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Allan Timmermann

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. 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.

    Mentioned in:

    1. Combining Forecasts
      by Clive Jones in Business Forecasting on 2012-06-26 00:30:56
  2. Pesaran, M. Hashem & Timmermann, Allan, 2007. "Selection of estimation window in the presence of breaks," Journal of Econometrics, Elsevier, vol. 137(1), pages 134-161, March.

    Mentioned in:

    1. Forecasting GDP in the presence of breaks: when is the past is a good guide to the future?
      by bankunderground in Bank Underground on 2015-08-20 11:30:00
    2. Forecasting GDP in the presence of breaks: when is the past a good guide to the future?
      by Guest Author in The Big Picture on 2015-09-01 14:00:11
  3. Author Profile
    1. Top Forecasting Institutions and Researchers According to IDEAS!
      by Clive Jones in Business Forecasting on 2013-06-28 01:43:46
    2. Ranking California Economists as of May 2015
      by Matthew Kahn in Environmental and Urban Economics on 2015-06-04 02:25:00
    3. Peers at Work as of August 2016
      by Matthew Kahn in Environmental and Urban Economics on 2016-09-04 19:36:00

RePEc Biblio mentions

As found on the RePEc Biblio, the curated bibliography of Economics:
  1. G. Elliott & C. Granger & A. Timmermann (ed.), 2006. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 1, number 1.

    Mentioned in:

    1. > Econometrics > Forecasting

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. Allan Timmermann & Massimo Guidolin, 2006. "An econometric model of nonlinear dynamics in the joint distribution of stock and bond returns," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 1-22.

    Mentioned in:

    1. An econometric model of nonlinear dynamics in the joint distribution of stock and bond returns (Journal of Applied Econometrics 2006) in ReplicationWiki ()
  2. Timmermann, Allan, 1995. "Cointegration Tests of Present Value Models with a Time-Varying Discount Factor," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(1), pages 17-31, Jan.-Marc.

    Mentioned in:

    1. Cointegration tests of present value models with a time-varying discount factor (Journal of Applied Econometrics 1995) in ReplicationWiki ()

Working papers

  1. Simon Smith & Allan Timmermann & Jonathan H. Wright, 2023. "Breaks in the Phillips Curve: Evidence from Panel Data," NBER Working Papers 31153, National Bureau of Economic Research, Inc.

    Cited by:

    1. Ferri, Piero & Cristini, Annalisa & Tramontana, Fabio, 2023. "Meta-models of the Phillips curve and income distribution," Journal of Economic Behavior & Organization, Elsevier, vol. 213(C), pages 215-232.
    2. Pierpaolo Benigno & Gauti B. Eggertsson, 2023. "It’s Baaack: The Surge in Inflation in the 2020s and the Return of the Non-Linear Phillips Curve," NBER Working Papers 31197, National Bureau of Economic Research, Inc.

  2. Peter Reinhard HANSEN & Allan TIMMERMANN, 2012. "Choice of Sample Split in Out-of-Sample Forecast Evaluation," Economics Working Papers ECO2012/10, European University Institute.

    Cited by:

    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.
    2. 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.
    3. Kuntz, Laura-Chloé, 2020. "Beta dispersion and market timing," Journal of Empirical Finance, Elsevier, vol. 59(C), pages 235-256.
    4. Papapostolou, Nikos C. & Pouliasis, Panos K. & Nomikos, Nikos K. & Kyriakou, Ioannis, 2016. "Shipping investor sentiment and international stock return predictability," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 96(C), pages 81-94.
    5. 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.
    6. Chen, Jian & Jiang, Fuwei & Liu, Yangshu & Tu, Jun, 2017. "International volatility risk and Chinese stock return predictability," Journal of International Money and Finance, Elsevier, vol. 70(C), pages 183-203.
    7. Firmin Doko Tchatoka & Qazi Haque, 2020. "On bootstrapping tests of equal forecast accuracy for nested models," Economics Discussion / Working Papers 20-06, The University of Western Australia, Department of Economics.
    8. 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.
    9. Chen, Jian & Tang, Guohao & Yao, Jiaquan & Zhou, Guofu, 2023. "Employee sentiment and stock returns," Journal of Economic Dynamics and Control, Elsevier, vol. 149(C).
    10. Xing, Li-Min & Zhang, Yue-Jun, 2022. "Forecasting crude oil prices with shrinkage methods: Can nonconvex penalty and Huber loss help?," Energy Economics, Elsevier, vol. 110(C).
    11. Biqing Cai & Jiti Gao, 2017. "A simple nonlinear predictive model for stock returns," Monash Econometrics and Business Statistics Working Papers 18/17, Monash University, Department of Econometrics and Business Statistics.
    12. Timmermann, Allan, 2018. "Forecasting Methods in Finance," CEPR Discussion Papers 12692, C.E.P.R. Discussion Papers.
    13. Zhang, Pinyi & Ci, Bicong, 2020. "Deep belief network for gold price forecasting," Resources Policy, Elsevier, vol. 69(C).
    14. Hatice Gökçe Karasoy Can & Çağlar Yüncüler, 2018. "The Explanatory Power and the Forecast Performance of Consumer Confidence Indices for Private Consumption Growth in Turkey," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 54(9), pages 2136-2152, July.
    15. Narayan, Paresh Kumar & Bannigidadmath, Deepa, 2015. "Are Indian stock returns predictable?," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 506-531.
    16. Cotter, John & Eyiah-Donkor, Emmanuel & Potì, Valerio, 2023. "Commodity futures return predictability and intertemporal asset pricing," Journal of Commodity Markets, Elsevier, vol. 31(C).
    17. Chen, Jian & Jiang, Fuwei & Xue, Shuyu & Yao, Jiaquan, 2019. "The world predictive power of U.S. equity market skewness risk," Journal of International Money and Finance, Elsevier, vol. 96(C), pages 210-227.
    18. John G. Fernald & Eric Hsu & Mark M. Spiegel, 2019. "Is China Fudging Its GDP Figures? Evidence from Trading Partner Data," Working Paper Series 2019-19, Federal Reserve Bank of San Francisco.
    19. Thomadakis, Apostolos, 2016. "Do Combination Forecasts Outperform the Historical Average? Economic and Statistical Evidence," MPRA Paper 71589, University Library of Munich, Germany.
    20. Harri Pönkä, 2017. "Predicting the direction of US stock markets using industry returns," Empirical Economics, Springer, vol. 52(4), pages 1451-1480, June.
    21. Jiali Fang & Ben Jacobsen & Yafeng Qin, 2014. "Predictability of the simple technical trading rules: An out‐of‐sample test," Review of Financial Economics, John Wiley & Sons, vol. 23(1), pages 30-45, January.
    22. Corradi, Valentina & Swanson, Norman R., 2014. "Testing for structural stability of factor augmented forecasting models," Journal of Econometrics, Elsevier, vol. 182(1), pages 100-118.
    23. Christian Hutter, 2020. "A new indicator for nowcasting employment subject to social security contributions in Germany," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 54(1), pages 1-10, December.
    24. Chiang, I-Hsuan Ethan & Liao, Yin & Zhou, Qing, 2021. "Modeling the cross-section of stock returns using sensible models in a model pool," Journal of Empirical Finance, Elsevier, vol. 60(C), pages 56-73.
    25. Camila Epprecht & Dominique Guegan & Álvaro Veiga, 2013. "Comparing variable selection techniques for linear regression: LASSO and Autometrics," Documents de travail du Centre d'Economie de la Sorbonne 13080, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    26. Peter Reinhard Hansen & Allan Timmermann, 2015. "Equivalence Between Out‐of‐Sample Forecast Comparisons and Wald Statistics," Econometrica, Econometric Society, vol. 83, pages 2485-2505, November.
    27. Duangnate, Kannika & Mjelde, James W., 2017. "Comparison of data-rich and small-scale data time series models generating probabilistic forecasts: An application to U.S. natural gas gross withdrawals," Energy Economics, Elsevier, vol. 65(C), pages 411-423.
    28. Denisa Georgiana Banulescu & Gilbert Colletaz & Christophe Hurlin & Sessi Tokpavi, 2013. "High-Frequency Risk Measures," Working Papers halshs-00859456, HAL.
    29. Algaba, Andres & Boudt, Kris, 2017. "Generalized financial ratios to predict the equity premium," Economic Modelling, Elsevier, vol. 66(C), pages 244-257.
    30. Swasti R. Khuntia & Jose L. Rueda & Mart A.M.M. Van der Meijden, 2018. "Long-Term Electricity Load Forecasting Considering Volatility Using Multiplicative Error Model," Energies, MDPI, vol. 11(12), pages 1-19, November.
    31. Gebka, Bartosz & Wohar, Mark E., 2019. "Stock return distribution and predictability: Evidence from over a century of daily data on the DJIA index," International Review of Economics & Finance, Elsevier, vol. 60(C), pages 1-25.
    32. Stephen A. Gorman & Frank J. Fabozzi, 2021. "The ABC’s of the alternative risk premium: academic roots," Journal of Asset Management, Palgrave Macmillan, vol. 22(6), pages 405-436, October.
    33. Zhang, Qin & Ni, He & Xu, Hao, 2023. "Nowcasting Chinese GDP in a data-rich environment: Lessons from machine learning algorithms," Economic Modelling, Elsevier, vol. 122(C).
    34. Goodness C. Aye & Frederick W. Deale & Rangan Gupta, 2014. "Does Debt Ceiling and Government Shutdown Help in Forecasting the US Equity Risk Premium?," Working Papers 201422, University of Pretoria, Department of Economics.
    35. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1203-1324, Elsevier.
    36. Allan Timmermann, 2018. "Forecasting Methods in Finance," Annual Review of Financial Economics, Annual Reviews, vol. 10(1), pages 449-479, November.
    37. Hui Chen & Scott Joslin & Sophie X. Ni, 2019. "Demand for Crash Insurance, Intermediary Constraints, and Risk Premia in Financial Markets," NBER Working Papers 25573, National Bureau of Economic Research, Inc.
    38. Baetje, Fabian & Menkhoff, Lukas, 2016. "Equity premium prediction: Are economic and technical indicators unstable?," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1193-1207.
    39. Biqing Cai & Jiti Gao, 2013. "Hermite Series Estimation in Nonlinear Cointegrating Models," Monash Econometrics and Business Statistics Working Papers 17/13, Monash University, Department of Econometrics and Business Statistics.
    40. He, Kaijian & Liu, Youjin & Yu, Lean & Lai, Kin Keung, 2016. "Multiscale dependence analysis and portfolio risk modeling for precious metal markets," Resources Policy, Elsevier, vol. 50(C), pages 224-233.
    41. Li, Chenchen & Wang, Yudong & Wu, Chongfeng, 2022. "Oil implied volatility and expected stock returns along the worldwide supply chain," Energy Economics, Elsevier, vol. 114(C).
    42. Bätje, Fabian & Menkhoff, Lukas, 2016. "Predicting the equity premium via its components," VfS Annual Conference 2016 (Augsburg): Demographic Change 145789, Verein für Socialpolitik / German Economic Association.
    43. Sakkas, Athanasios & Tessaromatis, Nikolaos, 2020. "Factor based commodity investing," Journal of Banking & Finance, Elsevier, vol. 115(C).
    44. Brooks, Chris & Burke, Simon P. & Stanescu, Silvia, 2016. "Finite sample weighting of recursive forecast errors," International Journal of Forecasting, Elsevier, vol. 32(2), pages 458-474.
    45. Baltas, Nick & Karyampas, Dimitrios, 2018. "Forecasting the equity risk premium: The importance of regime-dependent evaluation," Journal of Financial Markets, Elsevier, vol. 38(C), pages 83-102.
    46. Markiewicz, Agnieszka & Pick, Andreas, 2014. "Adaptive learning and survey data," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PB), pages 685-707.
    47. Li, Jia & Patton, Andrew J., 2018. "Asymptotic inference about predictive accuracy using high frequency data," Journal of Econometrics, Elsevier, vol. 203(2), pages 223-240.
    48. Huang, Yisu & Xu, Weiju & Huang, Dengshi & Zhao, Chenchen, 2023. "Chinese crude oil futures volatility and sustainability: An uncertainty indices perspective," Resources Policy, Elsevier, vol. 80(C).
    49. Jiang, Fuwei & Lee, Joshua & Martin, Xiumin & Zhou, Guofu, 2019. "Manager sentiment and stock returns," Journal of Financial Economics, Elsevier, vol. 132(1), pages 126-149.
    50. Ruan, Xinfeng & Zhang, Jin E., 2018. "Risk-neutral moments in the crude oil market," Energy Economics, Elsevier, vol. 72(C), pages 583-600.
    51. Lin, Qi & Lin, Xi, 2021. "Cash conversion cycle and aggregate stock returns," Journal of Financial Markets, Elsevier, vol. 52(C).
    52. Kolev, Gueorgui I. & Karapandza, Rasa, 2017. "Out-of-sample equity premium predictability and sample split–invariant inference," Journal of Banking & Finance, Elsevier, vol. 84(C), pages 188-201.
    53. He, Kaijian & Wang, Lijun & Zou, Yingchao & Lai, Kin Keung, 2014. "Value at risk estimation with entropy-based wavelet analysis in exchange markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 408(C), pages 62-71.
    54. Camila Epprecht & Dominique Guegan & Álvaro Veiga & Joel Correa da Rosa, 2017. "Variable selection and forecasting via automated methods for linear models: LASSO/adaLASSO and Autometrics," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00917797, HAL.
    55. Chen, Jian & Jiang, Fuwei & Li, Hongyi & Xu, Weidong, 2016. "Chinese stock market volatility and the role of U.S. economic variables," Pacific-Basin Finance Journal, Elsevier, vol. 39(C), pages 70-83.
    56. Huang, Dashan & Li, Jiangyuan & Wang, Liyao & Zhou, Guofu, 2020. "Time series momentum: Is it there?," Journal of Financial Economics, Elsevier, vol. 135(3), pages 774-794.
    57. 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.
    58. Richard A. Ashley & Kwok Ping Tsang, 2014. "Credible Granger-Causality Inference with Modest Sample Lengths: A Cross-Sample Validation Approach," Econometrics, MDPI, vol. 2(1), pages 1-20, March.
    59. He, Kaijian & Yu, Lean & Tang, Ling, 2015. "Electricity price forecasting with a BED (Bivariate EMD Denoising) methodology," Energy, Elsevier, vol. 91(C), pages 601-609.
    60. Kuntz, Laura-Chloé, 2020. "Beta dispersion and market timing," Discussion Papers 46/2020, Deutsche Bundesbank.
    61. Ewa Feder-Sempach & Piotr Szczepocki & Wiesław Dębski, 2023. "What if beta is not stable? Applying the Kalman filter to risk estimates of top US companies over the long time horizon," Bank i Kredyt, Narodowy Bank Polski, vol. 54(1), pages 25-44.
    62. Fernald, John G. & Hsu, Eric & Spiegel, Mark M., 2021. "Reprint: Is China fudging its GDP figures? Evidence from trading partner data," Journal of International Money and Finance, Elsevier, vol. 114(C).
    63. Jing Tian & Qing Zhou, 2018. "Improving equity premium forecasts by incorporating structural break uncertainty," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(S1), pages 619-656, November.
    64. Rossi, Barbara & Gürkaynak, Refet & Kısacıkoğlu, Burçin, 2013. "Do DSGE Models Forecast More Accurately Out-of-Sample than VAR Models?," CEPR Discussion Papers 9576, C.E.P.R. Discussion Papers.
    65. James Lightwood & Steve Anderson & Stanton A Glantz, 2020. "Predictive validation and forecasts of short-term changes in healthcare expenditure associated with changes in smoking behavior in the United States," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-18, January.

  3. Timmermann, Allan & Patton, Andrew, 2011. "Forecast Rationality Tests Based on Multi-Horizon Bounds," CEPR Discussion Papers 8194, C.E.P.R. Discussion Papers.

    Cited by:

    1. Stan Hurn & Jing Tian & Lina Xu, 2021. "Assessing the Informational Content of Official Australian Bureau of Meteorology Forecasts of Wind Speed," The Economic Record, The Economic Society of Australia, vol. 97(319), pages 525-547, December.
    2. Natsuki Arai, 2016. "Evaluating the Efficiency of the FOMC's New Economic Projections," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 48(5), pages 1019-1049, August.
    3. Reichlin, Lucrezia & Giannone, Domenico & Modugno, Michele & Banbura, Marta, 2012. "Now-casting and the real-time data flow," CEPR Discussion Papers 9112, C.E.P.R. Discussion Papers.
    4. Barbara Rossi & Tatevik Sekhposyan, 2016. "Forecast Rationality Tests in the Presence of Instabilities, with Applications to Federal Reserve and Survey Forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(3), pages 507-532, April.
    5. Lukas Hoesch & Barbara Rossi & Tatevik Sekhposyan, 2023. "Has the Information Channel of Monetary Policy Disappeared? Revisiting the Empirical Evidence," American Economic Journal: Macroeconomics, American Economic Association, vol. 15(3), pages 355-387, July.
    6. Michael P. Clements, 2022. "Forecaster Efficiency, Accuracy, and Disagreement: Evidence Using Individual‐Level Survey Data," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(2-3), pages 537-568, March.
    7. Thomas Jobert & Lionel Persyn, 2012. "Quelques constats sur les prévisions conjoncturelles de la croissance française," Revue d'économie politique, Dalloz, vol. 122(6), pages 833-849.
    8. 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.
    9. Ardia, David & Hoogerheide, Lennart F., 2014. "GARCH models for daily stock returns: Impact of estimation frequency on Value-at-Risk and Expected Shortfall forecasts," Economics Letters, Elsevier, vol. 123(2), pages 187-190.
    10. Arai, Natsuki, 2014. "Using forecast evaluation to improve the accuracy of the Greenbook forecast," International Journal of Forecasting, Elsevier, vol. 30(1), pages 12-19.
    11. 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.
    12. Manganelli, Simone, 2016. "Deciding with judgment," Working Paper Series 1947, European Central Bank.
    13. Faust, Jon & Wright, Jonathan H., 2013. "Forecasting Inflation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 2-56, Elsevier.
    14. Clements, Michael P. & Reade, J. James, 2020. "Forecasting and forecast narratives: The Bank of England Inflation Reports," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1488-1500.
    15. Nathan Goldstein & Ben‐Zion Zilberfarb, 2023. "The closer we get, the better we are?," Economic Inquiry, Western Economic Association International, vol. 61(2), pages 364-376, April.
    16. Todd E. Clark & Michael W. McCracken, 2011. "Advances in forecast evaluation," Working Papers (Old Series) 1120, Federal Reserve Bank of Cleveland.
    17. Han Liu & Yongjing Wang & Haiyan Song & Ying Liu, 2023. "Measuring tourism demand nowcasting performance using a monotonicity test," Tourism Economics, , vol. 29(5), pages 1302-1327, August.
    18. G. Kontogeorgos & K. Lambrias, 2022. "Evaluating the Eurosystem/ECB staff macroeconomic projections: The first 20 years," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 213-229, March.
    19. Timmermann, Allan & Zhu, Yinchu, 2019. "Comparing Forecasting Performance with Panel Data," CEPR Discussion Papers 13746, C.E.P.R. Discussion Papers.
    20. Manganelli, Simone, 2021. "Statistical decision functions with judgment," Working Paper Series 2512, European Central Bank.
    21. Siddhartha S. Bora & Ani L. Katchova & Todd H. Kuethe, 2023. "The accuracy and informativeness of agricultural baselines," American Journal of Agricultural Economics, John Wiley & Sons, vol. 105(4), pages 1116-1148, August.
    22. Roberto Casarin, 2014. "A Note on Tractable State-Space Model for Symmetric Positive-Definite Matrices," Working Papers 2014:23, Department of Economics, University of Venice "Ca' Foscari".
    23. Barbara Rossi, 2014. "Comment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(4), pages 510-514, October.
    24. Raïsa Basselier & David Antonio Liedo & Geert Langenus, 2018. "Nowcasting Real Economic Activity in the Euro Area: Assessing the Impact of Qualitative Surveys," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 14(1), pages 1-46, April.
    25. Barbara Rossi, 2011. "Comment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 25-29, August.
    26. Manzan, Sebastiano, 2021. "Are professional forecasters Bayesian?," Journal of Economic Dynamics and Control, Elsevier, vol. 123(C).
    27. Michael Clements, 2016. "Are Macro-Forecasters Essentially The Same? An Analysis of Disagreement, Accuracy and Efficiency," ICMA Centre Discussion Papers in Finance icma-dp2016-08, Henley Business School, University of Reading.
    28. Paulina Ziembińska, 2021. "Quality of Tests of Expectation Formation for Revised Data," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 13(4), pages 405-453, December.
    29. Jmaes McNeil, 2020. "Monetary policy and the term structure of Inflation expectations with information frictions," Working Papers daleconwp2020-07, Dalhousie University, Department of Economics.
    30. Messina, Jeffrey D. & Sinclair, Tara M. & Stekler, Herman, 2015. "What can we learn from revisions to the Greenbook forecasts?," Journal of Macroeconomics, Elsevier, vol. 45(C), pages 54-62.
    31. D'Haultfoeuille, Xavier & Gaillac, Christophe & Maurel, Arnaud, 2021. "Rationalizing Rational Expectations: Characterizations and Tests," TSE Working Papers 21-1211, Toulouse School of Economics (TSE).
    32. Thomas L. Hogan, 2022. "The calculus of dissent: Bias and diversity in FOMC projections," Public Choice, Springer, vol. 191(1), pages 105-135, April.
    33. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1203-1324, Elsevier.
    34. Lukasz Gatarek & Lennart Hoogerheide & Koen Hooning & Herman K. van Dijk, 2013. "Censored Posterior and Predictive Likelihood in Left-Tail Prediction for Accurate Value at Risk Estimation," Tinbergen Institute Discussion Papers 13-060/III, Tinbergen Institute, revised 06 Mar 2014.
    35. Nieto, Maria Rosa & Ruiz, Esther, 2016. "Frontiers in VaR forecasting and backtesting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 475-501.
    36. Kontogeorgos, Georgios & Lambrias, Kyriacos, 2019. "An analysis of the Eurosystem/ECB projections," Working Paper Series 2291, European Central Bank.
    37. Mr. Romain M Veyrune & Shaoyu Guo, 2019. "Autonomous Factor Forecast Quality: The Case of the Eurosystem," IMF Working Papers 2019/296, International Monetary Fund.
    38. Fabian Kruger & Hendrik Plett, 2022. "Prediction intervals for economic fixed-event forecasts," Papers 2210.13562, arXiv.org, revised Mar 2024.
    39. Boussios, David & Skorbiansky, Sharon Raszap & Maclachlan, Matthew, 2021. "Evaluating U.S. Department of Agriculture’s Long-Term Forecasts for U.S. Harvested Area," USDA Miscellaneous 309616, United States Department of Agriculture.
    40. Wright, Jonathan H., 2019. "Some observations on forecasting and policy," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1186-1192.
    41. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2012. "Time-varying Combinations of Predictive Densities using Nonlinear Filtering," Tinbergen Institute Discussion Papers 12-118/III, Tinbergen Institute.
    42. Cepni, Oguzhan & Clements, Michael P., 2024. "How local is the local inflation factor? Evidence from emerging European countries," International Journal of Forecasting, Elsevier, vol. 40(1), pages 160-183.
    43. Breitung, Jörg & Knüppel, Malte, 2018. "How far can we forecast? Statistical tests of the predictive content," Discussion Papers 07/2018, Deutsche Bundesbank.
    44. Pedersen, Michael, 2019. "Anomalies in macroeconomic prediction errors–evidence from Chilean private forecasters," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1100-1107.
    45. Pablo Pincheira, 2012. "Are Forecast Combinations Efficient?," Working Papers Central Bank of Chile 661, Central Bank of Chile.
    46. Daniela Bragoli & Michele Modugno, 2016. "A Nowcasting Model for Canada: Do U.S. Variables Matter?," Finance and Economics Discussion Series 2016-036, Board of Governors of the Federal Reserve System (U.S.).
    47. Hajo Holzmann & Matthias Eulert, 2014. "The role of the information set for forecasting - with applications to risk management," Papers 1404.7653, arXiv.org.
    48. Boussios, David & Skorbiansky, Sharon Raszap & MacLachlan, Matthew, 2021. "Evaluating U.S. Department of Agriculture’s Long-Term Forecasts for U.S. Harvested Area," Economic Research Report 327201, United States Department of Agriculture, Economic Research Service.
    49. Robert P. Lieli & Augusto Nieto-Barthaburu, 2023. "Forecasting with Feedback," Papers 2308.15062, arXiv.org, revised Jan 2024.
    50. 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.
    51. Pincheira, Pablo & Hardy, Nicolas, 2021. "The Mean Squared Prediction Error Paradox," MPRA Paper 107403, University Library of Munich, Germany.
    52. Boussios, David & Skoriansky, Sharon Raszap & MacLachlan, Matthew, 2021. "Evaluating U.S. Department of Agriculture’s Long-Term Forecasts for U.S. Harvested Area," USDA Miscellaneous 309619, United States Department of Agriculture.
    53. Wang, Yiyao & Lee, Tae-Hwy, 2014. "Asymmetric loss in the Greenbook and the Survey of Professional Forecasters," International Journal of Forecasting, Elsevier, vol. 30(2), pages 235-245.
    54. 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.
    55. Jing Tian & Firmin Doko Tchatoka & Thomas Goodwin, 2022. "Are internally consistent forecasts rational?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(7), pages 1338-1355, November.
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    129. Yanlin Shi, 2023. "Long memory and regime switching in the stochastic volatility modelling," Annals of Operations Research, Springer, vol. 320(2), pages 999-1020, January.
    130. Jonathan Tuck & Shane Barratt & Stephen Boyd, 2021. "Portfolio Construction Using Stratified Models," Papers 2101.04113, arXiv.org, revised Feb 2021.
    131. Portella-Carbó, Ferran & Pérez-Montiel, Jose & Ozcelebi, Oguzhan, 2023. "Tourism-led economic growth across the business cycle: Evidence from Europe (1995–2021)," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 1241-1253.
    132. Chadwick, Meltem Gülenay & Fazilet, Fatih & Tekatli, Necati, 2015. "Understanding the common dynamics of the emerging market currencies," Economic Modelling, Elsevier, vol. 49(C), pages 120-136.
    133. Koki, Constandina & Leonardos, Stefanos & Piliouras, Georgios, 2022. "Exploring the predictability of cryptocurrencies via Bayesian hidden Markov models," Research in International Business and Finance, Elsevier, vol. 59(C).
    134. Mark J. Flannery & Paul Glasserman & David K.A. Mordecai & Cliff Rossi, 2012. "Forging Best Practices in Risk Management," Working Papers 12-02, Office of Financial Research, US Department of the Treasury.
    135. Geir D. Berentsen & Jan Bulla & Antonello Maruotti & Bård Støve, 2022. "Modelling clusters of corporate defaults: Regime‐switching models significantly reduce the contagion source," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(3), pages 698-722, June.
    136. Glen Livingston & Darfiana Nur, 2020. "Bayesian inference of smooth transition autoregressive (STAR)(k)–GARCH(l, m) models," Statistical Papers, Springer, vol. 61(6), pages 2449-2482, December.
    137. Ta-Hsin Li, 2019. "Quantile-Frequency Analysis and Spectral Divergence Metrics for Diagnostic Checks of Time Series With Nonlinear Dynamics," Papers 1908.02545, arXiv.org.
    138. Chourdakis, Kyriakos & Dendramis, Yiannis & Tzavalis, Elias, 2014. "Are regime-shift sources of risk priced in the market?," Journal of Empirical Finance, Elsevier, vol. 28(C), pages 151-170.
    139. 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.
    140. Ayben Koy, 2017. "Modelling Nonlinear Dynamics of Oil Futures Market," Econometric Research in Finance, SGH Warsaw School of Economics, Collegium of Economic Analysis, vol. 2(1), pages 23-42, June.
    141. Heni Boubaker & Nadia Sghaier, 2015. "On the Dynamic Dependence between US and other Developed Stock Markets: An Extreme-value Time-varying Copula Approach," Bankers, Markets & Investors, ESKA Publishing, issue 136-137, pages 80-93, May-June.
    142. Nyberg, Henri, 2013. "Predicting bear and bull stock markets with dynamic binary time series models," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3351-3363.
    143. Alexis Flageollet & Hamza Bahaji, 2016. "Monetary Policy and Risk-Based Asset Allocation," Open Economies Review, Springer, vol. 27(5), pages 851-870, November.
    144. Samet G nay, 2015. "Markov Regime Switching Generalized Autoregressive Conditional Heteroskedastic Model and Volatility Modeling for Oil Returns," International Journal of Energy Economics and Policy, Econjournals, vol. 5(4), pages 979-985.
    145. Suthawan Prukumpai, 2015. "Time-varying Industrial Portfolio Betas under the Regime-switching Model: Evidence from the Stock Exchange of Thailand," Applied Economics Journal, Kasetsart University, Faculty of Economics, Center for Applied Economic Research, vol. 22(2), pages 54-76, December.
    146. Hu, Shicheng & Zhang, Weijie & Li, Danping & Wu, Bing, 2023. "Incorporating improved directional change and regime change detection to formulate trading strategies in foreign exchange markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 622(C).
    147. Anastasios G. Malliaris & Mary Malliaris, 2021. "What Microeconomic Fundamentals Drove Global Oil Prices during 1986–2020?," JRFM, MDPI, vol. 14(8), pages 1-13, August.
    148. Focardi, Sergio M. & Fabozzi, Frank J. & Mazza, Davide, 2019. "Modeling local trends with regime shifting models with time-varying probabilities," International Review of Financial Analysis, Elsevier, vol. 66(C).
    149. Ali Nasir & Ambreen Khursheed & Kazim Ali & Faisal Mustafa, 2021. "A Markov Decision Process Model for Optimal Trade of Options Using Statistical Data," Computational Economics, Springer;Society for Computational Economics, vol. 58(2), pages 327-346, August.
    150. Shi, Yanlin & Ho, Kin-Yip & Liu, Wai-Man, 2016. "Public information arrival and stock return volatility: Evidence from news sentiment and Markov Regime-Switching Approach," International Review of Economics & Finance, Elsevier, vol. 42(C), pages 291-312.
    151. Ma, Chenchen & Tu, Yundong, 2023. "Shrinkage estimation of multiple threshold factor models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1876-1892.
    152. Gębka, Bartosz & Serwa, Dobromił, 2015. "The elusive nature of motives to trade: Evidence from international stock markets," International Review of Financial Analysis, Elsevier, vol. 39(C), pages 147-157.
    153. Laura Arenas & Ana Maria Gil-Lafuente, 2021. "Regime Switching in High-Tech ETFs: Idiosyncratic Volatility and Return," Mathematics, MDPI, vol. 9(7), pages 1-25, March.
    154. Ho, Kin-Yip & Shi, Yanlin & Zhang, Zhaoyong, 2013. "How does news sentiment impact asset volatility? Evidence from long memory and regime-switching approaches," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 436-456.
    155. David Hallac & Peter Nystrup & Stephen Boyd, 2019. "Greedy Gaussian segmentation of multivariate time series," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 13(3), pages 727-751, September.
    156. Lim, Bryan & Arık, Sercan Ö. & Loeff, Nicolas & Pfister, Tomas, 2021. "Temporal Fusion Transformers for interpretable multi-horizon time series forecasting," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1748-1764.
    157. Guidolin, Massimo & Pedio, Manuela, 2017. "Identifying and measuring the contagion channels at work in the European financial crises," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 48(C), pages 117-134.
    158. Hasan, Md. Tanvir, 2022. "The sum of all SCARES COVID-19 sentiment and asset return," The Quarterly Review of Economics and Finance, Elsevier, vol. 86(C), pages 332-346.
    159. Mustafa, Andy Ali & Lin, Ching-Yang & Kakinaka, Makoto, 2022. "Detecting market pattern changes: A machine learning approach," Finance Research Letters, Elsevier, vol. 47(PA).
    160. Dichtl, Hubert & Drobetz, Wolfgang & Otto, Tizian, 2023. "Forecasting Stock Market Crashes via Machine Learning," Journal of Financial Stability, Elsevier, vol. 65(C).
    161. Tihana Skrinjaric, 2023. "Leading indicators of financial stress in Croatia: a regime switching approach," Public Sector Economics, Institute of Public Finance, vol. 47(2), pages 205-232.
    162. Mittelstaedt, Christian & Baumgärtner, Stefan, 2022. "Attribution of Collective Causal Responsibility to Individual Actors in a Stochastic System," VfS Annual Conference 2022 (Basel): Big Data in Economics 264051, Verein für Socialpolitik / German Economic Association.
    163. Kent Daniel & Ravi Jagannathan & Soohun Kim, 2012. "Tail Risk in Momentum Strategy Returns," NBER Working Papers 18169, National Bureau of Economic Research, Inc.

