vol. 20(4), pages 687-697, May.
    6. Tim Bollerslev & Ray Y. Chou & Narayanan Jayaraman & Kenneth F. Kroner - L, 1991. "es modéles ARCH en finance : un point sur la théorie et les résultats empiriques," Annals of Economics and Statistics, GENES, issue 24, pages 1-59.
    7. Holt, Matthew T. & Aradhyula, Satheesh V., 1991. "Endogenous Risk in a Rational-Expectation Model of the U.S. Broiler Market: A Multivariate Arch-M Approach," Staff Papers 200538, University of Wisconsin-Madison, Department of Agricultural and Applied Economics.
    8. McKenzie, Andrew M. & Holt, Matthew T., 1998. "Market Efficiency In Agricultural Futures Markets," 1998 Annual meeting, August 2-5, Salt Lake City, UT 20933, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    9. Maggiori, Matteo, 2021. "International Macroeconomics With Imperfect Financial Markets," SocArXiv z8g6r, Center for Open Science.
    10. Daly, Kevin, 2008. "Financial volatility: Issues and measuring techniques," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(11), pages 2377-2393.
    11. Holt, Matthew T. & Aradhyula, Satheesh V., 1998. "Endogenous risk in rational-expectations commodity models: A multivariate generalized ARCH-M approach," Journal of Empirical Finance, Elsevier, vol. 5(2), pages 99-129, June.
    12. Bollerslev, Tim, 1990. "Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model," The Review of Economics and Statistics, MIT Press, vol. 72(3), pages 498-505, August.
    13. Adrián Fernández-P�rez & Fernando Fernández-Rodr�guez & Simón Sosvilla-Rivero, 2012. "Exploiting trends in the foreign exchange markets," Applied Economics Letters, Taylor & Francis Journals, vol. 19(6), pages 591-597, April.
    14. Degiannakis, Stavros & Xekalaki, Evdokia, 2004. "Autoregressive Conditional Heteroskedasticity (ARCH) Models: A Review," MPRA Paper 80487, University Library of Munich, Germany.

  92. Diebold, F X & Pauly, P, 1988. "Has the EMS Reduced Member-Country Exchange Rate Volatility?," Empirical Economics, Springer, vol. 13(2), pages 81-102.

    Cited by:

    1. Hu, Michael Y. & Tsoukalas, Christos, 1999. "Combining conditional volatility forecasts using neural networks: an application to the EMS exchange rates," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 9(4), pages 407-422, November.
    2. Neely, Christopher J., 1999. "Target zones and conditional volatility: The role of realignments," Journal of Empirical Finance, Elsevier, vol. 6(2), pages 177-192, April.
    3. Hu, Michael Y. & Jiang, Christine X. & Tsoukalas, Christos, 1997. "The European exchange rates before and after the establishment of the European Monetary System," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 7(3), pages 235-253, October.
    4. Tim Bollerslev & Ray Y. Chou & Narayanan Jayaraman & Kenneth F. Kroner - L, 1991. "es modéles ARCH en finance : un point sur la théorie et les résultats empiriques," Annals of Economics and Statistics, GENES, issue 24, pages 1-59.
    5. Beum-Jo Park, 2002. "Asymmetric Volatility of Exchange Rate Returns Under The EMS: Some Evidence From Quantile Regression Approach for Tgarch Models," International Economic Journal, Taylor & Francis Journals, vol. 16(1), pages 105-125.
    6. David Chappell & Lindsay Chant, 1998. "A non-linear time series model for the South Korean Won/British pound exchange rate : 1.1.97-9.30.98," Global Economic Review, Taylor & Francis Journals, vol. 27(3), pages 65-75.
    7. Yin-Wong Cheung & Hung-Gay Fung & Kon S. Lai & Wai-Chung Lo, 1995. "Purchasing power parity under the European Monetary System," Journal of International Money and Finance, Elsevier, vol. 14(2), pages 179-189, April.
    8. Chihwa Kao, 2001. "Geography, Industrial Organization, and Agglomeration Heteroskedasticity Models with Estimates of the Variances of Foreign Exchange Rates," Center for Policy Research Working Papers 34, Center for Policy Research, Maxwell School, Syracuse University.

  93. Diebold, Francis X, 1988. "Serial Correlation and the Combination of Forecasts," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(1), pages 105-111, January.

    Cited by:

    1. J. M. Gil & L. M. Albisu, 1993. "Composite Forecasting Methods: An Application To Spanish Maize Prices," Journal of Agricultural Economics, Wiley Blackwell, vol. 44(2), pages 264-271, May.
    2. M A Sánchez-Granero & J E Trinidad-Segovia & J Clara-Rahola & A M Puertas & F J De las Nieves, 2017. "A model for foreign exchange markets based on glassy Brownian systems," PLOS ONE, Public Library of Science, vol. 12(12), pages 1-22, December.
    3. Yi-Ting Chen & Chu-An Liu, 2021. "Model Averaging for Asymptotically Optimal Combined Forecasts," IEAS Working Paper : academic research 21-A002, Institute of Economics, Academia Sinica, Taipei, Taiwan.
    4. Ekaterina V. Astafyeva & Maria Yu. Turuntseva, 2023. "Analysis of Opportunities to Improve the Quality of Natural Resource Price by Combining Forecasts Resulting from Methods Based on Regression Estimates of Weights [Анализ Возможностей Улучшения Каче," Russian Economic Development, Gaidar Institute for Economic Policy, issue 12, pages 24-33, December.
    5. de Menezes, Lilian M. & W. Bunn, Derek & Taylor, James W., 2000. "Review of guidelines for the use of combined forecasts," European Journal of Operational Research, Elsevier, vol. 120(1), pages 190-204, January.
    6. Christopher G. Gibbs, 2017. "Forecast combination, non-linear dynamics, and the macroeconomy," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 63(3), pages 653-686, March.
    7. David Hendry & Michael P. Clements, 2001. "Pooling of Forecasts," Economics Papers 2002-W9, Economics Group, Nuffield College, University of Oxford.
    8. Timmermann, Allan, 2006. "Forecast Combinations," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 4, pages 135-196, Elsevier.
    9. Pablo Pincheira-Brown & Andrea Bentancor & Nicolás Hardy, 2023. "An Inconvenient Truth about Forecast Combinations," Mathematics, MDPI, vol. 11(18), pages 1-24, September.
    10. Jiun-Hua Su, 2021. "No-Regret Forecasting with Egalitarian Committees," Papers 2109.13801, arXiv.org.
    11. Elkin Castaño & Luis Fernando Melo, 1998. "Métodos de Combinación de Pronósticos: Una Aplicación a la Inflación Colombiana," Borradores de Economia 109, Banco de la Republica de Colombia.
    12. Wang, Xiaoqian & Hyndman, Rob J. & Li, Feng & Kang, Yanfei, 2023. "Forecast combinations: An over 50-year review," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1518-1547.
    13. Elkin Castaño V. & Luis Fernando Melo Velandia, 1998. "Métodos De Combinación De Pronósticos:Una Aplicación A La Inflación Colombiana," Borradores de Economia 3212, Banco de la Republica.
    14. Frédérique Bec & Matteo Mogliani, 2013. "Nowcasting French GDP in Real-Time from Survey Opinions : Information or Forecast Combinations ?," Working Papers 2013-21, Center for Research in Economics and Statistics.
    15. de Menezes, Lilian M. & Bunn, Derek W., 1998. "The persistence of specification problems in the distribution of combined forecast errors," International Journal of Forecasting, Elsevier, vol. 14(3), pages 415-426, September.
    16. Francis X. Diebold & Jose A. Lopez, 1996. "Forecast Evaluation and Combination," NBER Technical Working Papers 0192, National Bureau of Economic Research, Inc.
    17. Elliott, Graham & Timmermann, Allan, 2004. "Optimal forecast combinations under general loss functions and forecast error distributions," Journal of Econometrics, Elsevier, vol. 122(1), pages 47-79, September.
    18. Pablo Pincheira, 2012. "Are Forecast Combinations Efficient?," Working Papers Central Bank of Chile 661, Central Bank of Chile.
    19. Ewa Ratuszny, 2015. "Risk Modeling of Commodities using CAViaR Models, the Encompassing Method and the Combined Forecasts," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 15, pages 129-156.
    20. Paul Soderlind, 2010. "Predicting stock price movements: regressions versus economists," Applied Economics Letters, Taylor & Francis Journals, vol. 17(9), pages 869-874.
    21. Massimo Guidolin & Carrie Fangzhou Na, 2007. "The economic and statistical value of forecast combinations under regime switching: an application to predictable U.S. returns," Working Papers 2006-059, Federal Reserve Bank of St. Louis.
    22. Bin Chen & Kenwin Maung, 2020. "Time-varying Forecast Combination for High-Dimensional Data," Papers 2010.10435, arXiv.org.
    23. Giovanni De Luca & Alfonso Carfora, 2014. "Predicting U.S. recessions through a combination of probability forecasts," Empirical Economics, Springer, vol. 46(1), pages 127-144, February.
    24. Kenton K. Yee, 2007. "A Bayesian Framework for Combining Valuation Estimates," Papers 0707.3482, arXiv.org.
    25. David G. McMillan & Mark E. Wohar, 2010. "Stock return predictability and dividend-price ratio: a nonlinear approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 15(4), pages 351-365.
    26. Konstantin Kuck & Karsten Schweikert, 2021. "Forecasting Baden‐Württemberg's GDP growth: MIDAS regressions versus dynamic mixed‐frequency factor models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 861-882, August.
    27. Ekaterina V. Astafyeva & Maria Yu. Turuntseva, 2023. "Анализ Возможностей Улучшения Качества Прогнозов Цен На Природные Ресурсы Методами Комбинирования На Основе Регрессионных Оценок Весов," Russian Economic Development (in Russian), Gaidar Institute for Economic Policy, issue 12, pages 24-33, December.
    28. Stuart, Rebecca, 2018. "A quarterly Phillips curve for Switzerland using interpolated data, 1963–2016," Economic Modelling, Elsevier, vol. 70(C), pages 78-86.
    29. Ekrem Kilic, 2005. "Forecasting Volatility of Turkish Markets: A Comparison of Thin and Thick Models," Econometrics 0510007, University Library of Munich, Germany.
    30. Elkin Castaño Vélez & Luis Fernando Melo Velandia, 2000. "Metodos de combinacion de pronosticos: una aplicacion a la inflacion," Lecturas de Economía, Universidad de Antioquia, Departamento de Economía, issue 52, pages 113-165, Enero Jun.

  94. Diebold, Francis X., 1986. "Exact maximum-likelihood estimation of autoregressive models via the Kalman filter," Economics Letters, Elsevier, vol. 22(2-3), pages 197-201.

    Cited by:

    1. Pollock, D. S. G., 2003. "Recursive estimation in econometrics," Computational Statistics & Data Analysis, Elsevier, vol. 44(1-2), pages 37-75, October.
    2. Manahov, Viktor & Hudson, Robert & Gebka, Bartosz, 2014. "Does high frequency trading affect technical analysis and market efficiency? And if so, how?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 28(C), pages 131-157.
    3. Stephen Pollock, 2002. "Recursive Estimation in Econometrics," Working Papers 462, Queen Mary University of London, School of Economics and Finance.

  95. Diebold, Francis X., 1986. "The exact initial covariance matrix of the state vector of a general MA(q) process," Economics Letters, Elsevier, vol. 22(1), pages 27-31.

    Cited by:

    1. Pollock, D. S. G., 2003. "Recursive estimation in econometrics," Computational Statistics & Data Analysis, Elsevier, vol. 44(1-2), pages 37-75, October.
    2. Stephen Pollock, 2002. "Recursive Estimation in Econometrics," Working Papers 462, Queen Mary University of London, School of Economics and Finance.