  5. Kenny, Geoff & Genre, Véronique & Meyler, Aidan & Timmermann, Allan, 2010. "Combining the forecasts in the ECB survey of professional forecasters: can anything beat the simple average?," Working Paper Series 1277, European Central Bank.

    Cited by:

    1. Driver, Ciaran & Trapani, Lorenzo & Urga, Giovanni, 2013. "On the use of cross-sectional measures of forecast uncertainty," International Journal of Forecasting, Elsevier, vol. 29(3), pages 367-377.
    2. Kajal Lahiri & Huaming Peng & Yongchen Zhao, 2013. "Testing the Value of Probability Forecasts for Calibrated Combining," Discussion Papers 13-02, University at Albany, SUNY, Department of Economics.
    3. Jung, Alexander & El-Shagi, Makram & Giesen, Sebastian, 2013. "Does Central Bank Staff Beat Private Forecasters?," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79925, Verein für Socialpolitik / German Economic Association.
    4. Kurmas Akdogan & Selen Baser & Meltem Gulenay Chadwick & Dilara Ertug & Timur Hulagu & Sevim Kosem & Fethi Ogunc & M. Utku Ozmen & Necati Tekatli, 2012. "Short-Term Inflation Forecasting Models For Turkey and a Forecast Combination Analysis," Working Papers 1209, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    5. Clements, Michael P., 2012. "Subjective and Ex Post Forecast Uncertainty: US Inflation and Output Growth," Economic Research Papers 270629, University of Warwick - Department of Economics.
    6. Gary Koop & Luca Onorante, 2011. "Estimating Phillips Curves in Turbulent Times using the ECBs Survey of Professional Forecasters," Working Papers 1109, University of Strathclyde Business School, Department of Economics.
    7. Kirstin Hubrich & Frauke Skudelny, 2016. "Forecast Combination for Euro Area Inflation - A Cure in Times of Crisis?," Finance and Economics Discussion Series 2016-104, Board of Governors of the Federal Reserve System (U.S.).
    8. Luis E. Rojas, 2011. "Professional Forecasters: How to Understand and Exploit Them Through a DSGE Model," Borradores de Economia 8945, Banco de la Republica.
    9. Giannone, Domenico & De Mol, Christine & Conflitti, Cristina, 2012. "Optimal Combination of Survey Forecasts," CEPR Discussion Papers 9096, C.E.P.R. Discussion Papers.
    10. Geoff Kenny, 2010. "Macroeconomic forecasting: can forecast combination help?," Research Bulletin, European Central Bank, vol. 11, pages 9-12.
    11. Oinonen, Sami & Paloviita, Maritta, 2014. "Analysis of aggregated inflation expectations based on the ECB SPF survey," Bank of Finland Research Discussion Papers 29/2014, Bank of Finland.
    12. Gianni Amisano & Andreas Beyer & Michele Lenza, 2010. "Enhancing monetary analysis," Research Bulletin, European Central Bank, vol. 11, pages 2-6.
    13. Geoff Kenny & Thomas Kostka & Federico Masera, 2015. "Can Macroeconomists Forecast Risk? Event-Based Evidence from the Euro-Area SPF," International Journal of Central Banking, International Journal of Central Banking, vol. 11(4), pages 1-46, December.
    14. Martin Scheicher, 2010. "“Return-free risk”? Market pricing in credit risk markets," Research Bulletin, European Central Bank, vol. 11, pages 7-8.
    15. Schnatz, Bernd & D'Agostino, Antonello, 2012. "Survey-based nowcasting of US growth: a real-time forecast comparison over more than 40 years," Working Paper Series 1455, European Central Bank.
    16. Xiaojie Xu, 2020. "Corn Cash Price Forecasting," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(4), pages 1297-1320, August.
    17. Genre, Véronique & Kenny, Geoff & Meyler, Aidan & Timmermann, Allan, 2013. "Combining expert forecasts: Can anything beat the simple average?," International Journal of Forecasting, Elsevier, vol. 29(1), pages 108-121.

  6. Timmermann, Allan & Aiolfi, Marco & Catão, Luís, 2010. "Common Factors in Latin America?s Business Cycles," CEPR Discussion Papers 7671, C.E.P.R. Discussion Papers.

    Cited by:

    1. Spinola, Danilo, 2023. "Instability constraints and development traps: an empirical analysis of growth cycles and economic volatility in Latin America," Revista CEPAL, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL), April.
    2. Pontines, Victor, 2017. "The financial cycles in four East Asian economies," Economic Modelling, Elsevier, vol. 65(C), pages 51-66.
    3. 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.
    4. Guglielmo Maria Caporale & Alessandro Girardi, 2012. "Business Cycles, International Trade and Capital Flows: Evidence from Latin America," Discussion Papers of DIW Berlin 1254, DIW Berlin, German Institute for Economic Research.
    5. Jean-Pierre Allegret & Alain Sand-Zantman, 2009. "Does a Monetary Union protect again shocks? An assessment of Latin American integration," Post-Print halshs-00371069, HAL.
    6. Issler, Joao Victor & Notini, Hilton & Rodrigues, Claudia & Soares, Ana Flávia, 2013. "Constructing coincident indices of economic activity for the Latin American economy," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 67(1), April.
    7. Christian Rohe, 2016. "On shock symmetry in South America: New evidence from intra-Brazilian real exchange rates," CQE Working Papers 5316, Center for Quantitative Economics (CQE), University of Muenster.
    8. Delalibera, Bruno Ricardo & Issler, João Victor & Branco, Roberto da Cunha Castello, 2017. "Using common features to investigate common growth cycles for BRICS Countries," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 784, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    9. Jean-Pierre Allegret & Alain Sand-Zantman, 2008. "Does a Monetary Union protect again foreign shocks? An assessment of Latin American integration using a Bayesian VAR," Post-Print halshs-00269122, HAL.
    10. Gannon, Gerard L. & Thuraisamy, Kannan S., 2017. "Sovereign risk and the impact of crisis: Evidence from Latin AmericaAuthor-Name: Batten, Jonathan A," Journal of Banking & Finance, Elsevier, vol. 77(C), pages 328-350.
    11. Campos, Nauro F. & Karanasos, Menelaos G. & Tan, Bin, 2012. "Two to tangle: Financial development, political instability and economic growth in Argentina," Journal of Banking & Finance, Elsevier, vol. 36(1), pages 290-304.
    12. Li, Ziran & Sun, Jiajing & Wang, Shouyang, 2013. "An information diffusion-based model of oil futures price," Energy Economics, Elsevier, vol. 36(C), pages 518-525.
    13. Melisso Boschi & Alessandro Girardi, 2008. "The Contribution Of Domestic, Regional And International Factors To Latin America'S Business Cycle," CAMA Working Papers 2008-33, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    14. Sebastian Fossati, 2017. "Output Growth And Structural Reform In Latin America: Have Business Cycles Changed?," Contemporary Economic Policy, Western Economic Association International, vol. 35(1), pages 62-75, January.
    15. Andrea Bonilla Bolanos, 2014. "An Examination of the Convergence in the Output of South American Countries: The Influence of the Region’s Integration Projects," Working Papers 1424, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    16. Carlos Barros & Guglielmo Maria Caporale & Luis Gil-Alana, 2014. "Long Memory in Angolan Macroeconomic Series: Mean Reversion versus Explosive Behaviour," African Development Review, African Development Bank, vol. 26(1), pages 59-73.
    17. James N. Blignaut & Jan H. van Heerden, 2015. "Is Water Shedding Next?," Working Papers 50, Economic Research Southern Africa.
    18. Catão, Luis A.V. & Fostel, Ana & Kapur, Sandeep, 2009. "Persistent gaps and default traps," Journal of Development Economics, Elsevier, vol. 89(2), pages 271-284, July.
    19. Sumru Altuğ & Melike Bildirici, 2010. "Business Cycles around the Globe: A Regime Switching Approach," Working Papers 0032, Yildiz Technical University, Department of Economics, revised Mar 2010.
    20. Nauro F. Campos & Menelaos G. Karanasos & Michail Karoglou & Panagiotis Koutroumpis & Constantin Zopounidis & Apostolos Christopoulos, 2022. "Apocalypse now, apocalypse when? Economic growth and structural breaks in Argentina (1886–2003)," Economics of Transition and Institutional Change, John Wiley & Sons, vol. 30(1), pages 3-32, January.
    21. Luciano Campos & Jesús Ruiz Andújar, 2022. "Common and idiosyncratic components of Latin American business cycles connectedness," Journal of Applied Economics, Taylor & Francis Journals, vol. 25(1), pages 691-722, December.
    22. Mejía-Reyes, Pablo & Rendón-Rojas, Liliana & Vergara-González, Reyna & Aroca, Patricio, 2018. "International synchronization of the Mexican states business cycles: Explaining factors," The North American Journal of Economics and Finance, Elsevier, vol. 44(C), pages 278-288.
    23. Allegret, Jean-Pierre & Sand-Zantman, Alain, 2009. "Does a Monetary Union protect against external shocks?: An assessment of Latin American integration," Journal of Policy Modeling, Elsevier, vol. 31(1), pages 102-118.
    24. Alfredo M. Leone & Jorge I. Canales Kriljenko & Rodolfo Maino, 2023. "The Long and Widening Gap: Analyzing Structural Breaks in Argentina’s Economic Decline," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 29(4), pages 243-259, November.
    25. Timmermann, Allan & Aiolfi, Marco & Catão, Luís, 2010. "Common Factors in Latin America?s Business Cycles," CEPR Discussion Papers 7671, C.E.P.R. Discussion Papers.
    26. Gonzalo Hernández & María Alejandra Prieto, 2020. "Terms of trade shocks and taxation in developing countries," Revista Cuadernos de Economia, Universidad Nacional de Colombia, FCE, CID, vol. 39(81), pages 613-634, July.
    27. Andrea Bonilla, 2014. "An Examination of the Convergence in the Output of South American Countries: The Influence of the Region's Integration Projects," Working Papers halshs-01069353, HAL.
    28. Mr. Jeromin Zettelmeyer, 2006. "Growth and Reforms in Latin America: A Survey of Facts and Arguments," IMF Working Papers 2006/210, International Monetary Fund.
    29. Matthias Morys & Martin Ivanov, 2013. "The emergence of a European region: Business cycles in South-East Europe from political independence to World War II," Centre for Historical Economics and Related Research at York (CHERRY) Discussion Papers 13/01, CHERRY, c/o Department of Economics, University of York.
    30. Ibarra-Ramírez Raúl, 2010. "Forecasting Inflation in Mexico Using Factor Models: Do Disaggregated CPI Data Improve Forecast Accuracy?," Working Papers 2010-01, Banco de México.
    31. Mr. Anoop Singh, 2006. "Macroeconomic Volatility: The Policy Lessons from Latin America," IMF Working Papers 2006/166, International Monetary Fund.
    32. Hallin, Marc & Liska, Roman, 2011. "Dynamic factors in the presence of blocks," Journal of Econometrics, Elsevier, vol. 163(1), pages 29-41, July.
    33. Gutiérrez, Mario A., 2007. "Economic growth in Latin America and the Caribbean: growth transitions rather than steady states," Macroeconomía del Desarrollo 5425, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL).
    34. Andrea Bonilla BOLAÑOS, 2017. "Are South American Countries Really Converging?: The Influence of the Region's Integration Projects," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 130-149, September.

  7. Marco Aiolfi & Carlos Capistrán & Allan Timmermann, 2010. "Forecast Combinations," CREATES Research Papers 2010-21, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Maurin, Laurent & Drechsel, Katja, 2008. "Flow of conjunctural information and forecast of euro area economic activity," Working Paper Series 925, European Central Bank.
    2. 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.
    3. Yin, Anwen, 2015. "Forecasting and model averaging with structural breaks," ISU General Staff Papers 201501010800005727, Iowa State University, Department of Economics.
    4. Tu, Yundong & Yi, Yanping, 2017. "Forecasting cointegrated nonstationary time series with time-varying variance," Journal of Econometrics, Elsevier, vol. 196(1), pages 83-98.
    5. Panopoulou, Ekaterini & Vrontos, Spyridon, 2015. "Hedge fund return predictability; To combine forecasts or combine information?," Journal of Banking & Finance, Elsevier, vol. 56(C), pages 103-122.
    6. Hsiao, Cheng & Wan, Shui Ki, 2014. "Is there an optimal forecast combination?," Journal of Econometrics, Elsevier, vol. 178(P2), pages 294-309.
    7. Christiane Baumeister & Pierre Guérin, 2020. "A Comparison of Monthly Global Indicators for Forecasting Growth," CESifo Working Paper Series 8656, CESifo.
    8. Massimiliano Marcellino, 2007. "Pooling‐Based Data Interpolation and Backdating," Journal of Time Series Analysis, Wiley Blackwell, vol. 28(1), pages 53-71, January.
    9. Wilson, Kevin J., 2017. "An investigation of dependence in expert judgement studies with multiple experts," International Journal of Forecasting, Elsevier, vol. 33(1), pages 325-336.
    10. Henzel, Steffen R. & Mayr, Johannes, 2013. "The mechanics of VAR forecast pooling—A DSGE model based Monte Carlo study," The North American Journal of Economics and Finance, Elsevier, vol. 24(C), pages 1-24.
    11. Jiahan Li & Ilias Tsiakas, 2016. "Equity Premium Prediction: The Role of Economic and Statistical Constraints," Working Paper series 16-25, Rimini Centre for Economic Analysis.
    12. Schwaab, Bernd & Koopman, Siem Jan & Lucas, André & Nucera, Federico, 2016. "The information in systemic risk rankings," Working Paper Series 1875, European Central Bank.
    13. Ercio Muñoz & Miguel Ricaurte & Mariel Siravegna, 2012. "Combinación de Proyecciones para el Precio del Petróleo: Aplicación y Evaluación de Metodologías," Working Papers Central Bank of Chile 660, Central Bank of Chile.
    14. Schrimpf, Andreas, 2008. "International Stock Return Predictability Under Model Uncertainty," ZEW Discussion Papers 08-048, ZEW - Leibniz Centre for European Economic Research.
    15. George Papadopoulos & Savas Papadopoulos & Thomas Sager, 2016. "Credit risk stress testing for EU15 banks: a model combination approach," Working Papers 203, Bank of Greece.
    16. Mr. Emil Stavrev, 2006. "Measures of Underlying Inflation in the Euro Area: Assessment and Role for Informing Monetary Policy," IMF Working Papers 2006/197, International Monetary Fund.
    17. Dan Zhu & Qingwei Wang & John Goddard, 2022. "A new hedging hypothesis regarding prediction interval formation in stock price forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(4), pages 697-717, July.
    18. Hansen, Bruce E., 2010. "Averaging estimators for autoregressions with a near unit root," Journal of Econometrics, Elsevier, vol. 158(1), pages 142-155, September.
    19. Cakici, Nusret & Fieberg, Christian & Metko, Daniel & Zaremba, Adam, 2023. "Machine learning goes global: Cross-sectional return predictability in international stock markets," Journal of Economic Dynamics and Control, Elsevier, vol. 155(C).
    20. 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.
    21. Davide Pettenuzzo & Francesco Ravazzolo, 2014. "Optimal portfolio choice under decision-based model combinations," Working Paper 2014/15, Norges Bank.
    22. Francesco Ravazzolo & Shaun P. Vahey, 2010. "Forecast densities for economic aggregates from disaggregate ensembles," Working Paper 2010/02, Norges Bank.
    23. Fernandez-Perez, Adrian & Fuertes, Ana-Maria & Miffre, Joëlle, 2019. "A comprehensive appraisal of style-integration methods," Journal of Banking & Finance, Elsevier, vol. 105(C), pages 134-150.
    24. Karlsson, Sune, 2012. "Forecasting with Bayesian Vector Autoregressions," Working Papers 2012:12, Örebro University, School of Business.
    25. Smith, Aaron & Naik, Prasad A. & Tsai, Chih-Ling, 2006. "Markov-switching model selection using Kullback-Leibler divergence," Journal of Econometrics, Elsevier, vol. 134(2), pages 553-577, October.
    26. Salinas, David & Flunkert, Valentin & Gasthaus, Jan & Januschowski, Tim, 2020. "DeepAR: Probabilistic forecasting with autoregressive recurrent networks," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1181-1191.
    27. Yu-chin Chen & Kwok Ping Tsang & Wen Jen Tsay, 2010. "Home Bias in Currency Forecasts," Working Papers 272010, Hong Kong Institute for Monetary Research.
    28. 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.
    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. Čapek, Jan & Crespo Cuaresma, Jesús & Hauzenberger, Niko & Reichel, Vlastimil, 2023. "Macroeconomic forecasting in the euro area using predictive combinations of DSGE models," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1820-1838.
    31. John Geweke & Gianni Amisano, 2008. "Optimal Prediction Pools," Working Paper series 22_08, Rimini Centre for Economic Analysis.
    32. Kilian, Lutz & Baumeister, Christiane & Lee, Thomas K, 2014. "Are there Gains from Pooling Real-Time Oil Price Forecasts?," CEPR Discussion Papers 10075, C.E.P.R. Discussion Papers.
    33. Scott A. Brave & Charles S. Gascon & William Kluender & Thomas Walstrum, 2019. "Predicting Benchmarked US State Employment Data in Real Time," Working Papers 2019-037, Federal Reserve Bank of St. Louis, revised 11 Mar 2021.
    34. 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].
    35. Matteo Ciccarelli & Carlo Altavilla, 2007. "Inflation Forecasts, Monetary Policy and Unemployment Dynamics: Evidence from the US and the Euro area," 2007 Meeting Papers 315, Society for Economic Dynamics.
    36. João F. Caldeira & Guilherme V. Moura & Francisco J. Nogales & André A. P. Santos, 2017. "Combining Multivariate Volatility Forecasts: An Economic-Based Approach," Journal of Financial Econometrics, Oxford University Press, vol. 15(2), pages 247-285.
    37. Fuertes, Ana-Maria & Olmo, Jose, 2013. "Optimally harnessing inter-day and intra-day information for daily value-at-risk prediction," International Journal of Forecasting, Elsevier, vol. 29(1), pages 28-42.
    38. Matteo Iacopini & Francesco Ravazzolo & Luca Rossini, 2020. "Proper scoring rules for evaluating asymmetry in density forecasting," Working Papers No 06/2020, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    39. Li Li & Yanfei Kang & Feng Li, 2021. "Bayesian forecast combination using time-varying features," Papers 2108.02082, arXiv.org, revised Jun 2022.
    40. Michiel De Pooter & Francesco Ravazzolo & Dick van Dijk, 2010. "Term structure forecasting using macro factors and forecast combination," International Finance Discussion Papers 993, Board of Governors of the Federal Reserve System (U.S.).
    41. Canova, Fabio & Matthes, Christian, 2018. "A composite likelihood approach for dynamic structural models," CEPR Discussion Papers 13245, C.E.P.R. Discussion Papers.
    42. 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.
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  8. Blake, David & Tonks, Ian & Timmermann, Allan & Wermers, Russ, 2010. "Decentralized Investment Management: Evidence from the Pension Fund Industry," CEPR Discussion Papers 7679, C.E.P.R. Discussion Papers.

    Cited by:

    1. Michael A.S. Joyce & Zhuoshi Liu & Ian Tonks, 2017. "Institutional Investors and the QE Portfolio Balance Channel," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(6), pages 1225-1246, September.
    2. Platanakis, Emmanouil & Sutcliffe, Charles & Ye, Xiaoxia, 2021. "Horses for courses: Mean-variance for asset allocation and 1/N for stock selection," European Journal of Operational Research, Elsevier, vol. 288(1), pages 302-317.
    3. Cai, Biqing & Cheng, Tingting & Yan, Cheng, 2018. "Time-varying skills (versus luck) in U.S. active mutual funds and hedge funds," Journal of Empirical Finance, Elsevier, vol. 49(C), pages 81-106.
    4. Joyce, Michael & Liu, Zhuoshi & Tonks, Ian, 2014. "Institutional investor portfolio allocation, quantitative easing and the global financial crisis," Bank of England working papers 510, Bank of England.
    5. Blake, David & Caulfield, Tristan & Ioannidis, Christos & Tonks, Ian, 2014. "Improved inference in the evaluation of mutual fund performance using panel bootstrap methods," Journal of Econometrics, Elsevier, vol. 183(2), pages 202-210.
    6. Campbell R. Harvey & Yan Liu, 2020. "False (and Missed) Discoveries in Financial Economics," Journal of Finance, American Finance Association, vol. 75(5), pages 2503-2553, October.
    7. Rossi, Alberto G. & Blake, David & Timmermann, Allan & Tonks, Ian & Wermers, Russ, 2015. "Network centrality and pension fund performance," CFR Working Papers 15-16, University of Cologne, Centre for Financial Research (CFR).
    8. D’Arcangelis, Anna Maria & Levantesi, Susanna & Rotundo, Giulia, 2021. "A complex networks approach to pension funds," Journal of Business Research, Elsevier, vol. 129(C), pages 687-702.
    9. Doyle, Joanne & Eades, Kenneth & Marshall, Brooks, 2021. "Estimating the effect of active management and private equity for defined benefit pension funds," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 161-169.
    10. Donnelly, Catherine & Guillén, Montserrat & Nielsen, Jens Perch, 2014. "Bringing cost transparency to the life annuity market," Insurance: Mathematics and Economics, Elsevier, vol. 56(C), pages 14-27.
    11. Xu, Ruihui & Zhang, Xuliang & Gozgor, Giray & Lau, Chi Keung Marco & Yan, Cheng, 2023. "Investor flow-chasing and price–performance puzzle: Evidence from global infrastructure funds," Research in International Business and Finance, Elsevier, vol. 65(C).
    12. Timmermann, Allan & Lunde, Asger & Groenborg, Niels & Wermers, Russ, 2017. "Picking Funds with Confidence," CEPR Discussion Papers 11896, C.E.P.R. Discussion Papers.
    13. Boubaker, Sabri & Gounopoulos, Dimitrios & Nguyen, Duc Khuong & Paltalidis, Nikos, 2017. "Assessing the effects of unconventional monetary policy and low interest rates on pension fund risk incentives," Journal of Banking & Finance, Elsevier, vol. 77(C), pages 35-52.
    14. Gordon Cookson & Tim Jenkinson & Howard Jones & Jose Vicente Martinez, 2022. "Virtual Reality? Investment Consultants’ Claims About Their Own Performance," Management Science, INFORMS, vol. 68(11), pages 8301-8318, November.
    15. Jansen, Kristy, 2021. "Essays on institutional investors, portfolio choice, and asset prices," Other publications TiSEM fd998408-d282-4e0f-b542-4, Tilburg University, School of Economics and Management.
    16. Ishita Sen, 2023. "Regulatory Limits to Risk Management," The Review of Financial Studies, Society for Financial Studies, vol. 36(6), pages 2175-2223.
    17. Campbell R. Harvey & Yan Liu, 2022. "Luck versus Skill in the Cross Section of Mutual Fund Returns: Reexamining the Evidence," Journal of Finance, American Finance Association, vol. 77(3), pages 1921-1966, June.
    18. Sebastian Bunnenberg & Martin Rohleder & Hendrik Scholz & Marco Wilkens, 2019. "Jensen's alpha and the market‐timing puzzle," Review of Financial Economics, John Wiley & Sons, vol. 37(2), pages 234-255, April.
    19. Rossi, Alberto G. & Blake, David & Timmermann, Allan & Tonks, Ian & Wermers, Russ, 2018. "Network centrality and delegated investment performance," Journal of Financial Economics, Elsevier, vol. 128(1), pages 183-206.
    20. Andonov, Aleksandar & Eichholtz, Piet & Kok, Nils, 2015. "Intermediated investment management in private markets: Evidence from pension fund investments in real estate," Journal of Financial Markets, Elsevier, vol. 22(C), pages 73-103.
    21. Cheng, Tingting & Yan, Cheng & Yan, Yayi, 2021. "Improved inference for fund alphas using high-dimensional cross-sectional tests," Journal of Empirical Finance, Elsevier, vol. 61(C), pages 57-81.
    22. Manuel Ammann & Christian Ehmann, 2017. "Is Governance Related to Investment Performance and Asset Allocation? Empirical Evidence from Swiss Pension Funds," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 153(3), pages 293-339, July.
    23. Lejeune, Miguel A. & Shen, Siqian, 2016. "Multi-objective probabilistically constrained programs with variable risk: Models for multi-portfolio financial optimization," European Journal of Operational Research, Elsevier, vol. 252(2), pages 522-539.
    24. Ran Ji & Miguel A. Lejeune, 2018. "Risk-budgeting multi-portfolio optimization with portfolio and marginal risk constraints," Annals of Operations Research, Springer, vol. 262(2), pages 547-578, March.
    25. Zambrana, Rafael & Zapatero, Fernando, 2021. "A tale of two types: Generalists vs. specialists in asset management," Journal of Financial Economics, Elsevier, vol. 142(2), pages 844-861.
    26. Broeders, Dirk W.G.A. & van Oord, Arco & Rijsbergen, David R., 2016. "Scale economies in pension fund investments: A dissection of investment costs across asset classes," Journal of International Money and Finance, Elsevier, vol. 67(C), pages 147-171.
    27. Blake, David & Sarno, Lucio & Zinna, Gabriele, 2017. "The market for lemmings: The herding behavior of pension funds," Journal of Financial Markets, Elsevier, vol. 36(C), pages 17-39.
    28. Minho Lee & Roy H. Kwon & Chi-Guhn Lee & Hassan Anis, 2018. "Decentralized strategic asset allocation with global constraints," Journal of Asset Management, Palgrave Macmillan, vol. 19(1), pages 13-26, January.
    29. Matteo Bonetti, 2021. "Pension Fund Equity Performance: Herding Does Not Pay Off," Working Papers 729, DNB.
    30. Yue Xu, 2021. "Spillovers of Senior Mutual Fund Managers’ Capital Raising Ability," CREATES Research Papers 2022-03, Department of Economics and Business Economics, Aarhus University.
    31. Cheng, Tingting & Yan, Cheng, 2017. "Evaluating the size of the bootstrap method for fund performance evaluation," Economics Letters, Elsevier, vol. 156(C), pages 36-41.
    32. Campbell R. Harvey & Yan Liu, 2020. "False (and Missed) Discoveries in Financial Economics," Papers 2006.04269, arXiv.org.
    33. Andreas G. F. Hoepner & Lisa Schopohl, 2018. "On the Price of Morals in Markets: An Empirical Study of the Swedish AP-Funds and the Norwegian Government Pension Fund," Journal of Business Ethics, Springer, vol. 151(3), pages 665-692, September.
    34. Sabri Boubaker & Dimitrios Gounopoulos & Duc Khuong Nguyen & Nikos Paltalidis, 2016. "Assessing the Effects of Unconventional Monetary Policy on Pension Funds Risk Incentives," Working Papers 2016-005, Department of Research, Ipag Business School.
    35. Broeders, Dirk W.G.A. & van Oord, Arco & Rijsbergen, David R., 2019. "Does it pay to pay performance fees? Empirical evidence from Dutch pension funds," Journal of International Money and Finance, Elsevier, vol. 93(C), pages 299-312.
    36. Gabriele Zinna, 2014. "Price pressures in the UK index-linked market: an empirical investigation," Temi di discussione (Economic working papers) 968, Bank of Italy, Economic Research and International Relations Area.