Chapters

  1. Francis X. Diebold & Laura Liu & Kamil Yilmaz, 2018. "Commodity Connectedness," Central Banking, Analysis, and Economic Policies Book Series, in: Enrique G. Mendoza & Ernesto Pastén & Diego Saravia (ed.),Monetary Policy and Global Spillovers: Mechanisms, Effects and Policy Measures, edition 1, volume 25, chapter 4, pages 097-136, Central Bank of Chile.
    See citations under working paper version above.
  2. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2013. "Financial Risk Measurement for Financial Risk Management," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1127-1220, Elsevier.
    See citations under working paper version above.
  3. Francis X. Diebold & Kamil Yilmaz, 2011. "Equity Market Spillovers in the Americas," Central Banking, Analysis, and Economic Policies Book Series, in: Rodrigo Alfaro (ed.),Financial Stability, Monetary Policy, and Central Banking, edition 1, volume 15, chapter 7, pages 199-214, Central Bank of Chile.
    See citations under working paper version above.
  4. S. Borağan Aruoba & Francis X. Diebold & M. Ayhan Kose & Marco E. Terrones, 2010. "Globalization, the Business Cycle, and Macroeconomic Monitoring," NBER Chapters, in: NBER International Seminar on Macroeconomics 2010, pages 245-286, National Bureau of Economic Research, Inc.
    See citations under working paper version above.
  5. Torben G. Andersen & Tim Bollerslev & Peter Christoffersen & Francis X. Diebold, 2007. "Practical Volatility and Correlation Modeling for Financial Market Risk Management," NBER Chapters, in: The Risks of Financial Institutions, pages 513-544, National Bureau of Economic Research, Inc.
    See citations under working paper version above.
  6. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.

    Cited by:

    1. Márcio Gomes Pinto Garcia & Marcelo Cunha Medeiros & Francisco Eduardo de Luna e Almeida Santos, 2014. "Economic gains of realized volatility in the Brazilian stock market," Brazilian Review of Finance, Brazilian Society of Finance, vol. 12(3), pages 319-349.
    2. Sattarhoff, Cristina & Gronwald, Marc, 2022. "Measuring informational efficiency of the European carbon market — A quantitative evaluation of higher order dependence," International Review of Financial Analysis, Elsevier, vol. 84(C).
    3. Davide Pettenuzzo & Konstantinos Metaxoglou & Aaron Smith, 2016. "Option-Implied Equity Premium Predictions via Entropic TiltinG," Working Papers 99R, Brandeis University, Department of Economics and International Business School, revised Aug 2016.
    4. Degiannakis, Stavros & Floros, Christos, 2014. "Intra-Day Realized Volatility for European and USA Stock Indices," MPRA Paper 64940, University Library of Munich, Germany, revised Jan 2015.
    5. Degiannakis, Stavros & Floros, Christos, 2013. "Modeling CAC40 volatility using ultra-high frequency data," Research in International Business and Finance, Elsevier, vol. 28(C), pages 68-81.
    6. Tim Bollerslev, 2008. "Glossary to ARCH (GARCH)," CREATES Research Papers 2008-49, Department of Economics and Business Economics, Aarhus University.
    7. Gadea Rivas, María Dolores & Gonzalo, Jesús, 2017. "Trends in distributional characteristics : Existence of global warming," UC3M Working papers. Economics 24121, Universidad Carlos III de Madrid. Departamento de Economía.
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    196. Rama K. Malladi & Prakash L. Dheeriya, 2021. "Time series analysis of Cryptocurrency returns and volatilities," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 45(1), pages 75-94, January.
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Books

  1. Diebold, Francis X. & Yilmaz, Kamil, 2015. "Financial and Macroeconomic Connectedness: A Network Approach to Measurement and Monitoring," OUP Catalogue, Oxford University Press, number 9780199338306.

    Cited by:

    1. Okorie, David Iheke & Lin, Boqiang, 2022. "Givers never lack: Nigerian oil & gas asymmetric network analyses," Energy Economics, Elsevier, vol. 108(C).
    2. Zhang, Xiaoyuan & Zhang, Tianqi, 2022. "Dynamic credit contagion and aggregate loss in networks," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    3. Ha, Jongrim & Kose, M. Ayhan & Otrok, Christopher & Prasad, Eswar, 2020. "Global Macro-Financial Cycles and Spillovers," IZA Discussion Papers 13000, Institute of Labor Economics (IZA).
    4. Áureo de Paula & Imran Rasul & Pedro CL Souza, 2023. "Identifying network ties from panel data: Theory and an application to tax competition," CeMMAP working papers 21/23, Institute for Fiscal Studies.
    5. Lyócsa, Štefan & Výrost, Tomáš & Baumöhl, Eduard, 2019. "Return spillovers around the globe: A network approach," Economic Modelling, Elsevier, vol. 77(C), pages 133-146.
    6. Lovcha, Yuliya & Pérez Laborda, Àlex & Sikora, Iryna, 2019. "The Determinants of CO2 prices in the EU ETS System," Working Papers 2072/376031, Universitat Rovira i Virgili, Department of Economics.
    7. Baumöhl, Eduard & Kočenda, Evžen & Lyócsa, Štefan & Výrost, Tomáš, 2018. "Networks of volatility spillovers among stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1555-1574.
    8. Cimini, Riccardo, 2015. "Eurozone network “Connectedness” after fiscal year 2008," Finance Research Letters, Elsevier, vol. 14(C), pages 160-166.
    9. Matteo Barigozzi & Christian Brownlees, 2013. "Nets: Network Estimation for Time Series," Working Papers 723, Barcelona School of Economics.
    10. Raju Huidrom & M. Ayhan Kose & Hideaki Matsuoka & Franziska L. Ohnsorge, 2020. "How important are spillovers from major emerging markets?," International Finance, Wiley Blackwell, vol. 23(1), pages 47-63, March.
    11. Jozef Baruník & Evžen Kocenda, 2019. "Total, Asymmetric and Frequency Connectedness Between Oil and Forex Markets," CESifo Working Paper Series 7756, CESifo.
    12. Thiem, Christopher, 2018. "Cross-category spillovers of economic policy uncertainty," Ruhr Economic Papers 744, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    13. Carlos Arteta & M. Ayhan Kose & Franziska Ohnsorge & Marc Stocker, 2015. "The Coming U.S. Interest Rate Tightening Cycle: Smooth Sailing or Stormy Waters?," Policy Research Notes (PRNs) 100014, The World Bank.
    14. Kose, M. Ayhan & Sugawara, Naotaka & E. Terrones, Marco, 2020. "Global Recessions," CEPR Discussion Papers 14397, C.E.P.R. Discussion Papers.
    15. Jonathan E. Ogbuabor & God’stime O. Eigbiremolen & Gladys C. Aneke & Manasseh O. Charles, 2018. "Measuring the dynamics of APEC output connectedness," Asian-Pacific Economic Literature, The Crawford School, The Australian National University, vol. 32(1), pages 29-44, May.
    16. Miao, Ke & Phillips, Peter C.B. & Su, Liangjun, 2023. "High-dimensional VARs with common factors," Journal of Econometrics, Elsevier, vol. 233(1), pages 155-183.
    17. Mishra, Abinash & Srivastava, Pranjal & Chakrabarti, Anindya S., 2020. "'Too central to fail' firms in bi-layered financial networks: Evidence of linkages from the US corporate bond and stock markets," IIMA Working Papers WP 2020-06-02, Indian Institute of Management Ahmedabad, Research and Publication Department.
    18. International Monetary Fund, 2018. "Brazil: Financial Sector Assessment Program-Technical Note on Stress Testing and Systemic Risk Analysis," IMF Staff Country Reports 2018/344, International Monetary Fund.
    19. Ekeocha, Patterson & Ogbuabor, Jonathan, 2020. "Measuring and Evaluating the Dynamics of Trade Shock Propagation in the Oceania," Conference papers 333234, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    20. Nikolaos Antonakakis & Juncal Cunado & George Filis & David Gabauer & Fernando Perez de Gracia, 2018. "Oil volatility, oil and gas firms and portfolio diversification," BAFES Working Papers BAFES18, Department of Accounting, Finance & Economic, Bournemouth University.
    21. Stoupos, Nikolaos & Kiohos, Apostolos, 2022. "Bond markets integration in the EU: New empirical evidence from the Eastern non-euro member-states," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    22. Timo Bettendorf & Reinhold Heinlein, 2023. "Connectedness between G10 currencies: Searching for the causal structure," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 3938-3959, October.
    23. Erhan Uluceviz & Kamil Yilmaz, 2020. "Real-financial connectedness in the Swiss economy," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 156(1), pages 1-20, December.
    24. Rebekka Gätjen & Melanie Schienle, 2015. "Measuring Connectedness of Euro Area Sovereign Risk," SFB 649 Discussion Papers SFB649DP2015-019, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    25. Karkowska, Renata & Urjasz, Szczepan, 2021. "Connectedness structures of sovereign bond markets in Central and Eastern Europe," International Review of Financial Analysis, Elsevier, vol. 74(C).
    26. Everett Grant, 2018. "The Double-Edged Sword of Global Integration: Robustness, Fragility \& Contagion in the International Firm Network," 2018 Meeting Papers 506, Society for Economic Dynamics.
    27. Honghai Yu & Wencong Sun & Xiangting Ye & Libing Fang, 2019. "Measuring the increasing connectedness of Chinese assets with global assets: using a variance decompositions method," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(5), pages 1261-1290, March.
    28. Arreola Hernandez, Jose & Kang, Sang Hoon & Shahzad, Syed Jawad Hussain & Yoon, Seong-Min, 2020. "Spillovers and diversification potential of bank equity returns from developed and emerging America," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    29. Nicolas Debarsy & Cyrille Dossougoin & Cem Ertur & Jean-Yves Gnabo, 2018. "Measuring sovereign risk spillovers and assessing the role of transmission channels: A spatial econometrics approach," Post-Print hal-01744629, HAL.
    30. Gao, Yang & Li, Yangyang & Zhao, Chengjie & Wang, Yaojun, 2022. "Risk spillover analysis across worldwide ESG stock markets: New evidence from the frequency-domain," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    31. Georgios Magkonis & Abhijit Sharma, 2019. "Inflation Linkages Within The Eurozone: Core vs. Periphery," Scottish Journal of Political Economy, Scottish Economic Society, vol. 66(2), pages 277-289, May.
    32. Tam Hoang-Nhat Dang & Nhan Thien Nguyen & Duc Hong Vo, 2023. "Sectoral volatility spillovers and their determinants in Vietnam," Economic Change and Restructuring, Springer, vol. 56(1), pages 681-700, February.
    33. Magkonis, Georgios & Tsopanakis, Andreas, 2016. "The financial and fiscal stress interconnectedness: The case of G5 economies," International Review of Financial Analysis, Elsevier, vol. 46(C), pages 62-69.
    34. Hardik A. Marfatia & Rangan Gupta & Esin Cakan, 2017. "The International REIT's Time-Varying Response to the U.S. Monetary Policy and Macroeconomic Surprises," Working Papers 201712, University of Pretoria, Department of Economics.
    35. Kang, Sang Hoon & Maitra, Debasish & Dash, Saumya Ranjan & Brooks, Robert, 2019. "Dynamic spillovers and connectedness between stock, commodities, bonds, and VIX markets," Pacific-Basin Finance Journal, Elsevier, vol. 58(C).
    36. Daniel Danau, 2018. "Prudence and preference for flexibility gain," Working Papers hal-01806743, HAL.
    37. Prasad, Nalin & Grant, Andrew & Kim, Suk-Joong, 2018. "Time varying volatility indices and their determinants: Evidence from developed and emerging stock markets," International Review of Financial Analysis, Elsevier, vol. 60(C), pages 115-126.
    38. Áureo de Paula, 2015. "Econometrics of network models," CeMMAP working papers CWP52/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    39. Fijorek, Kamil & Jurkowska, Aleksandra & Jonek-Kowalska, Izabela, 2021. "Financial contagion between the financial and the mining industries – Empirical evidence based on the symmetric and asymmetric CoVaR approach," Resources Policy, Elsevier, vol. 70(C).
    40. Ben R. Craig & Martin Saldias Zambrana, 2016. "Spatial Dependence and Data-Driven Networks of International Banks," Working Papers (Old Series) 1627, Federal Reserve Bank of Cleveland.
    41. Baruník, Jozef & Kočenda, Evžen & Vácha, Lukáš, 2017. "Asymmetric volatility connectedness on the forex market," Journal of International Money and Finance, Elsevier, vol. 77(C), pages 39-56.
    42. Georgios Magkonis & Andreas Tsopanakis, 2018. "The Financial Connectedness between Eurozone Core and Periphery: A Disaggregated View," Working Papers in Economics & Finance 2018-03, University of Portsmouth, Portsmouth Business School, Economics and Finance Subject Group.
    43. Bostanci, Gorkem & Yilmaz, Kamil, 2020. "How connected is the global sovereign credit risk network?," Journal of Banking & Finance, Elsevier, vol. 113(C).
    44. Luo, Jiawen & Ji, Qiang, 2018. "High-frequency volatility connectedness between the US crude oil market and China's agricultural commodity markets," Energy Economics, Elsevier, vol. 76(C), pages 424-438.
    45. Akbulut Nesrin & Ari Yakup, 2023. "TVP-VAR Frequency Connectedness Between the Foreign Exchange Rates of Non-Euro Area Member Countries," Folia Oeconomica Stetinensia, Sciendo, vol. 23(2), pages 1-23, December.
    46. Francis X. Diebold & Kamil Yilmaz, 2016. "Trans-Atlantic Equity Volatility Connectedness: U.S. and European Financial Institutions, 2004–2014," Journal of Financial Econometrics, Oxford University Press, vol. 14(1), pages 81-127.
    47. David I. Okorie, 2021. "A network analysis of electricity demand and the cryptocurrency markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 3093-3108, April.
    48. Sanjay Kumar Rout & Hrushikesh Mallick, 2021. "International interdependency of macroeconomic activities: a multivariate empirical analysis," International Economics and Economic Policy, Springer, vol. 18(2), pages 425-450, May.
    49. Ahelegbey, Daniel Felix, 2015. "The Econometrics of Bayesian Graphical Models: A Review With Financial Application," MPRA Paper 92634, University Library of Munich, Germany, revised 25 Apr 2016.
    50. Bettendorf, Timo & Heinlein, Reinhold, 2019. "Connectedness between G10 currencies: Searching for the causal structure," Discussion Papers 06/2019, Deutsche Bundesbank.
    51. Hahn Shik Lee & Woo Suk Lee, 2018. "Housing market volatility connectedness among G7 countries," Applied Economics Letters, Taylor & Francis Journals, vol. 25(3), pages 146-151, February.
    52. Zhang, Wenting & Hamori, Shigeyuki, 2021. "Crude oil market and stock markets during the COVID-19 pandemic: Evidence from the US, Japan, and Germany," International Review of Financial Analysis, Elsevier, vol. 74(C).
    53. Balcilar, Mehmet & Elsayed, Ahmed H. & Hammoudeh, Shawkat, 2023. "Financial connectedness and risk transmission among MENA countries: Evidence from connectedness network and clustering analysis1," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
    54. International Monetary Fund, 2018. "Brazil: Financial System Stability Assessment," IMF Staff Country Reports 2018/339, International Monetary Fund.
    55. Calderón-Colín, Roberto & Carmona Sánchez, Juan Francisco, 2023. "A multivariate analysis of SIEFORE daily returns," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 4(1).
    56. Bonaccolto, Giovanni & Caporin, Massimiliano & Maillet, Bertrand B., 2022. "Dynamic large financial networks via conditional expected shortfalls," European Journal of Operational Research, Elsevier, vol. 298(1), pages 322-336.
    57. Julián Andrada-Félix & Adrian Fernandez-Perez & Simón Sosvilla-Rivero, 2018. "Fear connectedness among asset classes," Applied Economics, Taylor & Francis Journals, vol. 50(39), pages 4234-4249, August.
    58. Warshaw, Evan, 2020. "Asymmetric volatility spillover between European equity and foreign exchange markets: Evidence from the frequency domain," International Review of Economics & Finance, Elsevier, vol. 68(C), pages 1-14.
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    1. Eyden Samunderu & Yvonne T. Murahwa, 2021. "Return Based Risk Measures for Non-Normally Distributed Returns: An Alternative Modelling Approach," JRFM, MDPI, vol. 14(11), pages 1-48, November.
    2. Atsushi Inoue & Barbara Rossi, 2019. "A New Approach to Measuring Economic Policy Shocks, with an Application to Conventional and Unconventional Monetary Policy," Working Papers 1082, Barcelona School of Economics.
    3. Minchul Shin & Molin Zhong, 2015. "Does Realized Volatility Help Bond Yield Density Prediction?," Finance and Economics Discussion Series 2015-115, Board of Governors of the Federal Reserve System (U.S.).
    4. Bruno Feunou & Jean-Sébastien Fontaine & Anh Le & Christian Lundblad, 2022. "Tractable Term Structure Models," Management Science, INFORMS, vol. 68(11), pages 8411-8429, November.
    5. Machava, Agostinho & Brännäs, Kurt, 2015. "Mozambican Monetary Policy and the Yield Curve of Treasury Bills - An Empirical Study," Umeå Economic Studies 918, Umeå University, Department of Economics.
    6. Creal, Drew D. & Wu, Jing Cynthia, 2015. "Estimation of affine term structure models with spanned or unspanned stochastic volatility," Journal of Econometrics, Elsevier, vol. 185(1), pages 60-81.
    7. Constantino Hevia & Martin Sola, 2018. "Bond risk premia and restrictions on risk prices," Department of Economics Working Papers 2018_03, Universidad Torcuato Di Tella.
    8. Michelle Lewis & C. John McDermott, 2016. "New Zealand's experience with changing its inflation target and the impact on inflation expectations," New Zealand Economic Papers, Taylor & Francis Journals, vol. 50(3), pages 343-361, September.