  9. Timmermann, Allan & Aiolfi, Marco & Rodriguez, Marius, 2010. "Understanding Analysts' Earnings Expectations: Biases, Nonlinearities and Predictability," CEPR Discussion Papers 7656, C.E.P.R. Discussion Papers.

    Cited by:

    1. Baghestani, Hamid & Khallaf, Ashraf, 2012. "Predictions of growth in U.S. corporate profits: Asymmetric vs. symmetric loss," International Review of Economics & Finance, Elsevier, vol. 22(1), pages 222-229.

  10. Pesaran, M.H. & Pick, A. & Timmermann, A., 2009. "Variable Selection and Inference for Multi-period Forecasting Problems," Cambridge Working Papers in Economics 0901, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Lobanov, Mikhail (Лобанов, Михаил) & Zvezdvanovic-Lobanova, Jelena (Звезданович-Лобанова, Елена), 2017. "Specifics of Agricultural Policy in the Countries of Central-Eastern and South-Eastern Europe in 1990–2010s [Особенности Аграрной Политики В Странах Центрально- И Юго-Восточной Европы В 1990-2010-Х," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 3, pages 150-173, June.

  11. Carlos Capistrán & Allan Timmermann, 2008. "Disagreement and Biases in Inflation Expectations," CREATES Research Papers 2008-56, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Bernd Hayo & Florian Neumeier, 2018. "Households’ Inflation Perceptions and Expectations: Survey Evidence from New Zealand," ifo Working Paper Series 255, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    2. Capistrán, Carlos & López-Moctezuma, Gabriel, 2014. "Forecast revisions of Mexican inflation and GDP growth," International Journal of Forecasting, Elsevier, vol. 30(2), pages 177-191.
    3. Chia-Lin Chang & Bert de Bruijn & Philip Hans Franses & Michael McAleer, 2013. "Analyzing Fixed-event Forecast Revisions," Documentos de Trabajo del ICAE 2013-14, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico, revised Apr 2013.
    4. Aretz, Kevin & Bartram, Söhnke M. & Pope, Peter F., 2011. "Asymmetric Loss Functions and the Rationality of Expected Stock Returns," MPRA Paper 47343, University Library of Munich, Germany.
    5. Jonathan Benchimol & Makram El-Shagi & Yossi Saadon, 2020. "Do Expert Experience and Characteristics Affect Inflation Forecasts?," Bank of Israel Working Papers 2020.11, Bank of Israel.
    6. Ahrens, Steffen & Lustenhouwer, Joep & Tettamanzi, Michele, 2017. "The Stabilizing Role of Forward Guidance: A Macro Experiment," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168063, Verein für Socialpolitik / German Economic Association.
    7. Mankiw, N. Gregory & Reis, Ricardo, 2002. "Sticky Information Versus Sticky Prices: A Proposal to Replace the New Keynesian Phillips Curve," Scholarly Articles 3415324, Harvard University Department of Economics.
    8. Carlos Capistrán & Manuel Ramos‐Francia, 2010. "Does Inflation Targeting Affect the Dispersion of Inflation Expectations?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 42(1), pages 113-134, February.
    9. Pedersen, Michael, 2015. "What affects the predictions of private forecasters? The role of central bank forecasts in Chile," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1043-1055.
    10. Olivier Coibion & Yuriy Gorodnichenko & Rupal Kamdar, 2017. "The Formation of Expectations, Inflation and the Phillips Curve," NBER Working Papers 23304, National Bureau of Economic Research, Inc.
    11. Ehrmann, Michael, 2021. "Point targets, tolerance bands or target ranges? Inflation target types and the anchoring of inflation expectations," Journal of International Economics, Elsevier, vol. 132(C).
    12. James M. Nason & Gregor W. Smith, 2013. "Measuring The Slowly Evolving Trend In Us Inflation With Professional Forecasts," Working Paper 1316, Economics Department, Queen's University.
    13. 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.
    14. Valentina Corradi & Norman Swanson, 2013. "A Survey of Recent Advances in Forecast Accuracy Comparison Testing, with an Extension to Stochastic Dominance," Departmental Working Papers 201309, Rutgers University, Department of Economics.
    15. Gross, Marco, 2009. "Nonparametric Hybrid Phillips Curves Based on Subjective Expectations: Estimates for the Euro Area," Working Paper Series 1119, European Central Bank.
    16. Michael P. Clements, 2022. "Forecaster Efficiency, Accuracy, and Disagreement: Evidence Using Individual‐Level Survey Data," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(2-3), pages 537-568, March.
    17. Yoshiyuki Nakazono, 2016. "Inflation expectations and monetary policy under disagreements," Bank of Japan Working Paper Series 16-E-1, Bank of Japan.
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  12. Davide Pettenuzzo & Allan G. Timmermann & Rossen I. Valkanov, 2008. "Return Predictability under Equilibrium Constraints on the Equity Premium," Working Papers 37, Brandeis University, Department of Economics and International Business School.

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    1. Rangan Gupta & Mampho P. Modise & Josine Uwilingiye, 2011. "Out-of-Sample Equity Premium Predictability in South Africa: Evidence from a Large Number of Predictors," Working Papers 201122, University of Pretoria, Department of Economics.

  13. Carlos Capistrán & Allan Timmermann, 2008. "Forecast Combination With Entry and Exit of Experts," CREATES Research Papers 2008-55, Department of Economics and Business Economics, Aarhus University.

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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. Kajal Lahiri & Huaming Peng & Xuguang Simon Sheng, 2021. "Measuring Uncertainty of a Combined Forecast and Some Tests for Forecaster Heterogeneity," Working Papers 2021-005, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    3. Tu, Yundong & Yi, Yanping, 2017. "Forecasting cointegrated nonstationary time series with time-varying variance," Journal of Econometrics, Elsevier, vol. 196(1), pages 83-98.
    4. Yin, Anwen, 2015. "Forecasting and model averaging with structural breaks," ISU General Staff Papers 201501010800005727, Iowa State University, Department of Economics.
    5. Capistrán, Carlos & López-Moctezuma, Gabriel, 2014. "Forecast revisions of Mexican inflation and GDP growth," International Journal of Forecasting, Elsevier, vol. 30(2), pages 177-191.
    6. Panopoulou, Ekaterini & Vrontos, Spyridon, 2015. "Hedge fund return predictability; To combine forecasts or combine information?," Journal of Banking & Finance, Elsevier, vol. 56(C), pages 103-122.
    7. Hsiao, Cheng & Wan, Shui Ki, 2014. "Is there an optimal forecast combination?," Journal of Econometrics, Elsevier, vol. 178(P2), pages 294-309.
    8. Jonathan Benchimol & Makram El-Shagi & Yossi Saadon, 2020. "Do Expert Experience and Characteristics Affect Inflation Forecasts?," Bank of Israel Working Papers 2020.11, Bank of Israel.
    9. Christiane Baumeister & Pierre Guérin, 2020. "A Comparison of Monthly Global Indicators for Forecasting Growth," CESifo Working Paper Series 8656, CESifo.
    10. Wilson, Kevin J., 2017. "An investigation of dependence in expert judgement studies with multiple experts," International Journal of Forecasting, Elsevier, vol. 33(1), pages 325-336.
    11. Jiahan Li & Ilias Tsiakas, 2016. "Equity Premium Prediction: The Role of Economic and Statistical Constraints," Working Paper series 16-25, Rimini Centre for Economic Analysis.
    12. George Papadopoulos & Savas Papadopoulos & Thomas Sager, 2016. "Credit risk stress testing for EU15 banks: a model combination approach," Working Papers 203, Bank of Greece.
    13. Alberto Caruso & Laura Coroneo, 2023. "Does Real‐Time Macroeconomic Information Help to Predict Interest Rates?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 55(8), pages 2027-2059, December.
    14. Mihaela Simionescu (Bratu), 2014. "The Performance of Predictions Based on the Dobrescu Macromodel for the Romanian Economy," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 179-195, October.
    15. Dan Zhu & Qingwei Wang & John Goddard, 2022. "A new hedging hypothesis regarding prediction interval formation in stock price forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(4), pages 697-717, July.
    16. Cakici, Nusret & Fieberg, Christian & Metko, Daniel & Zaremba, Adam, 2023. "Machine learning goes global: Cross-sectional return predictability in international stock markets," Journal of Economic Dynamics and Control, Elsevier, vol. 155(C).
    17. Davide Pettenuzzo & Francesco Ravazzolo, 2014. "Optimal portfolio choice under decision-based model combinations," Working Paper 2014/15, Norges Bank.
    18. Francesco Ravazzolo & Shaun P. Vahey, 2010. "Forecast densities for economic aggregates from disaggregate ensembles," Working Paper 2010/02, Norges Bank.
    19. Fernandez-Perez, Adrian & Fuertes, Ana-Maria & Miffre, Joëlle, 2019. "A comprehensive appraisal of style-integration methods," Journal of Banking & Finance, Elsevier, vol. 105(C), pages 134-150.
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    285. Kourentzes, Nikolaos & Barrow, Devon & Petropoulos, Fotios, 2019. "Another look at forecast selection and combination: Evidence from forecast pooling," International Journal of Production Economics, Elsevier, vol. 209(C), pages 226-235.
    286. Norman R. Swanson & Weiqi Xiong & Xiye Yang, 2020. "Predicting interest rates using shrinkage methods, real‐time diffusion indexes, and model combinations," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(5), pages 587-613, August.
    287. Yang, Dazhi & van der Meer, Dennis, 2021. "Post-processing in solar forecasting: Ten overarching thinking tools," Renewable and Sustainable Energy Reviews, Elsevier, vol. 140(C).
    288. Kevin J. Lansing, 2019. "Endogenous Forecast Switching Near the Zero Lower Bound," Working Paper Series 2017-24, Federal Reserve Bank of San Francisco.
    289. Iason Kynigakis & Ekaterini Panopoulou, 2022. "Does model complexity add value to asset allocation? Evidence from machine learning forecasting models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(3), pages 603-639, April.
    290. João Valle e Azevedo & João Tovar Jalles, 2011. "Rational vs. Professional Forecasts," Working Papers w201114, Banco de Portugal, Economics and Research Department.
    291. 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.
    292. Salisu, Afees A. & Vo, Xuan Vinh, 2020. "Predicting stock returns in the presence of COVID-19 pandemic: The role of health news," International Review of Financial Analysis, Elsevier, vol. 71(C).
    293. Ding, Lili & Zhao, Zhongchao & Wang, Lei, 2022. "Probability density forecasts for natural gas demand in China: Do mixed-frequency dynamic factors matter?," Applied Energy, Elsevier, vol. 312(C).
    294. Maciejowska, Katarzyna & Nowotarski, Jakub & Weron, Rafał, 2016. "Probabilistic forecasting of electricity spot prices using Factor Quantile Regression Averaging," International Journal of Forecasting, Elsevier, vol. 32(3), pages 957-965.
    295. 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.
    296. Raval, Devesh & Rosenbaum, Ted & Wilson, Nathan E., 2021. "How do machine learning algorithms perform in predicting hospital choices? evidence from changing environments," Journal of Health Economics, Elsevier, vol. 78(C).
    297. Niu, Zibo & Wang, Chenlu & Zhang, Hongwei, 2023. "Forecasting stock market volatility with various geopolitical risks categories: New evidence from machine learning models," International Review of Financial Analysis, Elsevier, vol. 89(C).
    298. Lyócsa, Štefan & Molnár, Peter & Výrost, Tomáš, 2021. "Stock market volatility forecasting: Do we need high-frequency data?," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1092-1110.
    299. Lof, Matthijs & Nyberg, Henri, 2017. "Noncausality and the commodity currency hypothesis," Energy Economics, Elsevier, vol. 65(C), pages 424-433.
    300. Greenaway-McGrevy, Ryan, 2022. "Forecast combination for VARs in large N and T panels," International Journal of Forecasting, Elsevier, vol. 38(1), pages 142-164.
    301. Jose Torres-Pruñonosa & Pablo García-Estévez & Josep Maria Raya & Camilo Prado-Román, 2022. "How on Earth Did Spanish Banking Sell the Housing Stock?," SAGE Open, , vol. 12(1), pages 21582440221, March.
    302. Proaño, Christian R. & Theobald, Thomas, 2014. "Predicting recessions with a composite real-time dynamic probit model," International Journal of Forecasting, Elsevier, vol. 30(4), pages 898-917.
    303. Panopoulou, Ekaterini & Souropanis, Ioannis, 2019. "The role of technical indicators in exchange rate forecasting," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 197-221.
    304. Stefano Cassella & Huseyin Gulen, 2018. "Extrapolation Bias and the Predictability of Stock Returns by Price-Scaled Variables," The Review of Financial Studies, Society for Financial Studies, vol. 31(11), pages 4345-4397.
    305. Christian Kascha & Francesco Ravazzolo, 2008. "Combining inflation density forecasts," Working Paper 2008/22, Norges Bank.
    306. Xiaojie Xu, 2020. "Corn Cash Price Forecasting," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(4), pages 1297-1320, August.
    307. Björn Fastrich & Peter Winker, 2014. "Combining Forecasts with Missing Data: Making Use of Portfolio Theory," Computational Economics, Springer;Society for Computational Economics, vol. 44(2), pages 127-152, August.
    308. Genre, Véronique & Kenny, Geoff & Meyler, Aidan & Timmermann, Allan, 2013. "Combining expert forecasts: Can anything beat the simple average?," International Journal of Forecasting, Elsevier, vol. 29(1), pages 108-121.
    309. Stavroula P. Fameliti & Vasiliki D. Skintzi, 2020. "Predictive ability and economic gains from volatility forecast combinations," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 200-219, March.
    310. Bordignon, Silvano & Bunn, Derek W. & Lisi, Francesco & Nan, Fany, 2013. "Combining day-ahead forecasts for British electricity prices," Energy Economics, Elsevier, vol. 35(C), pages 88-103.
    311. Li, Gang & Wu, Doris Chenguang & Zhou, Menglin & Liu, Anyu, 2019. "The combination of interval forecasts in tourism," Annals of Tourism Research, Elsevier, vol. 75(C), pages 363-378.
    312. Dominik Wolff & Ulrich Neugebauer, 2019. "Tree-based machine learning approaches for equity market predictions," Journal of Asset Management, Palgrave Macmillan, vol. 20(4), pages 273-288, July.
    313. Mamdouh Abdelmoula M. ABDELSALAM, 2017. "Improving Phillips Curve’s Inflation Forecasts under Misspecification," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 54-76, September.
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    315. Shahid IQBAL & Maqbool H. SIAL, 2016. "Projections of Inflation Dynamics for Pakistan: GMDH Approach," Journal of Economics and Political Economy, KSP Journals, vol. 3(3), pages 536-559, September.
    316. Malte Knüppel & Fabian Krüger, 2022. "Forecast uncertainty, disagreement, and the linear pool," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(1), pages 23-41, January.
    317. Bonnier, Jean-Baptiste, 2022. "Forecasting crude oil volatility with exogenous predictors: As good as it GETS?," Energy Economics, Elsevier, vol. 111(C).
    318. Rossi, Barbara & Gürkaynak, Refet & Kısacıkoğlu, Burçin, 2013. "Do DSGE Models Forecast More Accurately Out-of-Sample than VAR Models?," CEPR Discussion Papers 9576, C.E.P.R. Discussion Papers.
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  14. Andrew J. Patton & Allan Timmermann, 2008. "The Resolution of Macroeconomic Uncertainty: Evidence from Survey Forecast," CREATES Research Papers 2008-54, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Pfajfar, D. & Zakelj, B., 2012. "Uncertainty and Disagreement in Forecasting Inflation : Evidence from the Laboratory (Revised version of EBC DP 2011-014)," Other publications TiSEM 2b92a09f-918e-4614-978d-0, Tilburg University, School of Economics and Management.
    2. Jonas Dovern & Ulrich Fritsche & Jiri Slacalek, 2012. "Disagreement Among Forecasters in G7 Countries," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1081-1096, November.
    3. Pfajfar, D. & Zakelj, B., 2012. "Uncertainty and Disagreement in Forecasting Inflation : Evidence from the Laboratory (Revised version of CentER DP 2011-053)," Other publications TiSEM 38fac5ce-fe8f-4b61-a679-f, Tilburg University, School of Economics and Management.
    4. Ohnsorge,Franziska Lieselotte & Stocker,Marc & Some,Modeste Y., 2016. "Quantifying uncertainties in global growth forecasts," Policy Research Working Paper Series 7770, The World Bank.
    5. Fernandes, Marcelo & Thiele, Eduardo, 2015. "The Macroeconomic Determinants of the Term Structure of Inflation Expectations in Brazil," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 35(1), October.

  15. Allan Timmermann & Bruce N. Lehmann, 2007. "Performance Measurement and Evaluation," FMG Discussion Papers dp604, Financial Markets Group.

    Cited by:

    1. Cuthbertson, Keith & Nitzsche, Dirk & O'Sullivan, Niall, 2016. "A review of behavioural and management effects in mutual fund performance," International Review of Financial Analysis, Elsevier, vol. 44(C), pages 162-176.
    2. Cuthbertson, Keith & Nitzsche, Dirk, 2013. "Performance, stock selection and market timing of the German equity mutual fund industry," Journal of Empirical Finance, Elsevier, vol. 21(C), pages 86-101.

  16. Timmermann, Allan & Elliott, Graham, 2007. "Economic Forecasting," CEPR Discussion Papers 6158, C.E.P.R. Discussion Papers.

    Cited by:

    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. Andrii Babii & Xi Chen & Eric Ghysels & Rohit Kumar, 2020. "Binary Choice with Asymmetric Loss in a Data-Rich Environment: Theory and an Application to Racial Justice," Papers 2010.08463, arXiv.org, revised Nov 2021.
    3. 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.
    4. Emilio Zanetti Chini, 2018. "Forecaster’s utility and forecasts coherence," CREATES Research Papers 2018-01, Department of Economics and Business Economics, Aarhus University.
    5. Massimiliano Marcellino, 2007. "Pooling‐Based Data Interpolation and Backdating," Journal of Time Series Analysis, Wiley Blackwell, vol. 28(1), pages 53-71, January.
    6. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2017. "The contribution of jumps to forecasting the density of returns," Post-Print halshs-01442618, HAL.
    7. Duncan, Roberto & Martínez-García, Enrique, 2019. "New perspectives on forecasting inflation in emerging market economies: An empirical assessment," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1008-1031.
    8. Shahzad Ahmad & Farooq Pasha, 2015. "A Pragmatic Model for Monetary Policy Analysis I: The Case of Pakistan," SBP Research Bulletin, State Bank of Pakistan, Research Department, vol. 11, pages 1-42.
    9. Becker, Sascha & Nautz, Dieter, 2010. "Inflation, price dispersion and market integration through the lens of a monetary search model," Discussion Papers 2010/2, Free University Berlin, School of Business & Economics.
    10. Medel, Carlos A., 2017. "Forecasting Chilean Inflation with the Hybrid New Keynesian Phillips Curve: Globalisation, Combination, and Accuracy," MPRA Paper 78439, University Library of Munich, Germany.
    11. Pinto, Jeronymo Marcondes & Marçal, Emerson Fernandes, 2019. "Cross-validation based forecasting method: a machine learning approach," Textos para discussão 498, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    12. Oleg Korenok & Stanislav Radchenko & Norman R. Swanson, 2010. "International evidence on the efficacy of new‐Keynesian models of inflation persistence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 31-54, January.
    13. 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.
    14. Masayoshi Hayashi, 2012. "Forecasting Welfare Caseloads: The Case of the Japanese Public Assistance Program," CIRJE F-Series CIRJE-F-846, CIRJE, Faculty of Economics, University of Tokyo.
    15. Edda Claus, 2011. "Seven Leading Indexes of New Zealand Employment," The Economic Record, The Economic Society of Australia, vol. 87(276), pages 76-89, March.
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    17. 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].
    18. João F. Caldeira & Guilherme V. Moura & Francisco J. Nogales & André A. P. Santos, 2017. "Combining Multivariate Volatility Forecasts: An Economic-Based Approach," Journal of Financial Econometrics, Oxford University Press, vol. 15(2), pages 247-285.
    19. Dabo-Niang, Sophie & Francq, Christian & Zakoian, Jean-Michel, 2009. "Combining parametric and nonparametric approaches for more efficient time series prediction," MPRA Paper 16893, University Library of Munich, Germany.
    20. Tim Bollerslev & Hao Zhou, 2006. "Expected stock returns and variance risk premia," Finance and Economics Discussion Series 2007-11, Board of Governors of the Federal Reserve System (U.S.).
    21. Elliot Beck & Damian Kozbur & Michael Wolf, 2023. "Hedging Forecast Combinations With an Application to the Random Forest," Papers 2308.15384, arXiv.org, revised Aug 2023.
    22. Régis Barnichon & Geert Mesters, 2020. "Optimal policy perturbations," Economics Working Papers 1716, Department of Economics and Business, Universitat Pompeu Fabra.
    23. Lima, Luiz Renato & Meng, Fanning & Godeiro, Lucas, 2020. "Quantile forecasting with mixed-frequency data," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1149-1162.
    24. Timmermann, Allan & Patton, Andrew, 2007. "Learning in Real Time: Theory and Empirical Evidence from the Term Structure of Survey Forecasts," CEPR Discussion Papers 6526, C.E.P.R. Discussion Papers.
    25. Bajgrowicz, Pierre & Scaillet, Olivier, 2012. "Technical trading revisited: False discoveries, persistence tests, and transaction costs," Journal of Financial Economics, Elsevier, vol. 106(3), pages 473-491.
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    27. 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.
    28. Sun, Yuying & Hong, Yongmiao & Wang, Shouyang & Zhang, Xinyu, 2023. "Penalized time-varying model averaging," Journal of Econometrics, Elsevier, vol. 235(2), pages 1355-1377.
    29. Lumengo Bonga-Bonga, 2008. "Modeling the rand-dollar future spot rates: The Kalman Filter approach," Working Papers 098, Economic Research Southern Africa.
    30. Thierry Cohignac & Nabil Kazi-Tani, 2019. "Quantile Mixing and Model Uncertainty Measures," Working Papers hal-02405859, HAL.
    31. Philip Hans Franses & Michael McAleer & Rianne Legerstee, 2010. "Evaluating Macroeconomic Forecasts: A Review of Some Recent Developments," CIRJE F-Series CIRJE-F-729, CIRJE, Faculty of Economics, University of Tokyo.
    32. David O. Cushman, 2012. "Mankiw vs. DeLong and Krugman on the CEA's Real GDP Forecasts in Early 2009: What Might a Time Series Econometrician Have Said?," Econ Journal Watch, Econ Journal Watch, vol. 9(3), pages 309-349, September.
    33. Becker, R. & Clements, A.E. & Doolan, M.B. & Hurn, A.S., 2015. "Selecting volatility forecasting models for portfolio allocation purposes," International Journal of Forecasting, Elsevier, vol. 31(3), pages 849-861.
    34. Joseph P. Byrne & Shuo Cao. & Dimitris Korobilis., 2015. "Term Structure Dynamics, Macro-Finance Factors and Model Uncertainty," Working Papers 2015_08, Business School - Economics, University of Glasgow.
    35. Konstantinos Nikolopoulos & Waleed S. Alghassab & Konstantia Litsiou & Stelios Sapountzis, 2019. "Long-Term Economic Forecasting with Structured Analogies and Interaction Groups," Working Papers 19018, Bangor Business School, Prifysgol Bangor University (Cymru / Wales).
    36. Mueller, Hannes & Rauh, Christopher, 2019. "The Hard Problem of Prediction for Conflict Prevention," CEPR Discussion Papers 13748, C.E.P.R. Discussion Papers.
    37. Lahiri, Kajal & Wang, J. George, 2013. "Evaluating probability forecasts for GDP declines using alternative methodologies," International Journal of Forecasting, Elsevier, vol. 29(1), pages 175-190.
    38. Maik Wolters, 2017. "How the Baby Boomers' Retirement Wave Distorts Model-Based Output Gap Estimates," Jena Economics Research Papers 2017-008, Friedrich-Schiller-University Jena.
    39. Hännikäinen, Jari, 2014. "Multi-step forecasting in the presence of breaks," MPRA Paper 55816, University Library of Munich, Germany.
    40. Manganelli, Simone, 2006. "A new theory of forecasting," Working Paper Series 584, European Central Bank.
    41. Loening, Josef L. & Durevall, Dick & Birru, Yohannes A., 2009. "Inflation dynamics and food prices in an agricultural economy : the case of Ethiopia," Policy Research Working Paper Series 4969, The World Bank.
    42. Dellas, Harris & Gibson, Heather D. & Hall, Stephen G. & Tavlas, George S., 2018. "The macroeconomic and fiscal implications of inflation forecast errors," Journal of Economic Dynamics and Control, Elsevier, vol. 93(C), pages 203-217.
    43. Giraitis, Liudas & Kapetanios, George & Price, Simon, 2014. "Adaptive forecasting in the presence of recent and ongoing structural change," Bank of England working papers 490, Bank of England.
    44. 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.
    45. 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.
    46. Graziano Moramarco, 2021. "Financial-cycle ratios and medium-term predictions of GDP: Evidence from the United States," Papers 2111.00822, arXiv.org, revised Jan 2024.
    47. Kőrösi, Gábor, 2016. "A lány továbbra is szolgál.. [Modelling and econometrics]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(6), pages 647-667.
    48. Patrick Schmidt & Matthias Katzfuss & Tilmann Gneiting, 2021. "Interpretation of point forecasts with unknown directive," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(6), pages 728-743, September.
    49. Kosei Fukuda, 2010. "Three new empirical perspectives on the Hodrick–Prescott parameter," Empirical Economics, Springer, vol. 39(3), pages 713-731, December.
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    51. Tsuchiya, Yoichi, 2016. "Directional analysis of fiscal sustainability: Revisiting Domar's debt sustainability condition," International Review of Economics & Finance, Elsevier, vol. 41(C), pages 189-201.
    52. Gergely Akos Ganics, 2017. "Optimal density forecast combinations," Working Papers 1751, Banco de España.
    53. Yin, Anwen, 2020. "Equity premium prediction and optimal portfolio decision with Bagging," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    54. Rodrigo Alfaro & Andrés Sagner, 2009. "When RSI met the Binomial-Tree," Working Papers Central Bank of Chile 520, Central Bank of Chile.
    55. Colino, Evelyn V. & Irwin, Scott H. & Garcia, Philip, 2008. "How Much Can Outlook Forecasts be Improved? An Application to the U.S. Hog Market," 2008 Conference, April 21-22, 2008, St. Louis, Missouri 37620, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    56. Ari Hyytinen & Petri Rouvinen & Mika Pajarinen & Joosua Virtanen, 2023. "Ex Ante Predictability of Rapid Growth: A Design Science Approach," Entrepreneurship Theory and Practice, , vol. 47(6), pages 2465-2493, November.
    57. Jaqueson K. Galimberti, 2020. "Forecasting GDP Growth from Outer Space," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(4), pages 697-722, August.
    58. Ramazan Gencay & Ege Yazgan, 2017. "When Are Wavelets Useful Forecasters?," Working Papers 1704, The Center for Financial Studies (CEFIS), Istanbul Bilgi University.
    59. Dewenter, Ralf & Heimeshoff, Ulrich, 2016. "Predicting advertising volumes: A structural time series approach," DICE Discussion Papers 228, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    60. Maria Antoinette Silgoner, 2005. "An Overview of European Economic Indicators: Great Variety of Data on the Euro Area, Need for More Extensive Coverage of the New EU Member States," Monetary Policy & the Economy, Oesterreichische Nationalbank (Austrian Central Bank), issue 3, pages 66-89.
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    62. Norman Swanson & Valentina Corradi, 2006. "Nonparametric Bootstrap Procedures for Predictive Inference Based on Recursive Estimation Schemes," Departmental Working Papers 200618, Rutgers University, Department of Economics.
    63. Montgomery, Jacob M. & Hollenbach, Florian M. & Ward, Michael D., 2015. "Calibrating ensemble forecasting models with sparse data in the social sciences," International Journal of Forecasting, Elsevier, vol. 31(3), pages 930-942.
    64. Galvao Jr., Antonio F., 2011. "Quantile regression for dynamic panel data with fixed effects," Journal of Econometrics, Elsevier, vol. 164(1), pages 142-157, September.
    65. Y. Tsuchiya, 2014. "A directional evaluation of corporate executives' exchange rate forecasts," Applied Economics, Taylor & Francis Journals, vol. 46(1), pages 95-101, January.
    66. 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.
    67. Boriss Siliverstovs & Daniel Wochner, 2020. "Recessions as Breadwinner for Forecasters State-Dependent Evaluation of Predictive Ability: Evidence from Big Macroeconomic US Data," Working Papers 2020/02, Latvijas Banka.
    68. Sudarshan Kumar & Sobhesh Kumar Agarwalla & Jayanth R. Varma & Vineet Virmani, 2023. "Harvesting the volatility smile in a large emerging market: A Dynamic Nelson–Siegel approach," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(11), pages 1615-1644, November.
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    1. Zi‐Yi Guo, 2021. "Out‐of‐sample performance of bias‐corrected estimators for diffusion processes," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(2), pages 243-268, March.
    2. John M. Maheu & Qiao Yang, 2015. "An Infinite Hidden Markov Model for Short-term Interest Rates," Working Paper series 15-05, Rimini Centre for Economic Analysis.
    3. Massimo Guidolin & Alexei G. Orlov & Manuela Pedio, 2015. "The Impact of Monetary Policy on Corporate Bonds under Regime Shifts," Working Papers 562, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    4. Lennart Hoogerheide & Richard Kleijn & Francesco Ravazzolo & Herman K. Van Dijk & Marno Verbeek, 2010. "Forecast accuracy and economic gains from Bayesian model averaging using time-varying weights," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 251-269.
    5. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2011. "Combining Predictive Densities using Bayesian Filtering with Applications to US Economics Data," Tinbergen Institute Discussion Papers 11-003/4, Tinbergen Institute.
    6. Antoine Mandel & Amir Sani, 2017. "A Machine Learning Approach to the Forecast Combination Puzzle," Working Papers halshs-01317974, HAL.
    7. Avino, Davide & Nneji, Ogonna, 2012. "Are CDS spreads predictable? An analysis of linear and non-linear forecasting models," MPRA Paper 42848, University Library of Munich, Germany.
    8. Massimo Guidolin, 2011. "Markov Switching Models in Empirical Finance," Working Papers 415, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    9. 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.
    10. 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.
    11. Crespo-Cuaresma, Jesus & Fortin, Ines & Hlouskova, Jaroslava & Obersteiner, Michael, 2021. "Regime-dependent commodity price dynamics: A predictive analysis," IHS Working Paper Series 28, Institute for Advanced Studies.
    12. Sadayuki Ono, 2007. "Term Structure Dynamics in a Monetary Economy with Learning," Discussion Papers 07/29, Department of Economics, University of York.
    13. 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.
    14. Safari, Ali & Davallou, Maryam, 2018. "Oil price forecasting using a hybrid model," Energy, Elsevier, vol. 148(C), pages 49-58.
    15. Miguel, Belmonte & Gary, Koop, 2013. "Model Switching and Model Averaging in Time- Varying Parameter Regression Models," SIRE Discussion Papers 2013-34, Scottish Institute for Research in Economics (SIRE).
    16. Massimo Guidolin & Federica Ria, 2011. "Regime shifts in mean-variance efficient frontiers: Some international evidence," Journal of Asset Management, Palgrave Macmillan, vol. 12(5), pages 322-349, November.
    17. Michiel D. de Pooter & Francesco Ravazzolo & Dick van Dijk, 2007. "Predicting the Term Structure of Interest Rates: Incorporating Parameter Uncertainty, Model Uncertainty and Macroeconomic Information," Tinbergen Institute Discussion Papers 07-028/4, Tinbergen Institute.
    18. Knut Are Aastveit & James Mitchell & Francesco Ravazzolo & Herman van Dijk, 2018. "The Evolution of Forecast Density Combinations in Economics," Tinbergen Institute Discussion Papers 18-069/III, Tinbergen Institute.
    19. Zhu, Xiaoneng & Rahman, Shahidur, 2015. "A regime-switching Nelson–Siegel term structure model of the macroeconomy," Journal of Macroeconomics, Elsevier, vol. 44(C), pages 1-17.
    20. Jia Liu & John M. Maheu, 2018. "Improving Markov switching models using realized variance," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(3), pages 297-318, April.
    21. Ravazzolo, F. & van Dijk, H.K. & Verbeek, M.J.C.M., 2007. "Predictive gains from forecast combinations using time-varying model weights," Econometric Institute Research Papers EI 2007-26, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    22. Massimo Guidolin & Stuart Hyde & David McMillan & Sadayuki Ono, 2009. "Non-linear predictability in stock and bond returns: when and where is it exploitable?," Working Papers 2008-010, Federal Reserve Bank of St. Louis.
    23. 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.
    24. Antoine Mandel & Amir Sani, 2016. "Learning Time-Varying Forecast Combinations," Documents de travail du Centre d'Economie de la Sorbonne 16036r, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Sep 2016.
    25. Guidolin, Massimo & Pedio, Manuela, 2019. "Forecasting and trading monetary policy effects on the riskless yield curve with regime switching Nelson–Siegel models," Journal of Economic Dynamics and Control, Elsevier, vol. 107(C), pages 1-1.
    26. Sermpinis, Georgios & Stasinakis, Charalampos & Dunis, Christian, 2014. "Stochastic and genetic neural network combinations in trading and hybrid time-varying leverage effects," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 30(C), pages 21-54.
    27. Federico Bassetti & Roberto Casarin & Francesco Ravazzolo, 2019. "Density Forecasting," BEMPS - Bozen Economics & Management Paper Series BEMPS59, Faculty of Economics and Management at the Free University of Bozen.
    28. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2012. "Time-varying Combinations of Predictive Densities using Nonlinear Filtering," Tinbergen Institute Discussion Papers 12-118/III, Tinbergen Institute.
    29. Massimo Guidolin & Alexei G. Orlov & Manuela Pedio, 2014. "Understanding the Impact of Monetary Policy Shocks on the Corporate Bond Market in Good and Bad Times: A Markov Switching Model," BAFFI CAREFIN Working Papers 1623, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    30. Verena Monschang & Bernd Wilfling, 2022. "A procedure for upgrading linear-convex combination forecasts with an application to volatility prediction," CQE Working Papers 9722, Center for Quantitative Economics (CQE), University of Muenster.
    31. Pierdzioch, Christian & Risse, Marian & Rohloff, Sebastian, 2014. "The international business cycle and gold-price fluctuations," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(2), pages 292-305.
    32. Marco Del Negro & Raiden B. Hasegawa & Frank Schorfheide, 2014. "Dynamic Prediction Pools: An Investigation of Financial Frictions and Forecasting Performance," PIER Working Paper Archive 14-034, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    33. Apostolos Thomadakis, 2012. "Contagion or Flight-to-Quality Phenomena in Stock and Bond Returns," School of Economics Discussion Papers 0612, School of Economics, University of Surrey.
    34. Massimo Guidolin & Daniel L. Thornton, 2010. "Predictions of short-term rates and the expectations hypothesis," Working Papers 2010-013, Federal Reserve Bank of St. Louis.
    35. Eo, Yunjong & Kang, Kyu Ho, 2020. "The effects of conventional and unconventional monetary policy on forecasting the yield curve," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
    36. Jin, Xin & Maheu, John M. & Yang, Qiao, 2022. "Infinite Markov pooling of predictive distributions," Journal of Econometrics, Elsevier, vol. 228(2), pages 302-321.
    37. Massimo Guidolin & Manuela Pedio, 2019. "Forecasting and Trading Monetary Policy Switching Nelson-Siegel Models," BAFFI CAREFIN Working Papers 19106, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    38. Chen, Ying & Niu, Linlin, 2014. "Adaptive dynamic Nelson–Siegel term structure model with applications," Journal of Econometrics, Elsevier, vol. 180(1), pages 98-115.
    39. Elena Andreou & Eric Ghysels & Constantinos Kourouyiannis, 2012. "Robust volatility forecasts in the presence of structural breaks," University of Cyprus Working Papers in Economics 08-2012, University of Cyprus Department of Economics.
    40. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2011. "Combining Predictive Densities using Nonlinear Filtering with Applications to US Economics Data," Tinbergen Institute Discussion Papers 11-172/4, Tinbergen Institute.
    41. Massimo Guidolin & Stuart Hyde, 2008. "Equity portfolio diversification under time-varying predictability and comovements: evidence from Ireland, the US, and the UK," Working Papers 2008-005, Federal Reserve Bank of St. Louis.
    42. Xiaojing Xi & Rogemar Mamon, 2014. "Capturing the Regime-Switching and Memory Properties of Interest Rates," Computational Economics, Springer;Society for Computational Economics, vol. 44(3), pages 307-337, October.
    43. Lin-Yee Hin & Nikolai Dokuchaev, 2016. "Short Rate Forecasting Based On The Inference From The Cir Model For Multiple Yield Curve Dynamics," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 11(01), pages 1-33, March.
    44. Kocięcki, Andrzej & Kolasa, Marcin & Rubaszek, Michał, 2012. "A Bayesian method of combining judgmental and model-based density forecasts," Economic Modelling, Elsevier, vol. 29(4), pages 1349-1355.

  18. Timmermann, Allan & Patton, Andrew, 2007. "Learning in Real Time: Theory and Empirical Evidence from the Term Structure of Survey Forecasts," CEPR Discussion Papers 6526, C.E.P.R. Discussion Papers.

    Cited by:

    1. Kajal Lahiri & Xuguang Sheng, 2008. "Measuring Forecast Uncertainty by Disagreement: The Missing Link," ifo Working Paper Series 60, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    2. Lahiri, Kajal & Sheng, Xuguang, 2010. "Learning and heterogeneity in GDP and inflation forecasts," International Journal of Forecasting, Elsevier, vol. 26(2), pages 265-292, April.
    3. 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.

  19. Pesaran, M.H. & Pettenuzzo, D. & Timmermann, A., 2006. "Learning, Structural Instability and Present Value Calculations," Cambridge Working Papers in Economics 0602, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Philip Vermeulen & Daniel Dias & Maarten Dossche & Erwan Gautier & Ignacio Hernando & Roberto Sabbatini & Harald Stahl, 2007. "Price setting in the euro area : some stylised facts from individual producer price data," Working Paper Research 111, National Bank of Belgium.
    2. Frey, Rainer & Hussinger, Katrin, 2006. "The Role of Technology in M&As: A Firm Level Comparison of Cross-Border and Domestic Deals," ZEW Discussion Papers 06-069, ZEW - Leibniz Centre for European Economic Research.
    3. Klaus Adam & Albert Marcet, 2011. "Internal Rationality, Imperfect Market Knowledge and Asset Prices," CEP Discussion Papers dp1068, Centre for Economic Performance, LSE.
    4. Pausch, Thilo, 2007. "Endogenous credit derivatives and bank behavior," Discussion Paper Series 2: Banking and Financial Studies 2007,16, Deutsche Bundesbank.
    5. Aoki, Kosuke & Kimura, Takeshi, 2007. "Uncertainty about perceived inflation target and monetary policy," Discussion Paper Series 1: Economic Studies 2007,18, Deutsche Bundesbank.
    6. Gandré, Pauline, 2015. "Asset prices and information disclosure under recency-biased learning," CEPREMAP Working Papers (Docweb) 1515, CEPREMAP.
    7. Koetter, Michael & Karmann, Alexander & Fiorentino, Elisabetta, 2006. "The cost efficiency of German banks: a comparison of SFA and DEA," Discussion Paper Series 2: Banking and Financial Studies 2006,10, Deutsche Bundesbank.
    8. Sascha Becker & Marc-Andreas Muendler & Sascha O. Becker, 2006. "The Effect of FDI on Job Separation," CESifo Working Paper Series 1864, CESifo.
    9. Beck, Günter W. & Wieland, Volker, 2006. "Money in monetary policy design under uncertainty: The two-pillar Phillips curve versus ECB-style cross-checking," CFS Working Paper Series 2007/17, Center for Financial Studies (CFS).
    10. Lemke, Wolfgang, 2007. "An affine macro-finance term structure model for the euro area," Discussion Paper Series 1: Economic Studies 2007,13, Deutsche Bundesbank.
    11. Wolfgang Gerke & Ferdinand Mager & Timo Reinschmidt & Christian Schmieder, 2008. "Empirical Risk Analysis of Pension Insurance: The Case of Germany," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 75(3), pages 763-784, September.
    12. Hashem M. Pesaran & Ron P. Smith, 2011. "Beyond the DSGE Straitjacket," CESifo Working Paper Series 3447, CESifo.
    13. Faria, Pedro & Schmidt, Tobias, 2007. "International cooperation on innovation: empirical evidence for German and Portuguese firms," Discussion Paper Series 1: Economic Studies 2007,30, Deutsche Bundesbank.
    14. Hakenes, Hendrik & Fecht, Falko, 2006. "Money market derivatives and the allocation of liquidity risk in the banking sector," Discussion Paper Series 2: Banking and Financial Studies 2006,12, Deutsche Bundesbank.
    15. Arnold, Ivo J. M. & Kool, Clemens J. M. & Raabe, Katharina, 2006. "Industries and the bank lending effects of bank credit demand and monetary policy in Germany," Discussion Paper Series 1: Economic Studies 2006,48, Deutsche Bundesbank.
    16. Stähler, Nikolai, 2007. "Unemployment and employment protection in a unionized economy with search frictions," Discussion Paper Series 1: Economic Studies 2007,04, Deutsche Bundesbank.
    17. M. Hashem Pesaran & Ron Smith, 2006. "Macroeconometric Modelling with a Global Perspective," IEPR Working Papers 06.43, Institute of Economic Policy Research (IEPR).
    18. Marcet, Albert & Adam, Klaus, 2009. "Internal Rationality and Asset Prices," CEPR Discussion Papers 7498, C.E.P.R. Discussion Papers.
    19. Ben J. Heijdra & Jenny Ligthart, 2006. "The Transitional Dynamics of Fiscal Policy in Small Open Economies," CESifo Working Paper Series 1777, CESifo.
    20. Knetsch, Thomas A. & Reimers, Hans-Eggert, 2006. "How to treat benchmark revisions? The case of German production and orders statistics," Discussion Paper Series 1: Economic Studies 2006,38, Deutsche Bundesbank.
    21. Koetter, Michael & Kick, Thomas, 2007. "Slippery slopes of stress: ordered failure events in German banking," Discussion Paper Series 2: Banking and Financial Studies 2007,03, Deutsche Bundesbank.
    22. Ñíguez, Trino-Manuel & Paya, Ivan & Peel, David & Perote, Javier, 2012. "On the stability of the constant relative risk aversion (CRRA) utility under high degrees of uncertainty," Economics Letters, Elsevier, vol. 115(2), pages 244-248.
    23. Theofanis Archontakis & Wolfgang Lemke, 2008. "Threshold Dynamics of Short‐term Interest Rates: Empirical Evidence and Implications for the Term Structure," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 37(1), pages 75-117, February.
    24. Lütkebohmert, Eva & Gordy, Michael B., 2007. "Granularity adjustment for Basel II," Discussion Paper Series 2: Banking and Financial Studies 2007,01, Deutsche Bundesbank.
    25. Radu Tunaru, 2015. "Model Risk in Financial Markets:From Financial Engineering to Risk Management," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 9524, January.
    26. Ramb, Fred, 2007. "Corporate marginal tax rate, tax loss carryforwards and investment functions: empirical analysis using a large German panel data set," Discussion Paper Series 1: Economic Studies 2007,21, Deutsche Bundesbank.
    27. Dasgupta, Partha, 2010. "The Place of Nature in Economic Development," Handbook of Development Economics, in: Dani Rodrik & Mark Rosenzweig (ed.), Handbook of Development Economics, edition 1, volume 5, chapter 0, pages 4977-5046, Elsevier.
    28. T M Niguez & I Paya & D Peel & J Perote, 2011. "On the stability of the CRRA utility under high degrees of uncertainty," Working Papers 615773, Lancaster University Management School, Economics Department.
    29. Tödter, Karl-Heinz & Manzke, Bernhard, 2007. "The welfare effects of inflation: a cost-benefit perspective," Discussion Paper Series 1: Economic Studies 2007,33, Deutsche Bundesbank.
    30. Wolfgang Härdle & Rouslan Moro & Dorothea Schäfer, 2007. "Estimating Probabilities of Default With Support Vector Machines," SFB 649 Discussion Papers SFB649DP2007-035, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    31. Binder, Michael & Offermanns, Christian J., 2007. "International investment positions and exchange rate dynamics: a dynamic panel analysis," Discussion Paper Series 1: Economic Studies 2007,23, Deutsche Bundesbank.
    32. Christian Schoder & Christian R. Proaño & Willi Semmler, 2012. "Are the current account imbalances between EMU countries sustainable?," IMK Working Paper 90-2012, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
    33. Ziegler, Christina & Eickmeier, Sandra, 2006. "How good are dynamic factor models at forecasting output and inflation? A meta-analytic approach," Discussion Paper Series 1: Economic Studies 2006,42, Deutsche Bundesbank.
    34. Loretan, Michael Stanislaus & Kurz-Kim, Jeong-Ryeol, 2007. "A note on the coefficient of determination in regression models with infinite-variance variables," Discussion Paper Series 1: Economic Studies 2007,10, Deutsche Bundesbank.
    35. Falko Fecht & Hans Grüner, 2008. "Limits to International Banking Consolidation," Open Economies Review, Springer, vol. 19(5), pages 651-666, November.
    36. Greiber, Claus & Setzer, Ralph, 2007. "Money and housing: evidence for the euro area and the US," Discussion Paper Series 1: Economic Studies 2007,12, Deutsche Bundesbank.
    37. Dr Martin Weale & Dr. James Mitchell, 2007. "The Rationality and Reliability of Expectations Reported by British Households: Micro Evidence from the British Household Panel Survey," National Institute of Economic and Social Research (NIESR) Discussion Papers 287, National Institute of Economic and Social Research.
    38. Dötz, Niko, 2007. "Time-varying contributions by the corporate bond and CDS markets to credit risk price discovery," Discussion Paper Series 2: Banking and Financial Studies 2007,08, Deutsche Bundesbank.
    39. Stahn, Kerstin, 2006. "Has the export pricing behaviour of German enterprises changed? Empirical evidence from German sectoral prices," Discussion Paper Series 1: Economic Studies 2006,37, Deutsche Bundesbank.
    40. Gandré, Pauline, 2020. "US stock prices and recency-biased learning in the run-up to the Global Financial Crisis and its aftermath," Journal of International Money and Finance, Elsevier, vol. 104(C).

  20. Pesaran, M.H. & Timmermann, A., 2006. "Testing Dependence Among Serially Correlated Multi-category Variables," Cambridge Working Papers in Economics 0648, Faculty of Economics, University of Cambridge.

    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. Etienne, Xiaoli, 2015. "Financialization of Agricultural Commodity Markets: Do Financial Data Help to Forecast Agricultural Prices," 2015 Conference, August 9-14, 2015, Milan, Italy 211626, International Association of Agricultural Economists.
    3. Chen, Shiu-Sheng, 2013. "Forecasting Crude Oil Price Movements with Oil-Sensitive Stocks," MPRA Paper 49240, University Library of Munich, Germany.
    4. 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.
    5. Cem Cakmakli & Richard Paap & Dick J.C. van Dijk, 2011. "Modeling and Estimation of Synchronization in Multistate Markov-Switching Models," Tinbergen Institute Discussion Papers 11-002/4, Tinbergen Institute.
    6. 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.
    7. Duncan, Roberto & Martínez-García, Enrique, 2019. "New perspectives on forecasting inflation in emerging market economies: An empirical assessment," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1008-1031.
    8. Baumeister, Christiane & Kilian, Lutz, 2014. "A general approach to recovering market expectations from futures prices with an application to crude oil," CFS Working Paper Series 466, Center for Financial Studies (CFS).
    9. Natalia Bailey & Sean Holly & M. Hashem Pesaran, 2016. "A Two‐Stage Approach to Spatio‐Temporal Analysis with Strong and Weak Cross‐Sectional Dependence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(1), pages 249-280, January.
    10. Helmut Elsinger, 2020. "Serial Correlation in Contingency Tables (Helmut Elsinger)," Working Papers 228, Oesterreichische Nationalbank (Austrian Central Bank).
    11. Sebastian Link, 2019. "The Price and Employment Response of Firms to the Introduction of Minimum Wages," CESifo Working Paper Series 7575, CESifo.
    12. Harchaoui, Tarek M. & Janssen, Robert V., 2018. "How can big data enhance the timeliness of official statistics?," International Journal of Forecasting, Elsevier, vol. 34(2), pages 225-234.
    13. Tsuchiya, Yoichi, 2013. "Are government and IMF forecasts useful? An application of a new market-timing test," Economics Letters, Elsevier, vol. 118(1), pages 118-120.
    14. Kilian, Lutz & Baumeister, Christiane & Lee, Thomas K, 2014. "Are there Gains from Pooling Real-Time Oil Price Forecasts?," CEPR Discussion Papers 10075, C.E.P.R. Discussion Papers.
    15. Knüppel, Malte & Schultefrankenfeld, Guido, 2011. "How informative are central bank assessments of macroeconomic risks?," Discussion Paper Series 1: Economic Studies 2011,13, Deutsche Bundesbank.
    16. Li, Dongxin & Zhang, Li & Li, Lihong, 2023. "Forecasting stock volatility with economic policy uncertainty: A smooth transition GARCH-MIDAS model," International Review of Financial Analysis, Elsevier, vol. 88(C).
    17. Lei, Xiying & Yang, Yao & Alharthi, Majed & Rasul, Farhat & Faraz Raza, Syed Muhammad, 2022. "Immense reliance on natural resources and environmental challenges in G-20 economies through the lens of COP-26 targets," Resources Policy, Elsevier, vol. 79(C).
    18. Danilo Leiva-Leon, 2014. "A New Approach to Infer Changes in the Synchronization of Business Cycle Phases," Staff Working Papers 14-38, Bank of Canada.
    19. Andrea Bastianin & Elisabetta Mirto & Yan Qin & Luca Rossini, 2024. "What drives the European carbon market? Macroeconomic factors and forecasts," Working Papers 2024.02, Fondazione Eni Enrico Mattei.
    20. Wang, Yudong & Liu, Li & Diao, Xundi & Wu, Chongfeng, 2015. "Forecasting the real prices of crude oil under economic and statistical constraints," Energy Economics, Elsevier, vol. 51(C), pages 599-608.
    21. 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.
    22. Shiu-Sheng Chen, 2016. "Commodity prices and related equity prices," Canadian Journal of Economics, Canadian Economics Association, vol. 49(3), pages 949-967, August.
    23. Xing, Li-Min & Zhang, Yue-Jun, 2022. "Forecasting crude oil prices with shrinkage methods: Can nonconvex penalty and Huber loss help?," Energy Economics, Elsevier, vol. 110(C).
    24. Nyberg, Henri & Pönkä, Harri, 2016. "International sign predictability of stock returns: The role of the United States," Economic Modelling, Elsevier, vol. 58(C), pages 323-338.
    25. 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.
    26. Sevcan Uzun & Ahmet Sensoy & Duc Khuong Nguyen, 2023. "Jump forecasting in foreign exchange markets: A high‐frequency analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(3), pages 578-624, April.
    27. IIZUKA Nobuo, 2013. "Predicting Business Cycle Phases by Professional Forecasters－ Are They Useful ?," ESRI Discussion paper series 305, Economic and Social Research Institute (ESRI).
    28. Yi, Yongsheng & Ma, Feng & Zhang, Yaojie & Huang, Dengshi, 2019. "Forecasting stock returns with cycle-decomposed predictors," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 250-261.
    29. Kajal Lahiri & Huaming Peng & Yongchen Zhao, 2013. "Testing the Value of Probability Forecasts for Calibrated Combining," Discussion Papers 13-02, University at Albany, SUNY, Department of Economics.
    30. Wang, Yudong & Hao, Xianfeng, 2022. "Forecasting the real prices of crude oil: A robust weighted least squares approach," Energy Economics, Elsevier, vol. 116(C).
    31. Ferrara, Laurent & Marcellino, Massimiliano & Mogliani, Matteo, 2015. "Macroeconomic forecasting during the Great Recession: The return of non-linearity?," International Journal of Forecasting, Elsevier, vol. 31(3), pages 664-679.
    32. Sebastian Link, 2018. "Harmonization and Interpretation of the ifo Business Survey's Micro Data," CESifo Working Paper Series 7427, CESifo.
    33. Christian Seiler, 2013. "Nonresponse in Business Tendency Surveys: Theoretical Discourse and Empirical Evidence," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 52.
    34. James Mitchell & Richard J. Smith & Martin R. Weale, 2013. "Efficient Aggregation Of Panel Qualitative Survey Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(4), pages 580-603, June.
    35. Lahiri, Kajal & Wang, J. George, 2013. "Evaluating probability forecasts for GDP declines using alternative methodologies," International Journal of Forecasting, Elsevier, vol. 29(1), pages 175-190.
    36. M. Mogliani & T. Ferrière, 2016. "Rationality of announcements, business cycle asymmetry, and predictability of revisions. The case of French GDP," Working papers 600, Banque de France.
    37. Chatziantoniou, Ioannis & Degiannakis, Stavros & Filis, George, 2019. "Futures-based forecasts: How useful are they for oil price volatility forecasting?," Energy Economics, Elsevier, vol. 81(C), pages 639-649.
    38. Baumeister, Christiane & Kilian, Lutz, 2013. "Do oil price increases cause higher food prices?," CFS Working Paper Series 2013/10, Center for Financial Studies (CFS).
    39. Harri Ponka, 2017. "The Role of Credit in Predicting US Recessions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(5), pages 469-482, August.
    40. Kajal Lahiri & Liu Yang, 2018. "Confidence Bands for ROC Curves With Serially Dependent Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 115-130, January.
    41. Tsuchiya, Yoichi, 2016. "Directional analysis of fiscal sustainability: Revisiting Domar's debt sustainability condition," International Review of Economics & Finance, Elsevier, vol. 41(C), pages 189-201.
    42. Morita, Hiroshi & 森田, 裕史, 2019. "Forecasting Public Investment Using Daily Stock Returns," Discussion paper series HIAS-E-88, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    43. Anthony Garratt & Shaun P. Vahey & Yunyi Zhang, 2019. "Real‐time forecast combinations for the oil price," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(3), pages 456-462, April.
    44. Harri Pönkä, 2017. "Predicting the direction of US stock markets using industry returns," Empirical Economics, Springer, vol. 52(4), pages 1451-1480, June.
    45. Yusui Tang & Feng Ma & Yaojie Zhang & Yu Wei, 2022. "Forecasting the oil price realized volatility: A multivariate heterogeneous autoregressive model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4770-4783, October.
    46. Link Sebastian, 2020. "Harmonization of the ifo Business Survey’s Micro Data," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 240(4), pages 543-555, August.
    47. Al-Sadoon, Majid M. & Li, Tong & Pesaran, M. Hashem, 2012. "An Exponential Class of Dynamic Binary Choice Panel Data Models with Fixed Effects," IZA Discussion Papers 7054, Institute of Labor Economics (IZA).
    48. Ben J. Heijdra & Jenny Ligthart, 2006. "Fiscal Policy, Monopolistic Competition, and Finite Lives," CESifo Working Paper Series 1661, CESifo.
    49. Lahiri, Kajal & Yang, Liu, 2013. "Forecasting Binary Outcomes," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1025-1106, Elsevier.
    50. Amor Aniss Benmoussa & Reinhard Ellwanger & Stephen Snudden, 2020. "The New Benchmark for Forecasts of the Real Price of Crude Oil," Staff Working Papers 20-39, Bank of Canada.
    51. Christian Seiler, 2012. "The Data Sets of the LMU-ifo Economics & Business Data Center - A Guide for Researchers," ifo Working Paper Series 138, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    52. Ron Alquist & Lutz Kilian & Robert Vigfusson, 2011. "Forecasting the Price of Oil," Staff Working Papers 11-15, Bank of Canada.
    53. Bernard, Jean-Thomas & Khalaf, Lynda & Kichian, Maral & Yelou, Clement, 2018. "Oil Price Forecasts For The Long Term: Expert Outlooks, Models, Or Both?," Macroeconomic Dynamics, Cambridge University Press, vol. 22(3), pages 581-599, April.
    54. Y. Tsuchiya, 2014. "A directional evaluation of corporate executives' exchange rate forecasts," Applied Economics, Taylor & Francis Journals, vol. 46(1), pages 95-101, January.
    55. Reinhard Ellwanger, Stephen Snudden, 2021. "Predictability of Aggregated Time Series," LCERPA Working Papers bm0127, Laurier Centre for Economic Research and Policy Analysis.
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  21. Sandeep Kapur & Allan Timmermann, 2005. "Relative Performance Evaluation Contracts and Asset Market Equilibrium," Birkbeck Working Papers in Economics and Finance 0503, Birkbeck, Department of Economics, Mathematics & Statistics.