  3. Francis X. Diebold (ed.), 2012. "Financial Risk Measurement and Management," Books, Edward Elgar Publishing, number 14102.

    Cited by:

    1. Kyle Jurado & Sydney C. Ludvigson & Serena Ng, 2015. "Measuring Uncertainty," American Economic Review, American Economic Association, vol. 105(3), pages 1177-1216, March.
    2. Victor Olkhov, 2018. "Econophysics Beyond General Equilibrium: the Business Cycle Model," Papers 1804.04721, arXiv.org.
    3. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2011. "Financial Risk Measurement for Financial Risk Management," CREATES Research Papers 2011-37, Department of Economics and Business Economics, Aarhus University.
    4. Olkhov, Victor, 2018. "Economic Transactions Govern Business Cycles," MPRA Paper 88531, University Library of Munich, Germany, revised 19 Aug 2018.
    5. F. Lilla, 2017. "High Frequency vs. Daily Resolution: the Economic Value of Forecasting Volatility Models - 2nd ed," Working Papers wp1099, Dipartimento Scienze Economiche, Universita' di Bologna.
    6. Massacci, Daniele, 2014. "A two-regime threshold model with conditional skewed Student t distributions for stock returns," Economic Modelling, Elsevier, vol. 43(C), pages 9-20.
    7. Victor Olkhov, 2020. "Business Cycles as Collective Risk Fluctuations," Papers 2012.04506, arXiv.org.
    8. Victor Olkhov, 2018. "How Macro Transactions Describe the Evolution and Fluctuation of Financial Variables," IJFS, MDPI, vol. 6(2), pages 1-19, March.
    9. Dias, Alexandra, 2013. "Market capitalization and Value-at-Risk," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 5248-5260.
    10. BALTES Nicolae & DRAGOE Alexandra-Gabriela-Maria, 2017. "Estimating The Return Of The Financial Titles Of The Companies From The Manufacturing Industry, Listed On The Bucharest Stock Exchange," Revista Economica, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 69(3), pages 19-28, August.
    11. Serena Ng & Jonathan H. Wright, 2013. "Facts and Challenges from the Great Recession for Forecasting and Macroeconomic Modeling," NBER Working Papers 19469, National Bureau of Economic Research, Inc.
    12. Olkhov, Victor, 2018. "The Business Cycle Model Beyond General Equilibrium," MPRA Paper 87204, University Library of Munich, Germany.
    13. F. Lilla, 2016. "High Frequency vs. Daily Resolution: the Economic Value of Forecasting Volatility Models," Working Papers wp1084, Dipartimento Scienze Economiche, Universita' di Bologna.
    14. Olkhov, Victor, 2018. "Economic and Financial Transactions Govern Business Cycles," MPRA Paper 93269, University Library of Munich, Germany.
    15. Victor Olkhov, 2021. "To VaR, or Not to VaR, That is the Question," Papers 2101.08559, arXiv.org, revised Oct 2021.
    16. Francis X. Diebold, 2012. "A Personal Perspective on the Origin(s) and Development of “Big Data": The Phenomenon, the Term, and the Discipline, Second Version," PIER Working Paper Archive 13-003, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 26 Nov 2012.

  4. Francis X. Diebold & Neil A. Doherty & Richard J. Herring, 2010. "The Known, the Unknown, and the Unknowable in Financial Risk Management: Measurement and Theory Advancing Practice," Economics Books, Princeton University Press, edition 1, number 9223.

    Cited by:

    1. Michal Skorepa & Jakub Seidler, 2014. "Capital Buffers Based on Banks' Domestic Systemic Importance: Selected Issues," Research and Policy Notes 2014/01, Czech National Bank.
    2. Yuanrong Wang & Yinsen Miao & Alexander CY Wong & Nikita P Granger & Christian Michler, 2023. "Domain-adapted Learning and Interpretability: DRL for Gas Trading," Papers 2301.08359, arXiv.org, revised Sep 2023.
    3. Michal Skorepa, 2014. "Concurrent Capital Buffers in a Banking Group," Occasional Publications - Chapters in Edited Volumes, in: CNB Financial Stability Report 2013/2014, chapter 0, pages 128-136, Czech National Bank.
    4. Christian Hugo Hoffmann, 2017. "Towards Understanding Dynamic Complexity in Financial Systems Structure-based Explanatory Modelling of Risks," Systems Research and Behavioral Science, Wiley Blackwell, vol. 34(6), pages 728-745, November.
    5. Ross Brown & Ronald V Kalafsky & Suzanne Mawson & Lori Davies, 2020. "Shocks, uncertainty and regional resilience: The case of Brexit and Scottish SMEs," Local Economy, London South Bank University, vol. 35(7), pages 655-675, November.
    6. Viscusi, W. Kip & Zeckhauser, Richard, 2014. "Regulating Ambiguous Risks: The Less Than Rational Regulation of Pharmaceuticals," Working Paper Series rwp14-005, Harvard University, John F. Kennedy School of Government.
    7. Gabel Taggart, 2023. "Taking stock of systems for organizing existential and global catastrophic risks: Implications for policy," Global Policy, London School of Economics and Political Science, vol. 14(3), pages 489-499, June.
    8. Stéphane Albert & Hervé Alexandre, 2018. "Banks’ earnings: Empirical evidence of the influence of economic and financial market factors," Review of Financial Economics, John Wiley & Sons, vol. 36(2), pages 97-116, April.
    9. Michael Hanemann, 2010. "The Impact of Climate Change: An Economic Perspective," Chapters, in: Emilio Cerdá Tena & Xavier Labandeira (ed.), Climate Change Policies, chapter 2, Edward Elgar Publishing.
    10. Gordon L Clark, 2012. "Pensions or Property?," Environment and Planning A, , vol. 44(5), pages 1185-1199, May.
    11. Jingnan Chen & Mark D. Flood & Richard B. Sowers, 2015. "Measuring the Unmeasurable: An Application of Uncertainty Quantification to Financial Portfolios," Working Papers 15-19, Office of Financial Research, US Department of the Treasury.
    12. Ekaterina Svetlova & Henk van Elst, 2012. "How is non-knowledge represented in economic theory?," Papers 1209.2204, arXiv.org.
    13. Gordon L. Clark, 2014. "Information, knowledge, and investing in offshore financial markets," Journal of Sustainable Finance & Investment, Taylor & Francis Journals, vol. 4(4), pages 299-320, October.
    14. Oksana Hoshovska & Zhanna Poplavska & Jana Kajanova & Olena Trevoho, 2023. "Random Risk Factors Influencing Cash Flows: Modifying RADR," Mathematics, MDPI, vol. 11(2), pages 1-22, January.
    15. Chuliá, Helena & Guillén, Montserrat & Uribe, Jorge M., 2017. "Measuring uncertainty in the stock market," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 18-33.
    16. Albert, Stéphane, 2015. "US bank holding companies: Structure of activities and performance through the cycles," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 253-269.
    17. Michal Skorepa & Jakub Seidler, 2013. "An Additional capital requirements based on the domestic systemic importance of a bank," Occasional Publications - Chapters in Edited Volumes, in: CNB Financial Stability Report 2012/2013, chapter 0, pages 96-102, Czech National Bank.
    18. Jaime Terceiro Lomba, 2019. "The energy transition and the financial system," Financial Stability Review, Banco de España, issue NOV.
    19. Andreas Richter & Thomas C. Wilson, 2020. "Covid-19: implications for insurer risk management and the insurability of pandemic risk," The Geneva Risk and Insurance Review, Palgrave Macmillan;International Association for the Study of Insurance Economics (The Geneva Association), vol. 45(2), pages 171-199, September.
    20. Amandha Ganegoda & John Evans, 2014. "A framework to manage the measurable, immeasurable and the unidentifiable financial risk," Australian Journal of Management, Australian School of Business, vol. 39(1), pages 5-34, February.
    21. Christian Hugo Hoffmann & Charles Djordjevic, 2020. "Complexity, Power Laws and a Humean Argument in Risk Management: The Fundamental Inadequacy of Probability Theory as a Foundation for Modeling Complex Risk in Banking," Homo Oeconomicus: Journal of Behavioral and Institutional Economics, Springer, vol. 37(3), pages 155-182, December.
    22. PARYS, Wilfried, 2020. "David Ricardo, the Stock Exchange, and the Battle of Waterloo: Samuelsonian legends lack historical evidence," Working Papers 2020009, University of Antwerp, Faculty of Business and Economics.