    Cited by:

    1. Axel Stahmer, 2015. "Fund flows inducing mispricing of risk in competitive financial markets," ESMT Research Working Papers ESMT-15-04, ESMT European School of Management and Technology.
    2. Vayanos, Dimitri & Jiang, Hao & Zheng, Lu, 2020. "Tracking Biased Weights: Asset Pricing Implications of Value-Weighted Indexing," CEPR Discussion Papers 15563, C.E.P.R. Discussion Papers.
    3. Opazo, Luis & Raddatz, Claudio & Schmukler, Sergio L., 2014. "Institutional investors and long-term investment : evidence from Chile," Policy Research Working Paper Series 6922, The World Bank.
    4. Stracca, Livio, 2005. "Delegated portfolio management: a survey of the theoretical literature," Working Paper Series 520, European Central Bank.
    5. Don U. A. Galagedera & John Watson, 2015. "Benchmarking superannuation funds based on relative performance," Applied Economics, Taylor & Francis Journals, vol. 47(28), pages 2959-2973, June.
    6. Buffa, Andrea & Vayanos, Dimitri & Woolley, Paul, 2014. "Asset management contracts and equilibrium prices," LSE Research Online Documents on Economics 119026, London School of Economics and Political Science, LSE Library.
    7. Luis Opazo & Claudio Raddatz & Sergio Schmukler, 2009. "The Long And The Short Of Emerging Market Debt," Working Papers Central Bank of Chile 530, Central Bank of Chile.
    8. Galagedera, Don U.A. & Watson, John & Premachandra, I.M. & Chen, Yao, 2016. "Modeling leakage in two-stage DEA models: An application to US mutual fund families," Omega, Elsevier, vol. 61(C), pages 62-77.
    9. Premachandra, I.M. & Zhu, Joe & Watson, John & Galagedera, Don U.A., 2012. "Best-performing US mutual fund families from 1993 to 2008: Evidence from a novel two-stage DEA model for efficiency decomposition," Journal of Banking & Finance, Elsevier, vol. 36(12), pages 3302-3317.
    10. Blake, David & Timmermann, Allan & Tonks, Ian & Wermers, Russ, 2010. "Decentralized investment management: evidence from the pension fund industry," MPRA Paper 35767, University Library of Munich, Germany.
    11. Pablo Solórzano-Taborga & Ana Belén Alonso-Conde & Javier Rojo-Suárez, 2020. "Data Envelopment Analysis and Multifactor Asset Pricing Models," IJFS, MDPI, vol. 8(2), pages 1-18, April.
    12. Claudio Raddatz & Sergio Schmukler, 2013. "Deconstructing Herding: Evidence from Pension Fund Investment Behavior," Journal of Financial Services Research, Springer;Western Finance Association, vol. 43(1), pages 99-126, February.
    13. Cuoco, Domenico & Kaniel, Ron, 2011. "Equilibrium prices in the presence of delegated portfolio management," Journal of Financial Economics, Elsevier, vol. 101(2), pages 264-296, August.
    14. Johnson, Timothy C., 2016. "Rethinking reversals," Journal of Financial Economics, Elsevier, vol. 120(2), pages 211-228.
    15. Gehrig, Thomas P. & Lütje, Torben & Menkhoff, Lukas, 2008. "Bonus Payments and Fund Managers' Behavior: Trans-Atlantic Evidence," Hannover Economic Papers (HEP) dp-411, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    16. Huang, Shiyang & Jiang, Ying & Qiu, Zhigang & Ye, Zhiqiang, 2019. "An equilibrium model of risk management spillover," Journal of Banking & Finance, Elsevier, vol. 107(C), pages 1-1.
    17. Huang, Shiyang & Qiu, Zhigang & Shang, Qi & Tang, Ke, 2013. "Asset pricing with heterogeneous beliefs and relative performance," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4107-4119.
    18. Liu, Xiangbo & Qiu, Zhigang & Xiong, Yan, 2013. "VaR constrained asset pricing with relative performance," Economics Letters, Elsevier, vol. 121(2), pages 174-178.
    19. Jean-Daniel Guigou & Patrick De Lamirande & Bruno Lovat, 2011. "Strategic delegation and collusion: Do incentive schemes matter?," LSF Research Working Paper Series 11-02, Luxembourg School of Finance, University of Luxembourg.

  22. Kosowski, Robert & Timmermann, Allan & Wermers, Russ & White, Hal, 2005. "Can mutual fund stars really pick stocks? New evidence from a bootstrap analysis," CFR Working Papers 05-14, University of Cologne, Centre for Financial Research (CFR).

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    1. Wei-Xing Zhou & Guo-Hua Mu & Si-Wei Chen & Didier Sornette, "undated". "Strategies used as Spectroscopy of Financial Markets Reveal New Stylized Facts," Working Papers ETH-RC-11-005, ETH Zurich, Chair of Systems Design.
    2. Mohammad (Vahid) Irani & Hugh Hoikwang Kim, 2023. "The consequences of non‐trading institutional investors," Financial Management, Financial Management Association International, vol. 52(3), pages 433-481, September.
    3. Enareta Kurtbegu & Juliana Caicedo-llano, 2014. "European equity fund managers: luck or skill?!," Economics Bulletin, AccessEcon, vol. 34(4), pages 2340-2350.
    4. Charles Cao & Grant Farnsworth & Hong Zhang, 2021. "The Economics of Hedge Fund Startups: Theory and Empirical Evidence," Journal of Finance, American Finance Association, vol. 76(3), pages 1427-1469, June.
    5. 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.
    6. Jezek, M., 2009. "Passive Investors, Active Traders and Strategic Delegation of Price Discovery," Cambridge Working Papers in Economics 0951, Faculty of Economics, University of Cambridge.
    7. Keith Cuthbertson & Dirk Nitzsche & Niall O’Sullivan, 2023. "UK mutual funds: performance persistence and portfolio size," Journal of Asset Management, Palgrave Macmillan, vol. 24(4), pages 284-298, July.
    8. Nicolae B. Gârleanu & Lasse H. Pedersen, 2015. "Efficiently Inefficient Markets for Assets and Asset Management," NBER Working Papers 21563, National Bureau of Economic Research, Inc.
    9. Dirk Brounen & Piet Eichholtz & David Ling, 2007. "Trading Intensity and Real Estate Performance," The Journal of Real Estate Finance and Economics, Springer, vol. 35(4), pages 449-474, November.
    10. Silvio John Camilleri & Ritienne Farrugia, 2018. "The Risk-Adjusted Performance of Alternative Investment Funds and UCITS: A Comparative Analysis," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 10(7), pages 1-23, July.
    11. Thomas George & Chuan-Yang Hwang & Tavy Ronen, 2010. "Bootstrap refinements in tests of microstructure frictions," Review of Quantitative Finance and Accounting, Springer, vol. 35(1), pages 47-70, July.
    12. Solórzano-Taborga, Pablo & Alonso-Conde, Ana Belén & Rojo-Suárez, Javier, 2018. "Efficiency and Persistence of Spanish Absolute Return Funds || Eficiencia y persistencia de los fondos de retorno absolutos españoles," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 25(1), pages 186-214, Junio.
    13. Andrew Clare & Mariana Clare, 2019. "An examination of ex ante fund performance: identifying indicators of future performance," Journal of Asset Management, Palgrave Macmillan, vol. 20(3), pages 175-195, May.
    14. H. Pierre Hsieh & Imen Tebourbi & Wen‐Min Lu & Nai‐Yu Liu, 2020. "Mutual fund performance: The decision quality and capital magnet efficiencies," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 41(5), pages 861-872, July.
    15. Favilukis, Jack & Lin, Xiaoji, 2016. "Does wage rigidity make firms riskier? Evidence from long-horizon return predictability," Journal of Monetary Economics, Elsevier, vol. 78(C), pages 80-95.
    16. Francis In & Sangbae Kim & Philip I Ji, 2014. "On timing ability in Australian managed funds," Australian Journal of Management, Australian School of Business, vol. 39(1), pages 93-106, February.
    17. Artamonov, Nikita & Voronina, Anna & Emelyanov, Nikita & Kurbatskii, Aleksei, 2020. "Estimation of interest rates’ impact on mutual funds’ performance in the USA," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 58, pages 55-75.
    18. Gallefoss, Kristoffer & Hansen, Helge Hoff & Haukaas, Eirik Solli & Molnár, Peter, 2015. "What daily data can tell us about mutual funds: Evidence from Norway," Journal of Banking & Finance, Elsevier, vol. 55(C), pages 117-129.
    19. Jung‐Soon Shin & Minki Kim & Dongjun Oh & Tong Suk Kim, 2019. "Do hedge funds time market tail risk? Evidence from option‐implied tail risk," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(2), pages 205-237, February.
    20. Li, Xin & Paulson, Nicholas, 2014. "Is Farm Management Skill Persistent?," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 170170, Agricultural and Applied Economics Association.
    21. Fernando Chague & Rodrigo De Losso, Bruno Giovannetti, 2017. "Uncovering Skilled Short-sellers," Working Papers, Department of Economics 2017_01, University of São Paulo (FEA-USP).
    22. Jha, Ranjini & Korkie, Bob & Turtle, Harry J., 2009. "Measuring performance in a dynamic world: Conditional mean-variance fundamentals," Journal of Banking & Finance, Elsevier, vol. 33(10), pages 1851-1859, October.
    23. Cuthbertson, Keith & Nitzsche, Dirk & O'Sullivan, Niall, 2008. "UK mutual fund performance: Skill or luck?," Journal of Empirical Finance, Elsevier, vol. 15(4), pages 613-634, September.
    24. Michael Busack & Wolfgang Drobetz & Jan Tille, 2017. "Can investors benefit from the performance of alternative UCITS funds?," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 31(1), pages 69-111, February.
    25. Dimitrios G. Konstantinides & Georgios C. Zachos, 2019. "Exhibiting Abnormal Returns Under a Risk Averse Strategy," Methodology and Computing in Applied Probability, Springer, vol. 21(2), pages 551-566, June.
    26. Alan Crane & Kevin Crotty, 2020. "How Skilled Are Security Analysts?," Journal of Finance, American Finance Association, vol. 75(3), pages 1629-1675, June.
    27. Fisher, Mark & Jensen, Mark J., 2022. "Bayesian nonparametric learning of how skill is distributed across the mutual fund industry," Journal of Econometrics, Elsevier, vol. 230(1), pages 131-153.
    28. Chang, Xiaochen & Guo, Songlin & Huang, Junkai, 2022. "Kidnapped mutual funds: Irrational preference of naive investors and fund incentive distortion," International Review of Financial Analysis, Elsevier, vol. 83(C).
    29. Subrata Roy, 2016. "Another Look in Conditioning Alphas on Economic Information: Indian Evidence," Global Business Review, International Management Institute, vol. 17(1), pages 191-213, February.
    30. Dimitrios Koutmos & Bochen Wu & Qi Zhang, 2020. "In search of winning mutual funds in the Chinese stock market," Review of Quantitative Finance and Accounting, Springer, vol. 54(2), pages 589-616, February.
    31. Javier Vidal-García & Marta Vidal & Sabri Boubaker & Riadh Manita, 2019. "Idiosyncratic risk and mutual fund performance," Annals of Operations Research, Springer, vol. 281(1), pages 349-372, October.
    32. Hou, Yang & Meng, Jiayin, 2018. "The momentum effect in the Chinese market and its relationship with the simultaneous and the lagged investor sentiment," MPRA Paper 94838, University Library of Munich, Germany.
    33. Johansson, Anders C. & Feng, Xunan, 2014. "Can Mutual Funds Pick Stocks in China? Evidence from the IPO Market," Stockholm School of Economics Asia Working Paper Series 2014-32, Stockholm School of Economics, Stockholm China Economic Research Institute.
    34. Cai, Biqing & Cheng, Tingting & Yan, Cheng, 2018. "Time-varying skills (versus luck) in U.S. active mutual funds and hedge funds," Journal of Empirical Finance, Elsevier, vol. 49(C), pages 81-106.
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    Cited by:

    1. Fernando Alexandre & Vasco J. Gabriel & Pedro Bação, 2007. "The Consumption-Wealth Ratio Under Asymmetric Adjustment," NIPE Working Papers 15/2007, NIPE - Universidade do Minho.
    2. Meenagh, David & Minford, Patrick & Peel, David, 2007. "Simulating stock returns under switching regimes - A new test of market efficiency," Economics Letters, Elsevier, vol. 94(2), pages 235-239, February.
    3. Bernd Scherer, 2009. "A note on portfolio choice for sovereign wealth funds," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 23(3), pages 315-327, September.
    4. John Powell & Rubén Roa & Jing Shi & Viliphonh Xayavong, 2007. "A Test for Long-Term Cyclical Clustering of Stock Market Regimes," Australian Journal of Management, Australian School of Business, vol. 32(2), pages 205-221, December.
    5. Marie Brière & Ombretta Signori, 2011. "Inflation hedging portfolios in different regimes," BIS Papers chapters, in: Bank for International Settlements (ed.), Portfolio and risk management for central banks and sovereign wealth funds, volume 58, pages 139-163, Bank for International Settlements.
    6. 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.
    7. Dewandaru, Ginanjar & Masih, Rumi & Bacha, Obiyathulla I. & Masih, A. Mansur M., 2014. "The Role of Islamic Asset Classes in the Diversified Portfolios: Mean Variance Spanning Test," MPRA Paper 56857, University Library of Munich, Germany.
    8. Roger Bowden & Jennifer Zhu, 2010. "Multi-scale variation, path risk and long-term portfolio management," Quantitative Finance, Taylor & Francis Journals, vol. 10(7), pages 783-796.
    9. Mark E. Wohar & David E. Rapach, 2005. "Return Predictability and the Implied Intertemporal Hedging Demands for Stocks and Bonds: International Evidence," Computing in Economics and Finance 2005 329, Society for Computational Economics.
    10. Guidolin, Massimo & Ono, Sadayuki, 2006. "Are the dynamic linkages between the macroeconomy and asset prices time-varying?," Journal of Economics and Business, Elsevier, vol. 58(5-6), pages 480-518.
    11. J. Sa‐Aadu & James Shilling & Ashish Tiwari, 2010. "On the Portfolio Properties of Real Estate in Good Times and Bad Times1," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 38(3), pages 529-565, September.
    12. Asger Lunde & Allan Timmermann, 2005. "Completion time structures of stock price movements," Annals of Finance, Springer, vol. 1(3), pages 293-326, August.
    13. Marie Brière & Ombretta Signori, 2012. "Inflation-Hedging Portfolios : Economic Regimes Matter," Post-Print hal-01494498, HAL.
    14. Klaus Grobys, 2012. "Active PortofolioManagement in the Presence of Regime Switching: What Are the Benefits of Defensive Asset Allocation Strategies If the Investor Faces Bear Markets?," 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. 4(1), pages 015-031, June.

  24. Timmermann, Allan & Catão, Luís, 2004. "Country and Industry Dynamics in Stock Returns," CEPR Discussion Papers 4368, C.E.P.R. Discussion Papers.

    Cited by:

    1. John Ammer & Jon Wongswan, 2007. "Cash Flows and Discount Rates, Industry and Country Effects and Co‐Movement in Stock Returns," The Financial Review, Eastern Finance Association, vol. 42(2), pages 211-226, May.
    2. Francesca Carrieri & Vihang Errunza & Sergei Sarkissian, 2012. "The Dynamics of Geographic versus Sectoral Diversification: Is There a Link to the Real Economy?," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 2(04), pages 1-41.
    3. Bekaert, Geert & Hodrick, Robert J. & Zhang, Xiaoyan, 2008. "International stock return comovements," Working Paper Series 931, European Central Bank.
    4. L’Her, Jean-François & Le Moigne, Cécile & Savaria, Patrick, 2007. "Importance relative des effets pays et secteurs dans les marchés développés," L'Actualité Economique, Société Canadienne de Science Economique, vol. 83(2), pages 201-226, juin.
    5. Bai, Ye & Green, Christopher J. & Leger, Lawrence, 2012. "Industry and country factors in emerging market returns: Did the Asian crisis make a difference?," Emerging Markets Review, Elsevier, vol. 13(4), pages 559-580.

  25. Pesaran, M.H. & Timmermann, A., 2004. "‘Real Time Econometrics’," Cambridge Working Papers in Economics 0432, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Bernd Brandl & Christian Keber & Matthias Schuster, 2006. "An automated econometric decision support system: forecasts for foreign exchange trades," 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. 14(4), pages 401-415, December.
    2. 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.
    3. 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.
    4. Chee Kian Leong, 2016. "Credit Risk Scoring with Bayesian Network Models," Computational Economics, Springer;Society for Computational Economics, vol. 47(3), pages 423-446, March.
    5. Heij, Christiaan & van Dijk, Dick & Groenen, Patrick J.F., 2011. "Real-time macroeconomic forecasting with leading indicators: An empirical comparison," International Journal of Forecasting, Elsevier, vol. 27(2), pages 466-481, April.
    6. Carlos Capistrán & Allan Timmermann, 2008. "Forecast Combination With Entry and Exit of Experts," CREATES Research Papers 2008-55, Department of Economics and Business Economics, Aarhus University.
    7. M. Hashem Pesaran, 2010. "Predictability of Asset Returns and the Efficient Market Hypothesis," CESifo Working Paper Series 3116, CESifo.
    8. Timmermann, Allan & Patton, Andrew, 2007. "Learning in Real Time: Theory and Empirical Evidence from the Term Structure of Survey Forecasts," CEPR Discussion Papers 6526, C.E.P.R. Discussion Papers.
    9. Bahram Pesaran & M. Hashem Pesaran, 2010. "Conditional Volatility and Correlations of Weekly Returns and the VaR Analysis of 2008 Stock Market Crash," CESifo Working Paper Series 3023, CESifo.
    10. Phillips, Peter C.B., 2005. "Automated Discovery In Econometrics," Econometric Theory, Cambridge University Press, vol. 21(1), pages 3-20, February.
    11. A. Girardi & R. Golinelli & C. Pappalardo, 2014. "The Role of Indicator Selection in Nowcasting Euro Area GDP in Pseudo Real Time," Working Papers wp919, Dipartimento Scienze Economiche, Universita' di Bologna.
    12. Atsushi Inoue & Barbara Rossi, 2011. "Out-of-sample forecast tests robust to the choice of window size," Working Papers 11-31, Federal Reserve Bank of Philadelphia.
    13. Heij, C. & van Dijk, D.J.C. & Groenen, P.J.F., 2009. "Macroeconomic forecasting with real-time data: an empirical comparison," Econometric Institute Research Papers EI 2009-27, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    14. Geweke, John F. & Horowitz, Joel L. & Pesaran, M. Hashem, 2006. "Econometrics: A Bird's Eye View," IZA Discussion Papers 2458, Institute of Labor Economics (IZA).
    15. Cécile Denis & Daniel Grenouilleau & Kieran Mc Morrow & Werner Röger, 2006. "Calculating potential growth rates and output gaps - A revised production function approach," European Economy - Economic Papers 2008 - 2015 247, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    16. Taipalus, Katja, 2012. "Signaling asset price bubbles with time-series methods," Bank of Finland Research Discussion Papers 7/2012, Bank of Finland.
    17. Richard G. Anderson, 2006. "Replicability, real-time data, and the science of economic research: FRED, ALFRED, and VDC," Review, Federal Reserve Bank of St. Louis, vol. 88(Jan), pages 81-93.
    18. 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.
    19. M. Hashem Pesaran & Bahram Pesaran, 2007. "Volatilities and Conditional Correlations in Futures Markets with a Multivariate t Distribution," CESifo Working Paper Series 2056, CESifo.
    20. Golinelli, Roberto & Parigi, Giuseppe, 2008. "Real-time squared: A real-time data set for real-time GDP forecasting," International Journal of Forecasting, Elsevier, vol. 24(3), pages 368-385.
    21. Proaño, Christian R. & Theobald, Thomas, 2014. "Predicting recessions with a composite real-time dynamic probit model," International Journal of Forecasting, Elsevier, vol. 30(4), pages 898-917.
    22. Pesaran, B. & Pesaran, M.H., 2007. "Modelling Volatilities and Conditional Correlations in Futures Markets with a Multivariate t Distribution," Cambridge Working Papers in Economics 0734, Faculty of Economics, University of Cambridge.

  26. Timmermann, Allan & Guidolin, Massimo, 2004. "Term Structure of Risk Under Alternative Econometric Specifications," CEPR Discussion Papers 4645, C.E.P.R. Discussion Papers.

    Cited by:

    1. C. James Hueng & Ruey Yau, 2006. "Investor preferences and portfolio selection: is diversification an appropriate strategy?," Quantitative Finance, Taylor & Francis Journals, vol. 6(3), pages 255-271.
    2. Andrew Ang & Allan Timmermann, 2011. "Regime Changes and Financial Markets," NBER Working Papers 17182, National Bureau of Economic Research, Inc.
    3. 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.
    4. Erik Kole & Dick Dijk, 2017. "How to Identify and Forecast Bull and Bear Markets?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(1), pages 120-139, January.
    5. Fuertes, Ana-Maria & Olmo, Jose, 2013. "Optimally harnessing inter-day and intra-day information for daily value-at-risk prediction," International Journal of Forecasting, Elsevier, vol. 29(1), pages 28-42.
    6. 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.
    7. 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.
    8. Huang Dashan & Yu Baimin & Lu Zudi & Fabozzi Frank J. & Focardi Sergio & Fukushima Masao, 2010. "Index-Exciting CAViaR: A New Empirical Time-Varying Risk Model," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(2), pages 1-26, March.
    9. Massimo Guidolin, 2011. "Markov Switching Models in Empirical Finance," Working Papers 415, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    10. Henryk Gurgul & Robert Syrek, 2010. "Polish stock market and some foreign markets - dependence analysis by regime-switching copulas," Managerial Economics, AGH University of Science and Technology, Faculty of Management, vol. 8, pages 21-39.
    11. Bakshi, Gurdip & Panayotov, George, 2010. "First-passage probability, jump models, and intra-horizon risk," Journal of Financial Economics, Elsevier, vol. 95(1), pages 20-40, January.
    12. 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.
    13. Tatsuyoshi Okimoto, 2014. "Asymmetric Increasing Trends in Dependence in International Equity Markets," CAMA Working Papers 2014-44, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    14. 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.
    15. CHOLLETE, Loran & HEINEN, Andréas & VALDESOGO, Alfonso, 2008. "Modeling international financial returns with a multivariate regime switching copula," LIDAM Discussion Papers CORE 2008013, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    16. Solange Berstein & Rómulo Chumacero, 2008. "VaR Limits for Pension Funds: An Evaluation," Working Papers 26, Superintendencia de Pensiones, revised May 2008.
    17. 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.
    18. Penaranda, Francisco, 2007. "Portfolio choice beyond the traditional approach," LSE Research Online Documents on Economics 24481, London School of Economics and Political Science, LSE Library.
    19. Cees Diks & Valentyn Panchenko & Dick van Dijk, 2011. "Likelihood-based scoring rules for comparing density forecasts in tails," Post-Print hal-00834423, HAL.
    20. 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.
    21. Chenglu Jin & Thomas Conlon & John Cotter, 2023. "Co-Skewness across Return Horizons," Journal of Financial Econometrics, Oxford University Press, vol. 21(5), pages 1483-1518.
    22. Giuseppe Storti & Luc Bauwens, 2006. "A component GARCH model with time varying weights," Computing in Economics and Finance 2006 388, Society for Computational Economics.
    23. Aliyu, Shehu Usman Rano & Aminu, Abubakar Wambai, 2018. "Economic regimes and stock market performance in Nigeria: Evidence from regime switching model," MPRA Paper 91430, University Library of Munich, Germany, revised 03 Oct 2018.
    24. Kole, Erik & van Dijk, Dick, 2023. "Moments, shocks and spillovers in Markov-switching VAR models," Journal of Econometrics, Elsevier, vol. 236(2).
    25. Dewandaru, Ginanjar & Masih, Rumi & Bacha, Obiyathulla I. & Masih, A. Mansur M., 2014. "The Role of Islamic Asset Classes in the Diversified Portfolios: Mean Variance Spanning Test," MPRA Paper 56857, University Library of Munich, Germany.
    26. Mike K. P. So & Chi-Ming Wong, 2012. "Estimation of multiple period expected shortfall and median shortfall for risk management," Quantitative Finance, Taylor & Francis Journals, vol. 12(5), pages 739-754, March.
    27. 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.
    28. Chang, Kuang-Liang, 2010. "House price dynamics, conditional higher-order moments, and density forecasts," Economic Modelling, Elsevier, vol. 27(5), pages 1029-1039, September.
    29. Rossi, Barbara & Sekhposyan, Tatevik, 2014. "Evaluating predictive densities of US output growth and inflation in a large macroeconomic data set," International Journal of Forecasting, Elsevier, vol. 30(3), pages 662-682.
    30. 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.
    31. Guidolin, Massimo & Ono, Sadayuki, 2006. "Are the dynamic linkages between the macroeconomy and asset prices time-varying?," Journal of Economics and Business, Elsevier, vol. 58(5-6), pages 480-518.
    32. BOUADDI, Mohammed & ROMBOUTS, Jeroen V.K., 2007. "Mixed exponential power asymmetric conditional heteroskedasticity," LIDAM Discussion Papers CORE 2007097, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    33. Chrétien, Stéphane & Coggins, Frank, 2010. "Performance and conservatism of monthly FHS VaR: An international investigation," International Review of Financial Analysis, Elsevier, vol. 19(5), pages 323-333, December.
    34. Alejandro Bernales & Diether W. Beuermann & Gonzalo Cortazar, 2014. "Thinly traded securities and risk management," Estudios de Economia, University of Chile, Department of Economics, vol. 41(1 Year 20), pages 5-48, June.
    35. Kuang-Liang Chang, 2011. "The optimal value-at-risk hedging strategy under bivariate regime switching ARCH framework," Applied Economics, Taylor & Francis Journals, vol. 43(21), pages 2627-2640.
    36. 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.
    37. Ono, Sadayuki, 2019. "Term structure dynamics in a monetary economy with learning," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 730-745.
    38. 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.
    39. Taamouti, Abderrahim, 2009. "Analytical Value-at-Risk and Expected Shortfall under regime-switching," Finance Research Letters, Elsevier, vol. 6(3), pages 138-151, September.
    40. Bec, Frédérique & Gollier, Christian, 2014. "Cyclicality and term structure of Value-at-Risk within a threshold autoregression setup," IDEI Working Papers 835, Institut d'Économie Industrielle (IDEI), Toulouse.
    41. Polanski, Arnold & Stoja, Evarist, 2012. "Efficient evaluation of multidimensional time-varying density forecasts, with applications to risk management," International Journal of Forecasting, Elsevier, vol. 28(2), pages 343-352.
    42. Agata Gemzik-Salwach, 2012. "The Use Of A Value At Risk Measure For The Analysis Of Bank Interest Margins," "e-Finanse", University of Information Technology and Management, Institute of Financial Research and Analysis, vol. 8(4), pages 15-29, February.
    43. Carolina Fugazza & Massimo Guidolin & Giovanna Nicodano, 2007. "Investing for the Long-run in European Real Estate," The Journal of Real Estate Finance and Economics, Springer, vol. 34(1), pages 35-80, January.
    44. Lönnbark, Carl, 2017. "Long vs. short term asymmetry in volatility and the term structure of risk," Finance Research Letters, Elsevier, vol. 23(C), pages 202-209.
    45. Jun Tu, 2010. "Is Regime Switching in Stock Returns Important in Portfolio Decisions?," Management Science, INFORMS, vol. 56(7), pages 1198-1215, July.
    46. Cortazar, Gonzalo & Beuermann, Diether & Bernales, Alejandro, 2013. "Risk Management with Thinly Traded Securities: Methodology and Implementation," IDB Publications (Working Papers) 4647, Inter-American Development Bank.
    47. Klaus Grobys, 2012. "Active PortofolioManagement in the Presence of Regime Switching: What Are the Benefits of Defensive Asset Allocation Strategies If the Investor Faces Bear Markets?," 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. 4(1), pages 015-031, June.

  27. Timmermann, Allan & Elliott, Graham, 2004. "Optimal Forecast Combination Under Regime Switching," CEPR Discussion Papers 4649, C.E.P.R. Discussion Papers.

    Cited by:

    1. Davide Pettenuzzo & Francesco Ravazzolo, 2014. "Optimal portfolio choice under decision-based model combinations," Working Paper 2014/15, Norges Bank.
    2. Favero, Carlo A. & Milani, Fabio, 2005. "Parameter Instability, Model Uncertainty and the Choice of Monetary Policy," CEPR Discussion Papers 4909, C.E.P.R. Discussion Papers.
    3. Valentina Corradi & Norman Swanson, 2013. "A Survey of Recent Advances in Forecast Accuracy Comparison Testing, with an Extension to Stochastic Dominance," Departmental Working Papers 201309, Rutgers University, Department of Economics.
    4. Carlos Capistrán & Allan Timmermann, 2008. "Forecast Combination With Entry and Exit of Experts," CREATES Research Papers 2008-55, Department of Economics and Business Economics, Aarhus University.
    5. Jakub Nowotarski, 2013. "Short-term forecasting of electricity spot prices using model averaging (Krótkoterminowe prognozowanie spotowych cen energii elektrycznej z wykorzystaniem uśredniania modeli)," HSC Research Reports HSC/13/17, Hugo Steinhaus Center, Wroclaw University of Technology.
    6. Sun, Yuying & Hong, Yongmiao & Wang, Shouyang & Zhang, Xinyu, 2023. "Penalized time-varying model averaging," Journal of Econometrics, Elsevier, vol. 235(2), pages 1355-1377.
    7. Lees, Kirdan & Matheson, Troy & Smith, Christie, 2011. "Open economy forecasting with a DSGE-VAR: Head to head with the RBNZ published forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 512-528.
    8. Antoine Mandel & Amir Sani, 2017. "A Machine Learning Approach to the Forecast Combination Puzzle," Working Papers halshs-01317974, HAL.
    9. A.S.M. Arroyo & A. de Juan Fern¨¢ndez, 2014. "Split-then-Combine Method for out-of-sample Combinations of Forecasts," Journal of Business Administration Research, Journal of Business Administration Research, Sciedu Press, vol. 3(1), pages 19-37, April.
    10. George Athanasopoulos & Rob J Hyndman & Nikolaos Kourentzes & Fotios Petropoulos, 2015. "Forecasting with Temporal Hierarchies," Monash Econometrics and Business Statistics Working Papers 16/15, Monash University, Department of Econometrics and Business Statistics.
    11. Norman Swanson & Valentina Corradi, 2006. "Nonparametric Bootstrap Procedures for Predictive Inference Based on Recursive Estimation Schemes," Departmental Working Papers 200618, Rutgers University, Department of Economics.
    12. Mehmet Pinar & Thanasis Stengos & M. Ege Yazgan, 2012. "Is there an Optimal Forecast Combination? A Stochastic Dominance Approach to Forecast Combination Puzzle," Working Paper series 17_12, Rimini Centre for Economic Analysis.
    13. Lima, Luiz Renato Regis de Oliveira & Issler, João Victor, 2007. "A panel data approach to economic forecasting: the bias-corrected average forecast," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 650, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    14. Giacomini, Raffaella & Rossi, Barbara, 2008. "Forecast Comparisons in Unstable Environments," Working Papers 08-04, Duke University, Department of Economics.
    15. Lyócsa, Štefan & Todorova, Neda & Výrost, Tomáš, 2021. "Predicting risk in energy markets: Low-frequency data still matter," Applied Energy, Elsevier, vol. 282(PA).
    16. Yongchen Zhao, 2021. "The robustness of forecast combination in unstable environments: a Monte Carlo study of advanced algorithms," Empirical Economics, Springer, vol. 61(1), pages 173-199, July.
    17. Wagner Piazza Gaglianone & João Victor Issler, 2014. "Microfounded Forecasting," Working Papers Series 372, Central Bank of Brazil, Research Department.
    18. Pierre Guérin & Danilo Leiva-Leon, 2015. "Model Averaging in Markov-Switching Models: Predicting National Recessions with Regional Data," Staff Working Papers 15-24, Bank of Canada.
    19. Valentina Corradi & Norman Swanson, 2004. "Bootstrap Procedures for Recursive Estimation Schemes With Applications to Forecast Model Selection," Departmental Working Papers 200418, Rutgers University, Department of Economics.
    20. 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.
    21. Steff De Visscher & Markus Eberhardt & Gerdie Everaert, 2017. "Measuring productivity and absorptive capacity evolution," Discussion Papers 2017-11, University of Nottingham, GEP.
    22. 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.
    23. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1203-1324, Elsevier.
    24. Ayadi, Mohamed A. & Lazrak, Skander & Liao, Yusui & Welch, Robert, 2018. "Performance of fixed-income mutual funds with regime-switching models," The Quarterly Review of Economics and Finance, Elsevier, vol. 69(C), pages 217-231.
    25. Rianne Legerstee & Philip Hans Franses, 2015. "Does Disagreement Amongst Forecasters Have Predictive Value?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(4), pages 290-302, July.
    26. Hyun Hak Kim, 2013. "Forecasting Macroeconomic Variables Using Data Dimension Reduction Methods: The Case of Korea," Working Papers 2013-26, Economic Research Institute, Bank of Korea.
    27. 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.
    28. 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.
    29. Antoine Mandel & Amir Sani, 2016. "Learning Time-Varying Forecast Combinations," Documents de travail du Centre d'Economie de la Sorbonne 16036r, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Sep 2016.
    30. Krüger Fabian & Pohlmeier Winfried & Mokinski Frieder, 2011. "Combining Survey Forecasts and Time Series Models: The Case of the Euribor," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(1), pages 63-81, February.
    31. Mehmet Pinar & Thanasis Stengos & M. Ege Yazgan, 2018. "Quantile forecast combination using stochastic dominance," Empirical Economics, Springer, vol. 55(4), pages 1717-1755, December.
    32. Barrow, Devon K. & Kourentzes, Nikolaos, 2016. "Distributions of forecasting errors of forecast combinations: Implications for inventory management," International Journal of Production Economics, Elsevier, vol. 177(C), pages 24-33.
    33. Barbara Rossi, 2019. "Forecasting in the presence of instabilities: How do we know whether models predict well and how to improve them," Economics Working Papers 1711, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2021.
    34. Georgios Papadopoulos & Dionysios Chionis & Nikolaos P. Rachaniotis, 2018. "Macro-financial linkages during tranquil and crisis periods: evidence from stressed economies," Risk Management, Palgrave Macmillan, vol. 20(2), pages 142-166, May.
    35. Eo, Yunjong & Kang, Kyu Ho, 2020. "The effects of conventional and unconventional monetary policy on forecasting the yield curve," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
    36. Marcus Cobb, 2009. "Forecasting Chilean Inflation From Disaggregate Components," Working Papers Central Bank of Chile 545, Central Bank of Chile.
    37. Zhe Huang & Franck Martin, 2017. "Optimal pairs trading strategies in a cointegration framework," Working Papers halshs-01566803, HAL.
    38. Bin Chen & Kenwin Maung, 2020. "Time-varying Forecast Combination for High-Dimensional Data," Papers 2010.10435, arXiv.org.
    39. Elena Andreou & Eric Ghysels & Constantinos Kourouyiannis, 2012. "Robust volatility forecasts in the presence of structural breaks," University of Cyprus Working Papers in Economics 08-2012, University of Cyprus Department of Economics.
    40. Krüger, Fabian & Nolte, Ingmar, 2016. "Disagreement versus uncertainty: Evidence from distribution forecasts," Journal of Banking & Finance, Elsevier, vol. 72(S), pages 172-186.
    41. Kenwin Maung, 2021. "Estimating high-dimensional Markov-switching VARs," Papers 2107.12552, arXiv.org.
    42. Daniel Borup & Martin Thyrsgaard, 2017. "Statistical tests for equal predictive ability across multiple forecasting methods," CREATES Research Papers 2017-19, Department of Economics and Business Economics, Aarhus University.
    43. Sylvia Kaufmann, 2016. "Hidden Markov models in time series, with applications in economics," Working Papers 16.06, Swiss National Bank, Study Center Gerzensee.
    44. Chen Zhuo & Yang Yuhong, 2007. "Time Series Models for Forecasting: Testing or Combining?," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 11(1), pages 56-90, March.

  28. Pesaran, M.H. & Pettenuzzo, D. & Timmermann, A., 2004. "‘Forecasting Time Series Subject to Multiple Structural Breaks’," Cambridge Working Papers in Economics 0433, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Bauwens, Luc & Rombouts, Jeroen V.K., 2012. "On marginal likelihood computation in change-point models," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3415-3429.
    2. 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).
    3. Dimitris, Korobilis, 2013. "Forecasting with Factor Models: A Bayesian Model Averaging Perspective," MPRA Paper 52724, University Library of Munich, Germany.
    4. Pesaran, M.H. & Pettenuzzo, D. & Timmermann, A., 2006. "Learning, Structural Instability and Present Value Calculations," Cambridge Working Papers in Economics 0602, Faculty of Economics, University of Cambridge.
    5. Timmermann, Allan & Pettenuzzo, Davide, 2016. "Forecasting Macroeconomic Variables under Model Instability," CEPR Discussion Papers 11355, C.E.P.R. Discussion Papers.
    6. Robert J. Barro & Tao Jin, 2016. "Rare Events and Long-Run Risks," NBER Working Papers 21871, National Bureau of Economic Research, Inc.
    7. Dionne, Georges & Maalaoui Chun, Olfa, 2013. "Default and liquidity regimes in the bond market during the 2002-2012 period," Working Papers 13-4, HEC Montreal, Canada Research Chair in Risk Management.
    8. Karlsson, Sune, 2012. "Forecasting with Bayesian Vector Autoregressions," Working Papers 2012:12, Örebro University, School of Business.
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    105. Andrew C. Chang & Trace J. Levinson, 2023. "Raiders of the lost high‐frequency forecasts: New data and evidence on the efficiency of the Fed's forecasting," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(1), pages 88-104, January.
    106. Tara M. Sinclair & Fred Joutz & Herman O. Stekler, 2009. "Can the Fed Predict the State of the Economy?," Working Papers 2009-001, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting, revised Mar 2010.
    107. Jaroslav Borovicka, 2016. "Identifying ambiguity shocks in business cycle models using survey data," 2016 Meeting Papers 1615, Society for Economic Dynamics.
    108. George A. Christodoulakis & Emmanuel C. Mamatzakis, 2008. "An assessment of the EU growth forecasts under asymmetric preferences," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(6), pages 483-492.
    109. Michael P. Clements, 2018. "Do Macroforecasters Herd?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(2-3), pages 265-292, March.
    110. Pierdzioch, Christian & Risse, Marian & Rohloff, Sebastian, 2014. "The international business cycle and gold-price fluctuations," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(2), pages 292-305.
    111. Timmermann Allan & Capistrán Carlos, 2006. "Disagreement and Biases in Inflation Expectations," Working Papers 2006-07, Banco de México.
    112. Pierdzioch, Christian & Risse, Marian & Rohloff, Sebastian, 2016. "A quantile-boosting approach to forecasting gold returns," The North American Journal of Economics and Finance, Elsevier, vol. 35(C), pages 38-55.
    113. Nazaria Solferino & Robert Waldmann, 2010. "Predicting the signs of forecast errors," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(5), pages 476-485.
    114. Bas Scheer, 2022. "Addressing Unemployment Rate Forecast Errors in Relation to the Business Cycle," CPB Discussion Paper 434, CPB Netherlands Bureau for Economic Policy Analysis.
    115. Hamid Baghestani, 2022. "Mortgage rate predictability and consumer home-buying assessments," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 46(3), pages 593-603, July.
    116. Sean D. Campbell, 2005. "Stock market volatility and the Great Moderation," Finance and Economics Discussion Series 2005-47, Board of Governors of the Federal Reserve System (U.S.).
    117. Reitz, Stefan & Stadtmann, Georg & Taylor, Mark P., 2010. "The effects of Japanese interventions on FX-forecast heterogeneity," Economics Letters, Elsevier, vol. 108(1), pages 62-64, July.
    118. Yanwei Jia & Jussi Keppo & Ville Satopää, 2023. "Herding in Probabilistic Forecasts," Management Science, INFORMS, vol. 69(5), pages 2713-2732, May.
    119. Papastamos, Dimitrios & Matysiak, George & Stevenson, Simon, 2015. "Assessing the accuracy and dispersion of real estate investment forecasts," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 141-152.
    120. Meredith Beechey & P�r Österholm, 2014. "Policy interest-rate expectations in Sweden: a forecast evaluation," Applied Economics Letters, Taylor & Francis Journals, vol. 21(14), pages 984-991, September.
    121. Jonsson, Thomas & Österholm, Pär, 2009. "The Properties of Survey-Based Inflation Expectations in Sweden," Working Papers 114, National Institute of Economic Research.
    122. Robert P. Lieli & Augusto Nieto-Barthaburu, 2023. "Forecasting with Feedback," Papers 2308.15062, arXiv.org, revised Jan 2024.
    123. Ásgeir Daníelsson, 2008. "Accuracy in forecasting macroeconomic variables in Iceland," Economics wp39, Department of Economics, Central bank of Iceland.
    124. Pierdzioch, Christian & Rülke, Jan-Christoph & Stadtmann, Georg, 2012. "On the loss function of the Bank of Canada: A note," Economics Letters, Elsevier, vol. 115(2), pages 155-159.
    125. Eliana González & Munir Jalil & Jose Vicente Romero Chamorro, 2010. "Inflación y expectativas de inflación en Colombia," Borradores de Economia 7307, Banco de la Republica.
    126. Julie Bennett & Michael T. Owyang, 2022. "On the Relative Performance of Inflation Forecasts," Review, Federal Reserve Bank of St. Louis, vol. 104(2), pages 131-148.
    127. Wang, Yiyao & Lee, Tae-Hwy, 2014. "Asymmetric loss in the Greenbook and the Survey of Professional Forecasters," International Journal of Forecasting, Elsevier, vol. 30(2), pages 235-245.
    128. 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.
    129. Christian Pierdzioch & Jan-Christoph Rülke & Georg Stadtmann, 2012. "Exchange-rate forecasts and asymmetric loss: empirical evidence for the yen/dollar exchange rate," Applied Economics Letters, Taylor & Francis Journals, vol. 19(18), pages 1759-1763, December.
    130. 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.
    131. Krol, Robert, 2013. "Evaluating state revenue forecasting under a flexible loss function," International Journal of Forecasting, Elsevier, vol. 29(2), pages 282-289.
    132. Kajal Lahiri & Fushang Liu, 2009. "On the Use of Density Forecasts to Identify Asymmetry in Forecasters' Loss Functions," Discussion Papers 09-03, University at Albany, SUNY, Department of Economics.
    133. Gneiting, Tilmann, 2011. "Quantiles as optimal point forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 197-207, April.
    134. Hamid Baghestani & Cassia Marchon, 2015. "On the accuracy of private forecasts of inflation and growth in Brazil," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 39(2), pages 370-381, April.
    135. Nakazono, Yoshiyuki, 2013. "Strategic behavior of Federal Open Market Committee board members: Evidence from members’ forecasts," Journal of Economic Behavior & Organization, Elsevier, vol. 93(C), pages 62-70.
    136. Bürgi, Constantin, 2017. "Bias, rationality and asymmetric loss functions," Economics Letters, Elsevier, vol. 154(C), pages 113-116.
    137. Jörg Döpke & Ulrich Fritsche & Christian Pierdzioch, 2015. "Predicting Recessions With Boosted Regression Trees," Working Papers 2015-004, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    138. Boskabadi, Elahe, 2022. "Economic policy uncertainty and forecast bias in the survey of professional forecasters," MPRA Paper 115081, University Library of Munich, Germany.
    139. Kirstin Hubrich & Simone Manganelli, 2014. "Comment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(4), pages 506-509, October.
    140. Rülke Jan-Christoph, 2012. "Do Private Sector Forecasters Desire to Deviate From the German Council of Economic Experts?," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 232(4), pages 414-428, August.
    141. 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).
    142. Eliana González & Munir Jalil & José Vicente Romero, 2010. "Inflación y expectativas de inflación en Colombia," Borradores de Economia 618, Banco de la Republica de Colombia.
    143. 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.
    144. Giovannelli, Alessandro & Pericoli, Filippo Maria, 2020. "Are GDP forecasts optimal? Evidence on European countries," International Journal of Forecasting, Elsevier, vol. 36(3), pages 963-973.
    145. Gneiting, Tilmann, 2011. "Quantiles as optimal point forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 197-207.
    146. Jan-Christoph Rülke, 2011. "Do private sector forecasters desire to deviate from the German council of economic experts?," WHU Working Paper Series - Economics Group 11-04, WHU - Otto Beisheim School of Management.
    147. Pierdzioch, Christian & Rülke, Jan-Christoph & Stadtmann, Georg, 2013. "A note on forecasting the prices of gold and silver: Asymmetric loss and forecast rationality," The Quarterly Review of Economics and Finance, Elsevier, vol. 53(3), pages 294-301.
    148. Lee, Tae-Hwy & Yang, Yang, 2006. "Bagging binary and quantile predictors for time series," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 465-497.
    149. Pablo Pincheira, 2010. "A Real Time Evaluation of the Central Bank of Chile GDP Growth Forecasts," Working Papers Central Bank of Chile 556, Central Bank of Chile.
    150. Döpke, Jörg & Müller, Karsten & Tegtmeier, Lars, 2018. "The economic value of business cycle forecasts for potential investors – Evidence from Germany," Research in International Business and Finance, Elsevier, vol. 46(C), pages 445-461.
    151. Pedro Henrique Melo Albuquerque & Yaohao Peng & João Pedro Fontoura da Silva, 2022. "Making the whole greater than the sum of its parts: A literature review of ensemble methods for financial time series forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(8), pages 1701-1724, December.
    152. Jörg Döpke & Ulrich Fritsche & Christian Pierdzioch, 2015. "Predicting Recessions in Germany With Boosted Regression Trees," Macroeconomics and Finance Series 201505, University of Hamburg, Department of Socioeconomics.
    153. 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.
    154. Sergey V. Smirnov, 2014. "Predicting US Recessions: Does a Wishful Bias Exist?," HSE Working papers WP BRP 77/EC/2014, National Research University Higher School of Economics.
    155. Hamid Baghestani, 2013. "Evaluating Federal Reserve predictions of growth in consumer spending," Applied Economics, Taylor & Francis Journals, vol. 45(13), pages 1637-1646, May.
    156. Young Bin Ahn & Yoichi Tsuchiya, 2022. "Consumer’s perceived and expected inflation in Japan—irrationality or asymmetric loss?," Empirical Economics, Springer, vol. 63(3), pages 1247-1292, September.

  30. Timmermann, Allan & Patton, Andrew, 2003. "Properties of Optimal Forecasts," CEPR Discussion Papers 4037, C.E.P.R. Discussion Papers.

    Cited by:

    1. Romulo A. Chumacero, 2004. "Forecasting Chilean Industrial Production with Automated Procedures," Econometric Society 2004 Latin American Meetings 177, Econometric Society.
    2. Capistrán Carlos & López Moctezuma Gabriel, 2008. "Experts' Macroeconomics Expectations: An Evaluation of Mexican Short-Run Forecasts," Working Papers 2008-11, Banco de México.
    3. 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.
    4. Romulo A. Chumacero, 2004. "Forecasting Chilean Industrial Production and Sales with Automated Procedures," Computing in Economics and Finance 2004 112, Society for Computational Economics.
    5. Timmermann, Allan & Elliott, Graham & Komunjer, Ivana, 2003. "Estimating Loss Function Parameters," CEPR Discussion Papers 3821, C.E.P.R. Discussion Papers.
    6. Anatolyev, Stanislav, 2009. "Dynamic modeling under linear-exponential loss," Economic Modelling, Elsevier, vol. 26(1), pages 82-89, January.
    7. Thomas Jobert & Lionel Persyn, 2012. "Quelques constats sur les prévisions conjoncturelles de la croissance française," Revue d'économie politique, Dalloz, vol. 122(6), pages 833-849.
    8. 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.
    9. Carmona, Carlos Capistran, 2005. "Bias in Federal Reserve Inflation Forecasts: Is the Federal Reserve Irrational or Just Cautious?," University of California at San Diego, Economics Working Paper Series qt6v28v0b6, Department of Economics, UC San Diego.
    10. 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.
    11. Timmermann Allan & Capistrán Carlos, 2006. "Disagreement and Biases in Inflation Expectations," Working Papers 2006-07, Banco de México.
    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. Patton, Andrew J., 2011. "Volatility forecast comparison using imperfect volatility proxies," Journal of Econometrics, Elsevier, vol. 160(1), pages 246-256, January.
    14. McCracken, Michael W., 2007. "Asymptotics for out of sample tests of Granger causality," Journal of Econometrics, Elsevier, vol. 140(2), pages 719-752, October.
    15. 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.

  31. Timmermann, Allan & Elliott, Graham & Komunjer, Ivana, 2003. "Estimating Loss Function Parameters," CEPR Discussion Papers 3821, C.E.P.R. Discussion Papers.

    Cited by:

    1. Graham Elliott & Ivana Komunjer & Allan Timmermann, 2008. "Biases in Macroeconomic Forecasts: Irrationality or Asymmetric Loss?," Journal of the European Economic Association, MIT Press, vol. 6(1), pages 122-157, March.
    2. Stan Hurn & Ralf Becker, 2006. "Testing for nonlinearity in mean in the presence of heteroskedasticity," Stan Hurn Discussion Papers 2006-02, School of Economics and Finance, Queensland University of Technology.
    3. Siliverstovs, Boriss & Engsted, Tom & Haldrup, Niels, 2002. "Long-Run Forecasting in Multicointegrated Systems," Finance Working Papers 02-14, University of Aarhus, Aarhus School of Business, Department of Business Studies.
    4. Basu, Sudipta & Markov, Stanimir, 2004. "Loss function assumptions in rational expectations tests on financial analysts' earnings forecasts," Journal of Accounting and Economics, Elsevier, vol. 38(1), pages 171-203, December.
    5. Yang Yang & Tae-Hwy Lee, 2004. "Bagging Binary Predictors for Time Series," Econometric Society 2004 Far Eastern Meetings 512, Econometric Society.
    6. Allan Timmermann & Andrew J. Patton, 2004. "Properties of Optimal Forecasts," Econometric Society 2004 North American Winter Meetings 234, Econometric Society.
    7. Adrian Pagan & Hashem Pesaran, 2007. "Econometric Analysis of Structural Systems with Permanent and Transitory Shocks. Working paper #7," NCER Working Paper Series 7, National Centre for Econometric Research.
    8. Martin Skitmore & Franco K. T. Cheung, 2007. "Explorations in specifying construction price forecast loss functions," Construction Management and Economics, Taylor & Francis Journals, vol. 25(5), pages 449-465.
    9. Lee, Tae-Hwy & Yang, Yang, 2006. "Bagging binary and quantile predictors for time series," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 465-497.
    10. Pedro Henrique Melo Albuquerque & Yaohao Peng & João Pedro Fontoura da Silva, 2022. "Making the whole greater than the sum of its parts: A literature review of ensemble methods for financial time series forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(8), pages 1701-1724, December.
    11. 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.

  32. Timmermann, Allan & Lunde, Asger, 2003. "Duration Dependence in Stock Prices: An Analysis of Bull and Bear Markets," CEPR Discussion Papers 4104, C.E.P.R. Discussion Papers.

    Cited by:

    1. Richard Copp & Michael L. Kremmer & Eduardo Roca, 2010. "Should funds invest in socially responsible investments during downturns?," Accounting Research Journal, Emerald Group Publishing Limited, vol. 23(3), pages 254-266, November.
    2. Don Harding & Adrian Pagan, 2009. "An econometric analysis of some models for constructed binary time series," CAMA Working Papers 2009-08, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    3. Rose Cunningham & Ilan Kolet, 2007. "Housing Market Cycles and Duration Dependence in the United States and Canada," Staff Working Papers 07-2, Bank of Canada.
    4. Ashraf, Dawood & Mohammad, Nazeeruddin, 2014. "Matching perception with the reality—Performance of Islamic equity investments," Pacific-Basin Finance Journal, Elsevier, vol. 28(C), pages 175-189.
    5. Lu, Tsung-Hsun & Chen, Yi-Chi & Hsu, Yu-Chin, 2015. "Trend definition or holding strategy: What determines the profitability of candlestick charting?," Journal of Banking & Finance, Elsevier, vol. 61(C), pages 172-183.
    6. Erik Kole & Dick Dijk, 2017. "How to Identify and Forecast Bull and Bear Markets?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(1), pages 120-139, January.
    7. Beata Bieszk-Stolorz & Krzysztof Dmytrów, 2021. "Evaluation of Changes on World Stock Exchanges in Connection with the SARS-CoV-2 Pandemic. Survival Analysis Methods," Risks, MDPI, vol. 9(7), pages 1-19, June.
    8. Ashraf, Dawood & Rizwan, Muhammad Suhail & Ahmad, Ghufran, 2022. "Islamic equity investments and the COVID-19 pandemic," Pacific-Basin Finance Journal, Elsevier, vol. 73(C).
    9. Chen, Shiu-Sheng, 2010. "Do higher oil prices push the stock market into bear territory?," Energy Economics, Elsevier, vol. 32(2), pages 490-495, March.
    10. Felix Haase & Matthias Neuenkirch, 2020. "Predictability of Bull and Bear Markets: A New Look at Forecasting Stock Market Regimes (and Returns) in the US," Research Papers in Economics 2020-01, University of Trier, Department of Economics.
    11. Alain-Philippe Fortin & Patrick Gagliardini & Olivier Scaillet, 2022. "Eigenvalue tests for the number of latent factors in short panels," Papers 2210.16042, arXiv.org.
    12. Linh Nguyen & Vilém Novák & Soheyla Mirshahi, 2020. "Trend‐cycle Estimation Using Fuzzy Transform and Its Application for Identifying Bull and Bear Phases in Markets," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 27(3), pages 111-124, July.
    13. Kirby, Chris, 2023. "A closer look at the regime-switching evidence of bull and bear markets," Finance Research Letters, Elsevier, vol. 52(C).
    14. Kurov, Alexander & Olson, Eric & Zaynutdinova, Gulnara R., 2022. "When does the fed care about stock prices?," Journal of Banking & Finance, Elsevier, vol. 142(C).
    15. Liu, Jia & Maheu, John M & Song, Yong, 2023. "Identification and Forecasting of Bull and Bear Markets using Multivariate Returns," MPRA Paper 119515, University Library of Munich, Germany.
    16. Woodward, George & Brooks, Robert, 2009. "Do realized betas exhibit up/down market tendencies?," International Review of Economics & Finance, Elsevier, vol. 18(3), pages 511-519, June.
    17. Mohammad, Nazeeruddin & Ashraf, Dawood, 2015. "The Market Timing Ability and Return Performance of Islamic Equities: an Empirical Study," Working Papers 1436-6, The Islamic Research and Teaching Institute (IRTI).
    18. 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.
    19. Dumitriu, Ramona & Stefanescu, Razvan & Nistor, Costel, 2010. "Systematic risks for the financial and for the non-financial Romanian companies," MPRA Paper 41636, University Library of Munich, Germany, revised 28 Feb 2010.
    20. Maheu, John M. & McCurdy, Thomas H. & Song, Yong, 2021. "Bull and bear markets during the COVID-19 pandemic," Finance Research Letters, Elsevier, vol. 42(C).
    21. 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.
    22. Vitor Castro, 2011. "The Portuguese Stock Market Cycle: Chronology and Duration Dependence," GEMF Working Papers 2011-17, GEMF, Faculty of Economics, University of Coimbra.
    23. Liao, Li-Chuan & Chou, Ray Yeutien & Chiu, Banghan, 2013. "Anchoring effect on foreign institutional investors’ momentum trading behavior: Evidence from the Taiwan stock market," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 72-91.
    24. Zhang, Chuanhai & Zhang, Zhengjun & Xu, Mengyu & Peng, Zhe, 2023. "Good and bad self-excitation: Asymmetric self-exciting jumps in Bitcoin returns," Economic Modelling, Elsevier, vol. 119(C).
    25. John M Maheu & Thomas H McCurdy & Yong Song, 2010. "Components of bull and bear markets: bull corrections and bear rallies," Working Papers tecipa-402, University of Toronto, Department of Economics.
    26. Asif, Raheel & Frömmel, Michael & Mende, Alexander, 2022. "The crisis alpha of managed futures: Myth or reality?," International Review of Financial Analysis, Elsevier, vol. 80(C).
    27. Fernando López & Mariano Matilla-García & Jesús Mur & Manuel Ruiz Marín, 2021. "Statistical Tests of Symbolic Dynamics," Mathematics, MDPI, vol. 9(8), pages 1-21, April.
    28. Mr. Marco Terrones & Mr. Ayhan Kose & Mr. Stijn Claessens, 2011. "Financial Cycles: What? How? When?," IMF Working Papers 2011/076, International Monetary Fund.
    29. Yong Song & Tomasz Wo'zniak, 2020. "Markov Switching," Papers 2002.03598, arXiv.org.
    30. Yehong Liu & Guosheng Yin, 2018. "Average Holding Price," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 13(01), pages 1-20, March.
    31. Pätäri, Eero & Ahmed, Sheraz & Luukka, Pasi & Yeomans, Julian Scott, 2023. "Can monthly-return rank order reveal a hidden dimension of momentum? The post-cost evidence from the U.S. stock markets," The North American Journal of Economics and Finance, Elsevier, vol. 65(C).
    32. Luca Agnello & Vitor Castro & Ricardo Sousa, 2019. "The Benevolence of Time, Sound Macroeconomic Environment and Governance Quality on the Duration of Sovereign Ratings Phases," Working Papers 34, European Stability Mechanism.
    33. Li, Ming-Yuan Leon, 2009. "Value or volume strategy?," Finance Research Letters, Elsevier, vol. 6(4), pages 210-218, December.
    34. B M, Lithin & chakraborty, Suman & iyer, Vishwanathan & M N, Nikhil & ledwani, Sanket, 2022. "Modeling asymmetric sovereign bond yield volatility with univariate GARCH models: Evidence from India," MPRA Paper 117067, University Library of Munich, Germany, revised 05 Jan 2023.
    35. Straetmans, S.T.M. & Candelon, B. & Ahmed, J., 2012. "Predicting and capitalizing on stock market bears in the U.S," Research Memorandum 019, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    36. Sabri Boubaker & Zhenya Liu & Yaosong Zhan, 2022. "Risk management for crude oil futures: an optimal stopping-timing approach," Annals of Operations Research, Springer, vol. 313(1), pages 9-27, June.
    37. Ferrer Fernández, María & Henry, Ólan & Pybis, Sam & Stamatogiannis, Michalis P., 2023. "Can we forecast better in periods of low uncertainty? The role of technical indicators," Journal of Empirical Finance, Elsevier, vol. 71(C), pages 1-12.
    38. He, Qing & Qian, Zongxin & Fei, Zhe & Chong, Terence Tai Leung, 2016. "Do Speculative Bubbles Migrate in the Chinese Stock Market?," MPRA Paper 80575, University Library of Munich, Germany.
    39. Chen, Shiu-Sheng, 2011. "Lack of consumer confidence and stock returns," Journal of Empirical Finance, Elsevier, vol. 18(2), pages 225-236, March.
    40. Fernando Henrique De Paula E Silva Mendes & Guilherme Valle Mour, 2014. "Evidências De Bull E Bear Market No Índice Bovespa: Uma Aplicação De Modelos De Regime Markoviano E Duration Dependence," Anais do XLI Encontro Nacional de Economia [Proceedings of the 41st Brazilian Economics Meeting] 138, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    41. Shyh-Wei Chen & Chung-Hua Shen, 2007. "Evidence of the duration-dependence from the stock markets in the Pacific Rim economies," Applied Economics, Taylor & Francis Journals, vol. 39(11), pages 1461-1474.
    42. Ben Sita, Bernard & Abdallah, Wissam, 2014. "Volatility links between the home and the host market for U.K. dual-listed stocks on U.S. markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 33(C), pages 183-199.
    43. Adrian pagan & Don Harding, 2006. "The Econometric Analysis of Constructed Binary Time Series. Working paper #1," NCER Working Paper Series 1, National Centre for Econometric Research.
    44. Paulo M.M. Rodrigues & João Cruz, 2018. "Structural Changes in the Duration of Bull Markets and Business Cycle Dynamics," Working Papers w201814, Banco de Portugal, Economics and Research Department.
    45. Min‐Hsien Chiang & Tsai‐Yin Lin & Chih‐Hsien Jerry Yu, 2009. "Liquidity Provision of Limit Order Trading in the Futures Market Under Bull and Bear Markets," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 36(7‐8), pages 1007-1038, September.
    46. Benjamin Chabot & Eric Ghysels & Ravi Jagannathan, 2014. "Momentum Trading, Return Chasing and Predictable Crashes," Working Paper Series WP-2014-27, Federal Reserve Bank of Chicago.
    47. Mehmet Balcilar & Rangan Gupta & Ricardo M. Sousa & Mark E. Wohar, 2020. "Linking U.S. State-Level Housing Market Returns and the Consumption-(Dis)Aggregate Wealth Ratio," Working Papers 202094, University of Pretoria, Department of Economics.
    48. Shiu‐Sheng Chen, 2007. "Does Monetary Policy Have Asymmetric Effects on Stock Returns?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(2‐3), pages 667-688, March.
    49. Pesaran, M. Hashem & Timmermann, Allan, 2006. "Testing Dependence among Serially Correlated Multi-Category Variables," IZA Discussion Papers 2196, Institute of Labor Economics (IZA).
    50. Jia Liu & John M. Maheu, 2018. "Improving Markov switching models using realized variance," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(3), pages 297-318, April.
    51. Chiang, Min-Hsien & Huang, Hsin-Yi, 2011. "Stock market momentum, business conditions, and GARCH option pricing models," Journal of Empirical Finance, Elsevier, vol. 18(3), pages 488-505, June.
    52. Mahadeo, Scott M.R. & Heinlein, Reinhold & Legrenzi, Gabriella D., 2019. "Energy contagion analysis: A new perspective with application to a small petroleum economy," Energy Economics, Elsevier, vol. 80(C), pages 890-903.
    53. Bejaoui, Azza & Karaa, Adel, 2016. "Revisiting the bull and bear markets notions in the Tunisian stock market: New evidence from multi-state duration-dependence Markov-switching models," Economic Modelling, Elsevier, vol. 59(C), pages 529-545.
    54. Yuanyuan Zhang & Stephen Chan & Jeffrey Chu & Hana Sulieman, 2020. "On the Market Efficiency and Liquidity of High-Frequency Cryptocurrencies in a Bull and Bear Market," JRFM, MDPI, vol. 13(1), pages 1-14, January.
    55. Tran, Thuy Nhung, 2022. "The Volatility of the Stock Market and Financial Cycle: GARCH Family Models," Jurnal Ekonomi Malaysia, Faculty of Economics and Business, Universiti Kebangsaan Malaysia, vol. 56(1), pages 151-168.
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    3. Mehmet Balcilar & Nico Katzke & Rangan Gupta, 2015. "Identifying Periods of US Housing Market Explosivity," Working Papers 201544, University of Pretoria, Department of Economics.
    4. Tae-Hwy Lee & Shahnaz Parsaeian & Aman Ullah, 2022. "Forecasting under Structural Breaks Using Improved Weighted Estimation," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202212, University of Kansas, Department of Economics.
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    105. Jun Lu & Shao Yi, 2022. "Autoencoding Conditional GAN for Portfolio Allocation Diversification," Papers 2207.05701, arXiv.org.
    106. Bachar Fakhry & Christian Richter, 2015. "Is the sovereign debt market efficient? Evidence from the US and German sovereign debt markets," International Economics and Economic Policy, Springer, vol. 12(3), pages 339-357, September.
    107. CIOACĂ, Sorin-Iulian, 2015. "Liquidity And Informational Inefficiency. The Case Of Romania," Studii Financiare (Financial Studies), Centre of Financial and Monetary Research "Victor Slavescu", vol. 19(1), pages 80-92.
    108. Choudhry, Taufiq & Jayasekera, Ranadeva, 2014. "Market efficiency during the global financial crisis: Empirical evidence from European banks," Journal of International Money and Finance, Elsevier, vol. 49(PB), pages 299-318.
    109. Nomikos, Nikos K. & Doctor, Kaizad, 2013. "Economic significance of market timing rules in the Forward Freight Agreement markets," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 52(C), pages 77-93.
    110. Camelia Oprean, 2012. "Testing the financial market informational efficiency in emerging states," Review of Applied Socio-Economic Research, Pro Global Science Association, vol. 4(2), pages 181-190, Decembre.
    111. Krzysztof DRACHAL, 2015. "The Structural Stability of a One-Day Risk Premium in View of the Recent Financial Crisis," Expert Journal of Economics, Sprint Investify, vol. 3(2), pages 136-142.
    112. Cheol‐Ho Park & Scott H. Irwin, 2007. "What Do We Know About The Profitability Of Technical Analysis?," Journal of Economic Surveys, Wiley Blackwell, vol. 21(4), pages 786-826, September.
    113. Xu Gong & Mengjie Li & Keqin Guan & Chuanwang Sun, 2023. "Climate change attention and carbon futures return prediction," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(9), pages 1261-1288, September.
    114. Sahar Afshan & Arshian Sharif & Abdelmohsen A. Nassani & Muhammad M. Q. Abro & Rubeena Batool & Khalid Zaman, 2021. "The role of information and communication technology (internet penetration) on Asian stock market efficiency: Evidence from quantile‐on‐quantile cointegration and causality approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2307-2324, April.
    115. Basak, Suryoday & Kar, Saibal & Saha, Snehanshu & Khaidem, Luckyson & Dey, Sudeepa Roy, 2019. "Predicting the direction of stock market prices using tree-based classifiers," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 552-567.
    116. Asal, Maher, 2016. "Testing for the presence of skill in Swedish mutual fund performance: Evidence from a bootstrap analysis," Journal of Economics and Business, Elsevier, vol. 88(C), pages 22-35.
    117. Ben Moews, 2023. "On random number generators and practical market efficiency," Papers 2305.17419, arXiv.org, revised Jul 2023.
    118. Dan Gabriel ANGHEL, 2017. "Intraday Market Efficiency for a Typical Central and Eastern European Stock Market: The Case of Romania," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 88-109, September.
    119. Kristoufek, Ladislav, 2019. "Are the crude oil markets really becoming more efficient over time? Some new evidence," Energy Economics, Elsevier, vol. 82(C), pages 253-263.
    120. Reboredo, Juan C. & Wen, Xiaoqian, 2015. "Are China’s new energy stock prices driven by new energy policies?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 624-636.
    121. Rechenthin, Michael & Street, W. Nick, 2013. "Using conditional probability to identify trends in intra-day high-frequency equity pricing," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(24), pages 6169-6188.
    122. 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.
    123. Pedro Pires Ribeiro & José Dias Curto, 2018. "How do zero-coupon inflation swaps predict inflation rates in the euro area? Evidence of efficiency and accuracy on 1-year contracts," Empirical Economics, Springer, vol. 54(4), pages 1451-1475, June.
    124. David Ubilava, 2014. "El Niño Southern Oscillation and the fishmeal–soya bean meal price ratio: regime-dependent dynamics revisited," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 41(4), pages 583-604.
    125. Konstandinos Chourmouziadis & Dimitra K. Chourmouziadou & Prodromos D. Chatzoglou, 2021. "Embedding Four Medium-Term Technical Indicators to an Intelligent Stock Trading Fuzzy System for Predicting: A Portfolio Management Approach," Computational Economics, Springer;Society for Computational Economics, vol. 57(4), pages 1183-1216, April.
    126. Mishra, Sasmita & Padhy, Sudarsan & Mishra, Satya Narayan & Misra, Satya Narayan, 2021. "A novel LASSO – TLBO – SVR hybrid model for an efficient portfolio construction," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).
    127. Katusiime, Lorna & Shamsuddin, Abul & Agbola, Frank W., 2015. "Foreign exchange market efficiency and profitability of trading rules: Evidence from a developing country," International Review of Economics & Finance, Elsevier, vol. 35(C), pages 315-332.
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    129. Erol Eğrioğlu & Robert Fildes, 2022. "A New Bootstrapped Hybrid Artificial Neural Network Approach for Time Series Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 59(4), pages 1355-1383, April.
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    134. Lanh Tran, 2017. "How Wave - Wavelet Trading Wins and "Beats" the Market," Papers 1704.00383, arXiv.org.

  36. Paye, Bradley S. & Timmermann, Allan, 2002. "How Stable are Financial Prediction Models? Evidence from US and International Stock Market Data," University of California at San Diego, Economics Working Paper Series qt74v515fr, Department of Economics, UC San Diego.

    Cited by:

    1. Marco Aiolfi & Carlo Ambrogio Favero, "undated". "Model Uncertainty, Thick Modelling and the predictability of Stock Returns," Working Papers 221, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    2. Todd E. Clark & Michael W. McCracken, 2002. "Forecast-based model selection in the presence of structural breaks," Research Working Paper RWP 02-05, Federal Reserve Bank of Kansas City.
    3. Todd E. Clark & Michael W. McCracken, 2008. "Improving forecast accuracy by combining recursive and rolling forecasts," Working Papers 2008-028, Federal Reserve Bank of St. Louis.
    4. Clark, Todd E. & McCracken, Michael W., 2005. "The power of tests of predictive ability in the presence of structural breaks," Journal of Econometrics, Elsevier, vol. 124(1), pages 1-31, January.
    5. Jan R. Magnus & Dmitry Danilov, 2004. "Forecast accuracy after pretesting with an application to the stock market," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(4), pages 251-274.

  37. Blake, David & Timmermann, Allan, 2002. "International Asset Allocation with Time-Varying Investment Opportunities," CEPR Discussion Papers 3464, C.E.P.R. Discussion Papers.

    Cited by:

    1. Schneider, Martin & Albuquerque, Rui & ,, 2006. "Global Private Information in International Equity Markets," CEPR Discussion Papers 5819, C.E.P.R. Discussion Papers.
    2. Nadima El-Hassan & Paul Kofman, 2003. "Tracking Error and Active Portfolio Management," Australian Journal of Management, Australian School of Business, vol. 28(2), pages 183-207, September.
    3. Rossi, Alberto G. & Blake, David & Timmermann, Allan & Tonks, Ian & Wermers, Russ, 2015. "Network centrality and pension fund performance," CFR Working Papers 15-16, University of Cologne, Centre for Financial Research (CFR).
    4. Blake, David & Timmermann, Allan & Tonks, Ian & Wermers, Russ, 2010. "Decentralized investment management: evidence from the pension fund industry," MPRA Paper 35767, University Library of Munich, Germany.
    5. Korteweg, Arthur & Sorensen, Morten, 2017. "Skill and luck in private equity performance," Journal of Financial Economics, Elsevier, vol. 124(3), pages 535-562.
    6. Fernández, Pablo & Aguirreamalloa, Javier & Corres, Luis, 2013. "Rentabilidad de los fondos de pensiones en España. 2001-2011," IESE Research Papers D/1060, IESE Business School.
    7. Kamel Laaradh, 2007. "« Investir Sur Le Marche Inernational Des Actions A-T-Il Plus D'Effet Sur La Persistance De La Performance Des Fonds ? Illustration Britannique »," Post-Print halshs-00544930, HAL.
    8. Dreassi, Alberto & Miani, Stefano & Paltrinieri, Andrea, 2017. "Sovereign pension and social security reserve funds: A portfolio analysis," Global Finance Journal, Elsevier, vol. 34(C), pages 43-53.
    9. Ion Lapteacru, 2019. "Do bank activities and funding strategies of foreign and state‐owned banks have a differential effect on risk‐taking in Central and Eastern Europe?," Economics of Transition and Institutional Change, John Wiley & Sons, vol. 27(2), pages 541-576, February.
    10. Manuel Ammann & Andreas Zingg, 2008. "Investment Performance of Swiss Pension Funds and Investment Foundations," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 144(II), pages 153-195, June.
    11. Rui Albuquerque & Gregory Bauer & Martin Schneider, 2004. "Characterizing Asymmetric Information in International Equity Markets," International Finance 0405005, University Library of Munich, Germany.
    12. Blake, David & Cairns, Andrew & Dowd, Kevin, 2008. "Turning pension plans into pension planes: What investment strategy designers of defined contribution pension plans can learn from commercial aircraft designers," MPRA Paper 33749, University Library of Munich, Germany.
    13. Rossi, Alberto G. & Blake, David & Timmermann, Allan & Tonks, Ian & Wermers, Russ, 2018. "Network centrality and delegated investment performance," Journal of Financial Economics, Elsevier, vol. 128(1), pages 183-206.
    14. Iwatsubo, Kentaro & Watkins, Clinton, 2021. "The changing role of foreign investors in Tokyo stock price formation," Pacific-Basin Finance Journal, Elsevier, vol. 67(C).
    15. Blake, David & Sarno, Lucio & Zinna, Gabriele, 2017. "The market for lemmings: The herding behavior of pension funds," Journal of Financial Markets, Elsevier, vol. 36(C), pages 17-39.
    16. Moosa, Imad A. & Al-Deehani, Talla M., 2009. "The Myth of International Diversification," Economia Internazionale / International Economics, Camera di Commercio Industria Artigianato Agricoltura di Genova, vol. 62(3), pages 383-406.
    17. Gabriele Zinna, 2014. "Price pressures in the UK index-linked market: an empirical investigation," Temi di discussione (Economic working papers) 968, Bank of Italy, Economic Research and International Relations Area.

  38. Allan Timmermann & M. Hashem Pesaran, 2002. "Market Timing and Return Prediction under Model Instability," FMG Discussion Papers dp412, Financial Markets Group.

    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. Pesaran, M.H. & Pettenuzzo, D. & Timmermann, A., 2006. "Learning, Structural Instability and Present Value Calculations," Cambridge Working Papers in Economics 0602, Faculty of Economics, University of Cambridge.
    3. Tae-Hwy Lee & Shahnaz Parsaeian & Aman Ullah, 2022. "Forecasting under Structural Breaks Using Improved Weighted Estimation," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202212, University of Kansas, Department of Economics.
    4. Geweke, John & Jiang, Yu, 2011. "Inference and prediction in a multiple-structural-break model," Journal of Econometrics, Elsevier, vol. 163(2), pages 172-185, August.
    5. Andrew Ang & Allan Timmermann, 2011. "Regime Changes and Financial Markets," NBER Working Papers 17182, National Bureau of Economic Research, Inc.
    6. Gloria Gonzalez-Rivera & Yingying Sun, 2016. "Density Forecast Evaluation in Unstable Environments," Working Papers 201606, University of California at Riverside, Department of Economics.
    7. Yao, Juan & Gao, Jiti & Alles, Lakshman, 2005. "Dynamic investigation into the predictability of Australian industrial stock returns: Using financial and economic information," Pacific-Basin Finance Journal, Elsevier, vol. 13(2), pages 225-245, March.
    8. Jing Tian & Heather M. Anderson, 2011. "Forecasting Under Strucural Break Uncertainty," Monash Econometrics and Business Statistics Working Papers 8/11, Monash University, Department of Econometrics and Business Statistics.
    9. 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.
    10. Pesaran, M. Hashem & Timmermann, Allan, 2004. "How costly is it to ignore breaks when forecasting the direction of a time series?," International Journal of Forecasting, Elsevier, vol. 20(3), pages 411-425.
    11. Kumar, Nikeel Nishkar & Patel, Arvind, 2023. "Nonlinear effect of air travel tourism demand on economic growth in Fiji," Journal of Air Transport Management, Elsevier, vol. 109(C).
    12. John M. Maheu & Stephen Gordon, 2004. "Learning, Forecasting and Structural Breaks," Cahiers de recherche 0422, CIRPEE.
    13. Caterina Forti Grazzini & Massimo Guidolin, 2013. "Forecasting yield spreads under crisis-induced multiple breakpoints," Applied Economics Letters, Taylor & Francis Journals, vol. 20(18), pages 1656-1664, December.
    14. Sun, Yuying & Hong, Yongmiao & Wang, Shouyang & Zhang, Xinyu, 2023. "Penalized time-varying model averaging," Journal of Econometrics, Elsevier, vol. 235(2), pages 1355-1377.
    15. Hui Hong & Fergal O'Brien & James Ryan, 2014. "Inflation And The Subsequent Timing Of The Chinese Stock Market," Asian Academy of Management Journal of Accounting and Finance (AAMJAF), Penerbit Universiti Sains Malaysia, vol. 10(2), pages 13-35.
    16. Nyberg, Henri & Pönkä, Harri, 2016. "International sign predictability of stock returns: The role of the United States," Economic Modelling, Elsevier, vol. 58(C), pages 323-338.
    17. Lennart Hoogerheide & Richard Kleijn & Francesco Ravazzolo & Herman K. Van Dijk & Marno Verbeek, 2010. "Forecast accuracy and economic gains from Bayesian model averaging using time-varying weights," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 251-269.
    18. Alptekin, Aynur & Broadstock, David C. & Chen, Xiaoqi & Wang, Dong, 2019. "Time-varying parameter energy demand functions: Benchmarking state-space methods against rolling-regressions," Energy Economics, Elsevier, vol. 82(C), pages 26-41.
    19. Wang, Yudong & Hao, Xianfeng, 2022. "Forecasting the real prices of crude oil: A robust weighted least squares approach," Energy Economics, Elsevier, vol. 116(C).
    20. Chatzitzisi, Evanthia & Fountas, Stilianos & Panagiotidis, Theodore, 2021. "Another look at calendar anomalies," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 823-840.
    21. Michael W. McCracken & Todd E. Clark, 2003. "The Predictive Content of the Output Gap for Inflation: Resolving In-Sample and Out-of-Sample Evidence," Computing in Economics and Finance 2003 183, Society for Computational Economics.
    22. Massimo Guidolin & Alexei Orlov, 2018. "Can Investors Benefit from Hedge Fund Strategies? Utility-Based, Out-of-Sample Evidence," BAFFI CAREFIN Working Papers 1890, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    23. Dellas, Harris & Gibson, Heather D. & Hall, Stephen G. & Tavlas, George S., 2018. "The macroeconomic and fiscal implications of inflation forecast errors," Journal of Economic Dynamics and Control, Elsevier, vol. 93(C), pages 203-217.
    24. Russell Davidson & Niels S. Grønborg, 2018. "Time-varying parameters: New test tailored to applications in finance and macroeconomics," CREATES Research Papers 2018-22, Department of Economics and Business Economics, Aarhus University.
    25. Davide De Gaetano, 2016. "Forecast Combinations For Realized Volatility In Presence Of Structural Breaks," Departmental Working Papers of Economics - University 'Roma Tre' 0208, Department of Economics - University Roma Tre.
    26. Boonsoo Koo & Myung Hwan Seo, 2013. "Structural-break models under mis-specification: implications for forecasting," Monash Econometrics and Business Statistics Working Papers 11/13, Monash University, Department of Econometrics and Business Statistics.
    27. Marco Aiolfi & Carlo Ambrogio Favero, "undated". "Model Uncertainty, Thick Modelling and the predictability of Stock Returns," Working Papers 221, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    28. Todd E. Clark & Michael W. McCracken, 2009. "Combining Forecasts from Nested Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(3), pages 303-329, June.
    29. Raffaella Giacomini & Barbara Rossi, 2013. "Forecasting in macroeconomics," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 17, pages 381-408, Edward Elgar Publishing.
    30. Colino, Evelyn V. & Irwin, Scott H. & Garcia, Philip, 2008. "How Much Can Outlook Forecasts be Improved? An Application to the U.S. Hog Market," 2008 Conference, April 21-22, 2008, St. Louis, Missouri 37620, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    31. Henkel, Sam James & Martin, J. Spencer & Nardari, Federico, 2011. "Time-varying short-horizon predictability," Journal of Financial Economics, Elsevier, vol. 99(3), pages 560-580, March.
    32. Davide De Gaetano, 2018. "Forecast Combinations in the Presence of Structural Breaks: Evidence from U.S. Equity Markets," Mathematics, MDPI, vol. 6(3), pages 1-19, March.
    33. Erik Hillebrand & Tae-Hwy Lee & Marcelo Cunha Medeiros, 2012. "Let´s do it again: bagging equity premium predictors," Textos para discussão 604, Department of Economics PUC-Rio (Brazil).
    34. Pesaran, M. Hashem & Pick, Andreas & Pranovich, Mikhail, 2013. "Optimal forecasts in the presence of structural breaks," Journal of Econometrics, Elsevier, vol. 177(2), pages 134-152.
    35. Todd E. Clark & Michael W. McCracken, 2002. "Forecast-based model selection in the presence of structural breaks," Research Working Paper RWP 02-05, Federal Reserve Bank of Kansas City.
    36. McKenzie, Michael & Satchell, Stephen & Wongwachara, Warapong, 2012. "Nonlinearity and smoothing in venture capital performance data," Journal of Empirical Finance, Elsevier, vol. 19(5), pages 782-795.
    37. Sander, Magnus, 2018. "Market timing over the business cycle," Journal of Empirical Finance, Elsevier, vol. 46(C), pages 130-145.
    38. Cederburg, Scott & O’Doherty, Michael S. & Wang, Feifei & Yan, Xuemin (Sterling), 2020. "On the performance of volatility-managed portfolios," Journal of Financial Economics, Elsevier, vol. 138(1), pages 95-117.
    39. Pesaran, M.H. & Timmermann, A., 2004. "‘Real Time Econometrics’," Cambridge Working Papers in Economics 0432, Faculty of Economics, University of Cambridge.
    40. Evzen Kocenda, 2001. "Detecting Structural Breaks: Exchange Rates in Transition Economies," Development and Comp Systems 0012009, University Library of Munich, Germany.
    41. Timmermann, Allan, 2008. "Elusive return predictability," International Journal of Forecasting, Elsevier, vol. 24(1), pages 1-18.
    42. Yang Yang & Tae-Hwy Lee, 2004. "Bagging Binary Predictors for Time Series," Econometric Society 2004 Far Eastern Meetings 512, Econometric Society.
    43. Patrick McGlenchy & Paul Kofman, 2004. "Structurally Sound Dynamic Index Futures Hedging," Econometric Society 2004 Australasian Meetings 80, Econometric Society.
    44. Daniele Bianchi & Kenichiro McAlinn, 2018. "Large-Scale Dynamic Predictive Regressions," Papers 1803.06738, arXiv.org.
    45. Sjoerd van den Hauwe & Richard Paap & Dick J.C. van Dijk, 2011. "An Alternative Bayesian Approach to Structural Breaks in Time Series Models," Tinbergen Institute Discussion Papers 11-023/4, Tinbergen Institute.
    46. Roch, Oriol, 2013. "Histogram-based prediction of directional price relatives," Finance Research Letters, Elsevier, vol. 10(3), pages 110-115.
    47. Pesaran, M.H. & Timmermann, A., 2003. "Small Sample Properties of Forecasts from Autoregressive Models under Structural Breaks," Cambridge Working Papers in Economics 0331, Faculty of Economics, University of Cambridge.
    48. Çakmaklı, Cem & van Dijk, Dick, 2016. "Getting the most out of macroeconomic information for predicting excess stock returns," International Journal of Forecasting, Elsevier, vol. 32(3), pages 650-668.
    49. Smith, Simon C. & Timmermann, Allan & Zhu, Yinchu, 2019. "Variable selection in panel models with breaks," Journal of Econometrics, Elsevier, vol. 212(1), pages 323-344.
    50. Tae-Hwy Lee & Shahnaz Parsaeian & Aman Ullah, 2022. "Optimal Forecast under Structural Breaks," Working Papers 202208, University of California at Riverside, Department of Economics.
    51. Demetrescu, Matei & Rodrigues, Paulo M.M., 2022. "Residual-augmented IVX predictive regression," Journal of Econometrics, Elsevier, vol. 227(2), pages 429-460.
    52. Adam Canopius, 2006. "Practitioners' Corner," Journal of Financial Econometrics, Oxford University Press, vol. 4(2), pages 346-351.
    53. Elliott, Graham & Muller, Ulrich K., 2004. "Confidence Sets for the Date of a Single Break in Linear Time Series Regressions," University of California at San Diego, Economics Working Paper Series qt9hf4j4c2, Department of Economics, UC San Diego.
    54. Pönkä, Harri, 2015. "Real oil prices and the international sign predictability of stock returns," MPRA Paper 68330, University Library of Munich, Germany.
    55. Todd E. Clark & Michael W. McCracken, 2008. "Improving forecast accuracy by combining recursive and rolling forecasts," Working Papers 2008-028, Federal Reserve Bank of St. Louis.
    56. Clark, Todd E. & McCracken, Michael W., 2005. "The power of tests of predictive ability in the presence of structural breaks," Journal of Econometrics, Elsevier, vol. 124(1), pages 1-31, January.
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    87. Emanuela Ciapanna & Marco Taboga, 2019. "Bayesian Analysis of Coefficient Instability in Dynamic Regressions," Econometrics, MDPI, vol. 7(3), pages 1-32, June.
    88. Xiaojie Xu, 2017. "Short-run price forecast performance of individual and composite models for 496 corn cash markets," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(14), pages 2593-2620, October.
    89. Tian, Jing & Anderson, Heather M., 2014. "Forecast combinations under structural break uncertainty," International Journal of Forecasting, Elsevier, vol. 30(1), pages 161-175.
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    91. Pierdzioch, Christian & Risse, Marian & Rohloff, Sebastian, 2014. "The international business cycle and gold-price fluctuations," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(2), pages 292-305.
    92. Paulo M.M. Rodrigues & Matei Demetrescu, 2019. "Testing for Episodic Predictability in Stock Returns," Working Papers w201906, Banco de Portugal, Economics and Research Department.
    93. Hanxiong Zhang & Robert Hudson & Hugh Metcalf & Viktor Manahov, 2017. "Investigation of institutional changes in the UK housing market using structural break tests and time-varying parameter models," Empirical Economics, Springer, vol. 53(2), pages 617-640, September.
    94. Kuang-Liang Chang, 2012. "Stock return predictability and stationarity of dividend yield," Economics Bulletin, AccessEcon, vol. 32(1), pages 715-729.
    95. 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.
    96. Feiyu Jiang & Zifeng Zhao & Xiaofeng Shao, 2022. "Modelling the COVID‐19 infection trajectory: A piecewise linear quantile trend model," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(5), pages 1589-1607, November.
    97. Cem Cakmakli & Dick van Dijk, 2010. "Getting the Most out of Macroeconomic Information for Predicting Stock Returns and Volatility," Tinbergen Institute Discussion Papers 10-115/4, Tinbergen Institute.
    98. Tae-Hwy Lee & Eric Hillebrand & Marcelo Medeiros, 2014. "Bagging Constrained Equity Premium Predictors," Working Papers 201421, University of California at Riverside, Department of Economics, revised Feb 2013.
    99. Donadelli, Michael & Persha, Lauren, 2014. "Understanding emerging market equity risk premia: Industries, governance and macroeconomic policy uncertainty," Research in International Business and Finance, Elsevier, vol. 30(C), pages 284-309.
    100. Mark E. Wohar & David E. Rapach, 2007. "Forecasting the recent behavior of US business fixed investment spending: an analysis of competing models This is a significantly revised version of our previous paper, 'Forecasting US Business Fixed ," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(1), pages 33-51.
    101. Lozinskaia, Agata & Saltykova, Anastasiia, 2019. "Fundamental Factors Affecting the MOEX Russia Index: Retrospective Analysis," MPRA Paper 97308, University Library of Munich, Germany, revised 23 Sep 2019.
    102. Barnhart, Scott W. & Giannetti, Antoine, 2009. "Negative earnings, positive earnings and stock return predictability: An empirical examination of market timing," Journal of Empirical Finance, Elsevier, vol. 16(1), pages 70-86, January.
    103. Gradojevic, Nikola & Gençay, Ramazan, 2013. "Fuzzy logic, trading uncertainty and technical trading," Journal of Banking & Finance, Elsevier, vol. 37(2), pages 578-586.
    104. Ryan Compton & Syeed Khan, 2010. "An examination of the stability of short-run Canadian stock predictability," Economics Bulletin, AccessEcon, vol. 30(2), pages 1293-1306.
    105. Agata Lozinskaia & Anastasiia Saltykova, 2019. "Fundamental Factors Affecting The Moex Russia Index: Structural Break Detection In A Long-Term Time Series," HSE Working papers WP BRP 77/FE/2019, National Research University Higher School of Economics.
    106. Muhammad Owais Qarni & Saqib Gulzar, 2020. "Intra-EMU and non-EMU, EU stock markets’ return spillover: evidence from ESDC," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 47(3), pages 543-577, August.
    107. Fan, Jianqing & Gong, Wenyan & Zhu, Ziwei, 2019. "Generalized high-dimensional trace regression via nuclear norm regularization," Journal of Econometrics, Elsevier, vol. 212(1), pages 177-202.
    108. Roy P. P. M. Hoevenaars & Roderick D. J. Molenaar & Peter C. Schotman & Tom B. M. Steenkamp, 2014. "Strategic Asset Allocation For Long‐Term Investors: Parameter Uncertainty And Prior Information," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(3), pages 353-376, April.
    109. Naser, Hanan & Alaali, Fatema, 2015. "Can Oil Prices Help Predict US Stock Market Returns: An Evidence Using a DMA Approach," MPRA Paper 65295, University Library of Munich, Germany, revised 25 Jun 2015.
    110. Jiawen Xu & Pierre Perron, 2017. "Forecasting in the presence of in and out of sample breaks," Boston University - Department of Economics - Working Papers Series WP2018-014, Boston University - Department of Economics, revised Nov 2018.
    111. Hanan Naser & Fatema Alaali, 2018. "Can oil prices help predict US stock market returns? Evidence using a dynamic model averaging (DMA) approach," Empirical Economics, Springer, vol. 55(4), pages 1757-1777, December.
    112. Mai Dao & Davide Furceri & Prakash Loungani, 2017. "Regional Labor Market Adjustment in the United States: Trend and Cycle," The Review of Economics and Statistics, MIT Press, vol. 99(2), pages 243-257, May.
    113. Zhao, Albert Bo & Cheng, Tingting, 2022. "Stock return prediction: Stacking a variety of models," Journal of Empirical Finance, Elsevier, vol. 67(C), pages 288-317.
    114. Wang, Yudong & Hao, Xianfeng & Wu, Chongfeng, 2021. "Forecasting stock returns: A time-dependent weighted least squares approach," Journal of Financial Markets, Elsevier, vol. 53(C).
    115. Pedro N. Rodríguez, & Simón Sosvilla-Rivero, 2006. "Forecasting Stock Price Changes: Is it Possible?," Working Papers 2006-22, FEDEA.
    116. Jiang, Feiyu & Zhao, Zifeng & Shao, Xiaofeng, 2023. "Time series analysis of COVID-19 infection curve: A change-point perspective," Journal of Econometrics, Elsevier, vol. 232(1), pages 1-17.
    117. Ioannis Kyriakou & Parastoo Mousavi & Jens Perch Nielsen & Michael Scholz, 2020. "Longer-Term Forecasting of Excess Stock Returns—The Five-Year Case," Mathematics, MDPI, vol. 8(6), pages 1-20, June.
    118. Sharma, Susan Sunila & Narayan, Paresh Kumar, 2022. "Technology shocks and stock returns: A long-term perspective," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 67-83.
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    121. 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.
    122. Johnson, Lorne D. & Sakoulis, Georgios, 2008. "Maximizing equity market sector predictability in a Bayesian time-varying parameter model," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 3083-3106, February.
    123. Ravazzolo, F. & van Dijk, D.J.C. & Paap, R. & Franses, Ph.H.B.F., 2006. "Bayesian Model Averaging in the Presence of Structural Breaks," Econometric Institute Research Papers EI 2006-33, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    124. Xiaojie Xu, 2020. "Corn Cash Price Forecasting," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(4), pages 1297-1320, August.
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  39. Bruce N. Lehmann & Allan Timmermann, 2002. "(UBS Pensions Series 3) Performance Clustering and Incentives in the UK Pension Fund Industry," FMG Discussion Papers dp425, Financial Markets Group.