  5. Francis X. Diebold & Glenn D. Rudebusch, 1999. "Business Cycles: Durations, Dynamics, and Forecasting," Economics Books, Princeton University Press, edition 1, number 6636.

    Cited by:

    1. Gordon W. Crawford & Michael C. Fratantoni, 2003. "Assessing the Forecasting Performance of Regime‐Switching, ARIMA and GARCH Models of House Prices," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 31(2), pages 223-243, June.
    2. Bao, Te & Ma, Mengzhong & Wen, Yonggang, 2023. "Herding in the non-fungible token (NFT) market," Journal of Behavioral and Experimental Finance, Elsevier, vol. 39(C).
    3. Philip Lowe, 2002. "Credit risk measurement and procyclicality," BIS Working Papers 116, Bank for International Settlements.
    4. Olkhov, Victor, 2019. "New Essentials of Economic Theory," MPRA Paper 95065, University Library of Munich, Germany.
    5. Guilhem Bentoglio & Jacky Fayolle & Matthieu Lemoine, 2002. "Unity and Plurality of the European Cycle," SciencePo Working papers Main hal-03458584, HAL.
    6. Mr. Thomas Helbling & Mr. Tamim Bayoumi, 2003. "Are they All in the Same Boat? the 2000-2001 Growth Slowdown and the G-7 Business Cycle Linkages," IMF Working Papers 2003/046, International Monetary Fund.
    7. Chang-Jin Kim & Charles Nelson, 1999. "A Bayesian Approach to Testing for Markov Switching in Univariate and Dynamic Factor Models," Working Papers 0035, University of Washington, Department of Economics.
    8. Sonia de Lucas Santos & M. Jesús Delgado Rodríguez & Inmaculada Álvarez Ayuso & José Luis Cendejas Bueno, 2011. "Los ciclos económicos internacionales: antecedentes y revisión de la literatura," Cuadernos de Economía - Spanish Journal of Economics and Finance, Asociación Cuadernos de Economía, vol. 34(95), pages 73-84, Agosto.
    9. Victor Olkhov, 2018. "Econophysics Beyond General Equilibrium: the Business Cycle Model," Papers 1804.04721, arXiv.org.
    10. Stan Du Plessis, 2006. "Reconsidering the business cycle and stabilisation policies in South Africa," Working Papers 010, Economic Research Southern Africa.
    11. Charles Ka Yui Leung & Nan-Kuang Chen & Chih-Chiang Hsu, 2004. "Structural Break or Asymmetry? An Empirical Study of the Stock Wealth Effect on Consumption," Econometric Society 2004 Far Eastern Meetings 690, Econometric Society.
    12. Guilhem Bentoglio & Jacky Fayolle & Matthieu Lemoine, 2001. "Unité et pluralité du cycle européen," Revue de l'OFCE, Presses de Sciences-Po, vol. 78(3), pages 9-73.
    13. John B. Guerard, 2024. "Sir David Hendry: An Appreciation from Wall Street and What Macroeconomics Got Right," Working Papers 2024-001, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting, revised Feb 2024.
    14. Olkhov, Victor, 2018. "Economic Transactions Govern Business Cycles," MPRA Paper 88531, University Library of Munich, Germany, revised 19 Aug 2018.
    15. Mehdi Pedram, 2011. "Optimal monetary policy in the monetary union: effects on business cycles," OPEC Energy Review, Organization of the Petroleum Exporting Countries, vol. 35(1), pages 90-117, March.
    16. Gustavo Cabrera González & Adrián de León Arias, 2021. "Dinámica anticipada del PIB trimestral en México ante shocks negativos derivados de factores debidos a la crisis sanitaria del covid-19," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 16(1), pages 1-15, Enero - M.
    17. Monica Billio & Jacques Anas & Laurent Ferrara & Marco Lo Duca, 2007. "A turning point chronology for the Euro-zone," Working Papers 2007_33, Department of Economics, University of Venice "Ca' Foscari".
    18. Michael D. Bordo & Thomas Helbling, 2003. "Have National Business Cycles Become More Synchronized?," NBER Working Papers 10130, National Bureau of Economic Research, Inc.
    19. Roumen Vesselinov, 2012. "New Composite Indicators for Bulgarian Business Cycle," International Journal of Business and Economic Sciences Applied Research (IJBESAR), International Hellenic University (IHU), Kavala Campus, Greece (formerly Eastern Macedonia and Thrace Institute of Technology - EMaTTech), vol. 5(2), pages 101-111, August.
    20. Victor Olkhov, 2020. "Business Cycles as Collective Risk Fluctuations," Papers 2012.04506, arXiv.org.
    21. Vougas, Dimitrios V., 2007. "Is the trend in post-WW II US real GDP uncertain or non-linear?," Economics Letters, Elsevier, vol. 94(3), pages 348-355, March.
    22. Mayes, David & Virén, Matti, 2004. "Asymmetries in the Euro area economy," Bank of Finland Research Discussion Papers 9/2004, Bank of Finland.
    23. Panchanan Das, 2015. "Entrepreneurial Impulse, Investment Behavior, and Economic Fluctuations–A VAR Analysis with Indian Data," Asian Development Review, MIT Press, vol. 32(2), pages 1-17, September.
    24. Eric Girardin, 2004. "Regime-Dependent Synchronization of Growth Cycles between Japan and East Asia," Asian Economic Papers, MIT Press, vol. 3(3), pages 147-176.
    25. Ghysels, Eric & Plazzi, Alberto & Valkanov, Rossen & Torous, Walter, 2013. "Forecasting Real Estate Prices," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 509-580, Elsevier.
    26. Zihao Wang & Kun Li & Steve Q. Xia & Hongfu Liu, 2021. "Economic Recession Prediction Using Deep Neural Network," Papers 2107.10980, arXiv.org.
    27. Matthieu Lemoine & Florian Pelgrin, 2003. "Introduction aux modèles espace-état et au filtre de Kalman," Revue de l'OFCE, Presses de Sciences-Po, vol. 86(3), pages 203-229.
    28. Olkhov, Victor, 2019. "New Essentials of Economic Theory III. Economic Applications," MPRA Paper 94053, University Library of Munich, Germany.
    29. Odia Ndongo, Yves Francis, 2006. "Datation du Cycle du PIB Camerounais entre 1960 et 2003," MPRA Paper 552, University Library of Munich, Germany.
    30. Herman J. Bierens, 2000. "Complex Unit Roots and Business Cycles: Are They Real?," Econometric Society World Congress 2000 Contributed Papers 0197, Econometric Society.
    31. Jagjit S. Chadha & Lucio Sarno, 2002. "Short‐ and long‐run price level uncertainty under different monetary policy regimes: an international comparison," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 64(3), pages 183-212, July.
    32. Mercè Sala-Rios & Teresa Torres-Solé & Mariona Farré-Perdiguer, 2016. "Credit and business cycles’ relationship: evidence from Spain," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 15(3), pages 149-171, December.
    33. Adrian Penalver & Daniele Siena, 2021. "The Deflationary Bias of the ZLB and the FED’s Strategic Response," Working papers 843, Banque de France.
    34. Chian, Abraham C.-L. & Rempel, Erico L. & Rogers, Colin, 2006. "Complex economic dynamics: Chaotic saddle, crisis and intermittency," Chaos, Solitons & Fractals, Elsevier, vol. 29(5), pages 1194-1218.
    35. Gustavo Cabrera González, 2019. "Modeling and Projection of the Mexican Exchange Rate (Peso/Dollar): a Bayesian Approach for Model Selection," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 14(2), pages 203-219, Abril-Jun.
    36. Viv. B Hall & McDermott C. John, 2004. "Regional Business Cycles in New Zealand: Do they exist? What might drive them?," ERSA conference papers ersa04p200, European Regional Science Association.
    37. Zarnowitz, Victor & Ozyildirim, Ataman, 2006. "Time series decomposition and measurement of business cycles, trends and growth cycles," Journal of Monetary Economics, Elsevier, vol. 53(7), pages 1717-1739, October.
    38. Olkhov, Victor, 2018. "The Business Cycle Model Beyond General Equilibrium," MPRA Paper 87204, University Library of Munich, Germany.
    39. Frédérick Demers & David Dupuis, 2005. "Forecasting Canadian GDP: Region-Specific versus Countrywide Information," Staff Working Papers 05-31, Bank of Canada.
    40. Olkhov, Victor, 2018. "Economic and Financial Transactions Govern Business Cycles," MPRA Paper 93269, University Library of Munich, Germany.
    41. Martha Misas & María Teresa Ramírez, 2006. "Colombian economic growth under Markov switching regimes with endogenous transition probabilities," Borradores de Economia 425, Banco de la Republica de Colombia.
    42. Islas C., Alejandro & Cortez, Willy Walter, 2018. "Can the informal sector affect the relationship between unemployment and output? An analysis of the Mexican case," Revista CEPAL, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL), December.
    43. Harry X. Wu & Eric Girardin, 2016. "The ‘new’ normal is ‘old’ in China: Very late catching up and return to the (pre-WTO) old normal," EcoMod2016 9721, EcoMod.
    44. Isaic Radu & Smirna Tudor & Paun Cristian, 2019. "A critical view on the mainstream theory of economic cycles," Management & Marketing, Sciendo, vol. 14(1), pages 48-58, March.
    45. Glenn D. Rudebusch, 2016. "Will the economic recovery die of old age?," FRBSF Economic Letter, Federal Reserve Bank of San Francisco.
    46. Meriam BouAli & Adnen Ben Nasr & Abdelwahed Trabelsi, 2016. "A Nonlinear Approach for Modeling and Forecasting US Business Cycles," International Economic Journal, Taylor & Francis Journals, vol. 30(1), pages 39-74, March.
    47. Vincent, BODART & Konstantin, KHOLODILIN & Fati, SHADMAN-MEHTA, 2005. "Identifying and Forecasting the Turning Points of the Belgian Business Cycle with Regime-Switching and Logit Models," Discussion Papers (ECON - Département des Sciences Economiques) 2005006, Université catholique de Louvain, Département des Sciences Economiques.
    48. Fernando H.P.S Mendes & João Frois Caldeira & Guilherme Valle Moura, 2019. "Duration-dependent Markov-switching model: an empirical study for the Brazilian business cycle," Economics Bulletin, AccessEcon, vol. 39(1), pages 676-685.
    49. Minakshy Iyer, 2006. "An Index of Uncertainty for Business Cycle Leading Indicators," Working Papers id:751, eSocialSciences.
    50. Tobias F. Rötheli, 2018. "Should business rely on business cycle forecasting?," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 26(1), pages 121-133, March.
    51. Mercè Sala-Rios & Teresa Torres-Solé & Mariona Farré-Perdiguer, 2018. "Immigrants’ employment and the business cycle in Spain: taking account of gender and origin," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 35(2), pages 463-490, August.
    52. Rizvi, Syed Aun R. & Arshad, Shaista, 2017. "Analysis of the efficiency–integration nexus of Japanese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 470(C), pages 296-308.
    53. Süssmuth Bernd & Woitek Ulrich, 2005. "Some New Results on Industrial Sector Mode-Locking and Business Cycle Formation," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(3), pages 1-35, September.

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