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    1. Bijapur, Mohan & Croci, Manuela & Zaidi, Rida, 2012. "Do asset regulations impede portfolio diversification? evidence from European life insurance funds," LSE Research Online Documents on Economics 56618, London School of Economics and Political Science, LSE Library.
    2. Lawrence Kryzanowski & Abdul Rahman, 2008. "Portfolio performance ambiguity and benchmark inefficiency revisited," Journal of Asset Management, Palgrave Macmillan, vol. 9(5), pages 321-332, December.
    3. Agarwal, Vikas & Gómez, Juan-Pedro & Priestley, Richard, 2012. "Management compensation and market timing under portfolio constraints," Journal of Economic Dynamics and Control, Elsevier, vol. 36(10), pages 1600-1625.
    4. Christoph Gort & Mei Wang, 2010. "Overconfidence and Active Management," Chapters, in: Brian Bruce (ed.), Handbook of Behavioral Finance, chapter 12, Edward Elgar Publishing.
    5. Claudio Raddatz & Sergio Schmukler, 2013. "Deconstructing Herding: Evidence from Pension Fund Investment Behavior," Journal of Financial Services Research, Springer;Western Finance Association, vol. 43(1), pages 99-126, February.
    6. Jem Tugwell, 2011. "Skill or luck? The role of strategies and scenario analysis as a competitive differentiator for fund management firms," Journal of Asset Management, Palgrave Macmillan, vol. 12(4), pages 281-291, September.
    7. Blake, David & Cairns, Andrew & Dowd, Kevin, 2008. "Turning pension plans into pension planes: What investment strategy designers of defined contribution pension plans can learn from commercial aircraft designers," MPRA Paper 33749, University Library of Munich, Germany.
    8. Martin Gold, 2010. "Fiduciary Finance," Books, Edward Elgar Publishing, number 13813.
    9. Svitlana Voronkova & Martin T. Bohl, 2005. "Institutional Traders’ Behavior in an Emerging Stock Market: Empirical Evidence on Polish Pension Fund Investors," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 32(7‐8), pages 1537-1560, September.
    10. Paul Cox & Stephen Brammer & Andrew Millington, 2007. "Pension Fund Manager Tournaments and Attitudes Towards Corporate Characteristics," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 34(7‐8), pages 1307-1326, September.
    11. John Watson & James Delaney & Michael Dempsey & J. Wickramanayake, 2016. "Australian superannuation (pension) fund product ratings and performance: A guide for fund managers," Australian Journal of Management, Australian School of Business, vol. 41(2), pages 189-211, May.

  40. Elliott, Graham & Timmermann, Allan, 2002. "Optimal Forecast Combination Under General Loss Functions and Forecast Error Distributions," University of California at San Diego, Economics Working Paper Series qt15r9t2q2, Department of Economics, UC San Diego.

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    1. 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.
    2. Aretz, Kevin & Bartram, Söhnke M. & Pope, Peter F., 2011. "Asymmetric Loss Functions and the Rationality of Expected Stock Returns," MPRA Paper 47343, University Library of Munich, Germany.
    3. Jiang Wu & Jianzhong Zhou & Lu Chen & Lei Ye, 2015. "Coupling Forecast Methods of Multiple Rainfall–Runoff Models for Improving the Precision of Hydrological Forecasting," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(14), pages 5091-5108, November.
    4. Cecilia Frale & Libero Monteforte, "undated". "FaMIDAS: A Mixed Frequency Factor Model with MIDAS structure," Working Papers 3, Department of the Treasury, Ministry of the Economy and of Finance.
    5. Giacomini, Raffaella & Komunjer, Ivana, 2002. "Evaluation and Combination of Conditional Quantile Forecasts," University of California at San Diego, Economics Working Paper Series qt4n99t4wz, Department of Economics, UC San Diego.
    6. Jan R. Magnus & Wendun Wang & Xinyu Zhang, 2016. "Weighted-Average Least Squares Prediction," Econometric Reviews, Taylor & Francis Journals, vol. 35(6), pages 1040-1074, June.
    7. Matteo Iacopini & Francesco Ravazzolo & Luca Rossini, 2020. "Proper scoring rules for evaluating asymmetry in density forecasting," Working Papers No 06/2020, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    8. Heather M. Anderson & Farshid Vahid, 2005. "Nonlinear Correlograms and Partial Autocorrelograms," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(s1), pages 957-982, December.
    9. Valentina Corradi & Norman Swanson, 2013. "A Survey of Recent Advances in Forecast Accuracy Comparison Testing, with an Extension to Stochastic Dominance," Departmental Working Papers 201309, Rutgers University, Department of Economics.
    10. Jakub Nowotarski, 2013. "Short-term forecasting of electricity spot prices using model averaging (Krótkoterminowe prognozowanie spotowych cen energii elektrycznej z wykorzystaniem uśredniania modeli)," HSC Research Reports HSC/13/17, Hugo Steinhaus Center, Wroclaw University of Technology.
    11. Xing, Li-Min & Zhang, Yue-Jun, 2022. "Forecasting crude oil prices with shrinkage methods: Can nonconvex penalty and Huber loss help?," Energy Economics, Elsevier, vol. 110(C).
    12. Jana Eklund & Sune Karlsson, 2007. "Forecast Combination and Model Averaging Using Predictive Measures," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 329-363.
    13. Luiz Renato Regis de Oliveira Lima & Wagner Piazza Gaglianone, 2012. "Constructing Optimal Density Forecasts from Point Forecast Combinations," Série Textos para Discussão (Working Papers) 5, Programa de Pós-Graduação em Economia - PPGE, Universidade Federal da Paraíba.
    14. Coroneo, Laura & Iacone, Fabrizio & Paccagnini, Alessia & Santos Monteiro, Paulo, 2023. "Testing the predictive accuracy of COVID-19 forecasts," International Journal of Forecasting, Elsevier, vol. 39(2), pages 606-622.
    15. Barbara Będowska-Sójka, 2018. "Is intraday data useful for forecasting VaR? The evidence from EUR/PLN exchange rate," Risk Management, Palgrave Macmillan, vol. 20(4), pages 326-346, November.
    16. Timmermann, Allan & Elliott, Graham, 2007. "Economic Forecasting," CEPR Discussion Papers 6158, C.E.P.R. Discussion Papers.
    17. 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.
    18. Wei, Xiaoqiao & Yang, Yuhong, 2012. "Robust forecast combinations," Journal of Econometrics, Elsevier, vol. 166(2), pages 224-236.
    19. 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.
    20. Xu, Yexiao, 2004. "Small levels of predictability and large economic gains," Journal of Empirical Finance, Elsevier, vol. 11(2), pages 247-275, March.
    21. Massimo Guidolin, 2011. "Markov Switching Models in Empirical Finance," Working Papers 415, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    22. Marco Aiolfi & Carlo Ambrogio Favero, "undated". "Model Uncertainty, Thick Modelling and the predictability of Stock Returns," Working Papers 221, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    23. Todd E. Clark & Michael W. McCracken, 2009. "Combining Forecasts from Nested Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(3), pages 303-329, June.
    24. Cheng, Gang & Yang, Yuhong, 2015. "Forecast combination with outlier protection," International Journal of Forecasting, Elsevier, vol. 31(2), pages 223-237.
    25. George Athanasopoulos & Rob J Hyndman & Nikolaos Kourentzes & Fotios Petropoulos, 2015. "Forecasting with Temporal Hierarchies," Monash Econometrics and Business Statistics Working Papers 16/15, Monash University, Department of Econometrics and Business Statistics.
    26. Norman Swanson & Valentina Corradi, 2006. "Nonparametric Bootstrap Procedures for Predictive Inference Based on Recursive Estimation Schemes," Departmental Working Papers 200618, Rutgers University, Department of Economics.
    27. Martin Baumgärtner & Jens Klose, 2019. "Forecasting exchange rates with commodity prices—a global country analysis," The World Economy, Wiley Blackwell, vol. 42(9), pages 2546-2565, September.
    28. Demetrescu, Matei & Hacıoğlu Hoke, Sinem, 2019. "Predictive regressions under asymmetric loss: Factor augmentation and model selection," International Journal of Forecasting, Elsevier, vol. 35(1), pages 80-99.
    29. Alessandro Riboni & Francisco Ruge-Murcia, 2020. "The Power of the Federal Reserve Chair," Cahiers de recherche 20-2020, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    30. Lima, Luiz Renato Regis de Oliveira & Issler, João Victor, 2007. "A panel data approach to economic forecasting: the bias-corrected average forecast," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 650, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    31. Jan J.J. Groen & George Kapetanios, 2008. "Revisiting Useful Approaches to Data-Rich Macroeconomic Forecasting," Working Papers 624, Queen Mary University of London, School of Economics and Finance.
    32. Heijmans, Roweno J.R.K. & Gerlagh, Reyer, 2019. "Regulating Global Externalities," Discussion Paper 2019-001, Tilburg University, Center for Economic Research.
    33. Wagner Piazza Gaglianone & João Victor Issler & Silvia Maria Matos, 2017. "Applying a microfounded-forecasting approach to predict Brazilian inflation," Empirical Economics, Springer, vol. 53(1), pages 137-163, August.
    34. Wagner Piazza Gaglianone & João Victor Issler, 2014. "Microfounded Forecasting," Working Papers Series 372, Central Bank of Brazil, Research Department.
    35. Valentina Corradi & Norman Swanson, 2004. "Bootstrap Procedures for Recursive Estimation Schemes With Applications to Forecast Model Selection," Departmental Working Papers 200418, Rutgers University, Department of Economics.
    36. Todd E. Clark & Michael W. McCracken, 2008. "Improving forecast accuracy by combining recursive and rolling forecasts," Working Papers 2008-028, Federal Reserve Bank of St. Louis.
    37. Carmona, Carlos Capistran, 2005. "Bias in Federal Reserve Inflation Forecasts: Is the Federal Reserve Irrational or Just Cautious?," University of California at San Diego, Economics Working Paper Series qt6v28v0b6, Department of Economics, UC San Diego.
    38. Xinyu Zhang & Alan T. K. Wan & Sherry Z. Zhou, 2011. "Focused Information Criteria, Model Selection, and Model Averaging in a Tobit Model With a Nonzero Threshold," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 132-142, June.
    39. Jin, Sainan & Corradi, Valentina & Swanson, Norman R., 2017. "Robust Forecast Comparison," Econometric Theory, Cambridge University Press, vol. 33(6), pages 1306-1351, December.
    40. Chotikapanich, D. & Griffiths, W.E. & Rao, D.S.P., 2001. "Averaging Income Distributions," Department of Economics - Working Papers Series 798, The University of Melbourne.
    41. 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.
    42. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1203-1324, Elsevier.
    43. Gary Cornwall & Jeff Chen & Beau Sauley, 2021. "Standing on the Shoulders of Machine Learning: Can We Improve Hypothesis Testing?," Papers 2103.01368, arXiv.org.
    44. Matei Demetrescu, 2007. "Optimal forecast intervals under asymmetric loss," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(4), pages 227-238.
    45. Clements, Michael P. & Harvey, David I., 2011. "Combining probability forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 208-223.
    46. John Galbraith & Greg Tkacz, 2007. "How Far Can Forecasting Models Forecast? Forecast Content Horizons for Some Important Macroeconomic Variables," Staff Working Papers 07-1, Bank of Canada.
    47. Zongwu Cai & Chaoqun Ma & Xianhua Mi, 2020. "Realized Volatility Forecasting Based on Dynamic Quantile Model Averaging," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202016, University of Kansas, Department of Economics, revised Sep 2020.
    48. Chen, Xiaohong & Fan, Yanqin, 2006. "Estimation and model selection of semiparametric copula-based multivariate dynamic models under copula misspecification," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 125-154.
    49. Capistrán Carlos, 2007. "Optimality Tests for Multi-Horizon Forecasts," Working Papers 2007-14, Banco de México.
    50. Sancetta, Alessio, 2007. "Online forecast combinations of distributions: Worst case bounds," Journal of Econometrics, Elsevier, vol. 141(2), pages 621-651, December.
    51. Carriero, Andrea & Giacomini, Raffaella, 2011. "How useful are no-arbitrage restrictions for forecasting the term structure of interest rates?," Journal of Econometrics, Elsevier, vol. 164(1), pages 21-34, September.
    52. Mehmet Pinar & Thanasis Stengos & M. Ege Yazgan, 2018. "Quantile forecast combination using stochastic dominance," Empirical Economics, Springer, vol. 55(4), pages 1717-1755, December.
    53. Golosnoy, Vasyl & Hamid, Alain & Okhrin, Yarema, 2014. "The empirical similarity approach for volatility prediction," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 321-329.
    54. Barrow, Devon K. & Kourentzes, Nikolaos, 2016. "Distributions of forecasting errors of forecast combinations: Implications for inventory management," International Journal of Production Economics, Elsevier, vol. 177(C), pages 24-33.
    55. 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.
    56. Coshall, John T. & Charlesworth, Richard, 2011. "A management orientated approach to combination forecasting of tourism demand," Tourism Management, Elsevier, vol. 32(4), pages 759-769.
    57. Aiolfi, Marco & Timmermann, Allan, 2006. "Persistence in forecasting performance and conditional combination strategies," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 31-53.
    58. Viviano, Davide & Bradic, Jelena, 2023. "Synthetic Learner: Model-free inference on treatments over time," Journal of Econometrics, Elsevier, vol. 234(2), pages 691-713.
    59. Heijmans, Roweno J.R.K. & Gerlagh, Reyer, 2019. "Regulating Global Externalities," Other publications TiSEM 9a0a6f7a-f8d0-4495-8aed-4, Tilburg University, School of Economics and Management.
    60. Sancetta, A., 2007. "Online Forecast Combination for Dependent Heterogeneous Data," Cambridge Working Papers in Economics 0718, Faculty of Economics, University of Cambridge.
    61. Massimiliano Giacalone, 2022. "Optimal forecasting accuracy using Lp-norm combination," METRON, Springer;Sapienza Università di Roma, vol. 80(2), pages 187-230, August.
    62. Sancetta, A. & Satchell, S.E., 2004. "Cost of Capital and Regulator’s Preferences: Investigation into a new method of estimating regulatory bias," Cambridge Working Papers in Economics 0441, Faculty of Economics, University of Cambridge.
    63. 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.
    64. Gneiting, Tilmann, 2011. "Quantiles as optimal point forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 197-207, April.
    65. Chanont Banternghansa & Michael W. McCracken, 2010. "Real-time forecast averaging with ALFRED," Working Papers 2010-033, Federal Reserve Bank of St. Louis.
    66. Elena Andreou & Eric Ghysels & Constantinos Kourouyiannis, 2012. "Robust volatility forecasts in the presence of structural breaks," University of Cyprus Working Papers in Economics 08-2012, University of Cyprus Department of Economics.
    67. Magnus, J.R. & Wang, W. & Zhang, Xinyu, 2012. "WALS Prediction," Discussion Paper 2012-043, Tilburg University, Center for Economic Research.
    68. Qing Zhou & Robert Faff, 2017. "The complementary role of cross-sectional and time-series information in forecasting stock returns," Australian Journal of Management, Australian School of Business, vol. 42(1), pages 113-139, February.
    69. Taylor, James W., 2020. "Forecast combinations for value at risk and expected shortfall," International Journal of Forecasting, Elsevier, vol. 36(2), pages 428-441.
    70. Gomez, Miguel I. & Gonzalez, Eliana & Melo, Luis F. & Torres, Jose L., 2006. "Forecasting Food Price Inflation, Challenges for Central Banks in Developing Countries using an Inflation Targeting Framework: the Case of Colombia," 2006 Annual meeting, July 23-26, Long Beach, CA 21181, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    71. Laborda, Ricardo, 2018. "Optimal combination of currency strategies," The North American Journal of Economics and Finance, Elsevier, vol. 43(C), pages 129-140.
    72. Luke Hartigan, 2016. "Alternative HAC Covariance Matrix Estimators with Improved Finite Sample Properties," Discussion Papers 2016-06, School of Economics, The University of New South Wales.
    73. Elena Andreou & Constantinos Kourouyiannis & Andros Kourtellos, 2012. "Volatility Forecast Combinations using Asymmetric Loss Functions," University of Cyprus Working Papers in Economics 07-2012, University of Cyprus Department of Economics.
    74. Gneiting, Tilmann, 2011. "Quantiles as optimal point forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 197-207.
    75. Björn Fastrich & Peter Winker, 2014. "Combining Forecasts with Missing Data: Making Use of Portfolio Theory," Computational Economics, Springer;Society for Computational Economics, vol. 44(2), pages 127-152, August.
    76. Ulrich Gunter & Irem Önder & Egon Smeral, 2020. "Are Combined Tourism Forecasts Better at Minimizing Forecasting Errors?," Forecasting, MDPI, vol. 2(3), pages 1-19, June.
    77. 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.
    78. Kocięcki, Andrzej & Kolasa, Marcin & Rubaszek, Michał, 2012. "A Bayesian method of combining judgmental and model-based density forecasts," Economic Modelling, Elsevier, vol. 29(4), pages 1349-1355.
    79. Kevin Aretz & David Peel, 2007. "Some implications of a quartic loss function," Economics Bulletin, AccessEcon, vol. 7(13), pages 1-7.
    80. 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.
    81. Magnus, J.R. & Wang, W. & Zhang, Xinyu, 2012. "WALS Prediction," Other publications TiSEM 7715e942-b446-4985-8216-f, Tilburg University, School of Economics and Management.

  41. Timmermann, Allan & Guidolin, Massimo, 2001. "Option Prices under Bayesian Learning: Implied Volatility Dynamics and Predictive Densities," CEPR Discussion Papers 3005, C.E.P.R. Discussion Papers.

    Cited by:

    1. Fearghal Kearney & Han Lin Shang & Lisa Sheenan, 2019. "Implied volatility surface predictability: the case of commodity markets," Papers 1909.11009, arXiv.org.
    2. 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.
    3. Laurent E. Calvet & Adlai J. Fisher, 2005. "Multifrequency News and Stock Returns," NBER Working Papers 11441, National Bureau of Economic Research, Inc.
    4. Shang, Han Lin & Kearney, Fearghal, 2022. "Dynamic functional time-series forecasts of foreign exchange implied volatility surfaces," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1025-1049.
    5. Sílvia Gonçalves & Massimo Guidolin, 2006. "Predictable Dynamics in the S&P 500 Index Options Implied Volatility Surface," The Journal of Business, University of Chicago Press, vol. 79(3), pages 1591-1636, May.
    6. Massimo Guidolin, 2006. "High equity premia and crash fears - Rational foundations," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 28(3), pages 693-708, August.
    7. Nikolaus Hautsch & Dieter Hess & Christoph Müller, 2008. "Price Adjustment to News with Uncertain Precision," FRU Working Papers 2008/01, University of Copenhagen. Department of Economics. Finance Research Unit.
    8. Moritz Duembgen & L. C. G. Rogers, 2014. "Estimate nothing," Quantitative Finance, Taylor & Francis Journals, vol. 14(12), pages 2065-2072, December.
    9. Laurent-Emmanuel Calvet & Veronika Czellar, 2011. "State-Observation Sampling and the Econometrics of Learning Models," Working Papers hal-00625500, HAL.
    10. Carsten Krabbe Nielsen, 2004. "Rational overconfidence and excess volatility in General Equilibrium," Econometric Society 2004 Australasian Meetings 279, Econometric Society.
    11. Shu Ling Chiang & Ming Shann Tsai, 2019. "Valuation of an option using non-parametric methods," Review of Derivatives Research, Springer, vol. 22(3), pages 419-447, October.
    12. Bernales, Alejandro & Chen, Louisa & Valenzuela, Marcela, 2017. "Learning and forecasts about option returns through the volatility risk premium," Journal of Economic Dynamics and Control, Elsevier, vol. 82(C), pages 312-330.
    13. Guidolin, Massimo & Timmermann, Allan, 2007. "Properties of equilibrium asset prices under alternative learning schemes," Journal of Economic Dynamics and Control, Elsevier, vol. 31(1), pages 161-217, January.
    14. Sudarshan Kumar & Sobhesh Kumar Agarwalla & Jayanth R. Varma & Vineet Virmani, 2023. "Harvesting the volatility smile in a large emerging market: A Dynamic Nelson–Siegel approach," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(11), pages 1615-1644, November.
    15. Calvet, Laurent E. & Czellar, Veronika, 2015. "Through the looking glass: Indirect inference via simple equilibria," Journal of Econometrics, Elsevier, vol. 185(2), pages 343-358.
    16. Massimo Guidolin, 2005. "Pessimistic beliefs under rational learning: quantitative implications for the equity premium puzzle," Working Papers 2005-005, Federal Reserve Bank of St. Louis.
    17. Bernales, Alejandro & Guidolin, Massimo, 2014. "Can we forecast the implied volatility surface dynamics of equity options? Predictability and economic value tests," Journal of Banking & Finance, Elsevier, vol. 46(C), pages 326-342.
    18. Le, Van & Zurbruegg, Ralf, 2014. "Forecasting option smile dynamics," International Review of Financial Analysis, Elsevier, vol. 35(C), pages 32-45.
    19. Nikolaus Hautsch & Dieter Hess & David Veredas, 2010. "The impact of macroeconomic news on quote adjustments, noise and informational volatility," Working Papers ECARES 2010-004, ULB -- Universite Libre de Bruxelles.
    20. Sadayuki Ono, 2007. "Option Pricing under Stochastic Volatility and Trading Volume," Discussion Papers 07/05, Department of Economics, University of York.
    21. Chalamandaris, Georgios & Rompolis, Leonidas S., 2012. "Exploring the role of the realized return distribution in the formation of the implied volatility smile," Journal of Banking & Finance, Elsevier, vol. 36(4), pages 1028-1044.
    22. Lei Shi, 2010. "Portfolio Analysis and Equilibrium Asset Pricing with Heterogeneous Beliefs," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 2-2010.
    23. Rainer Baule & Bart Frijns & Milena E. Tieves, 2018. "Volatility discovery and volatility quoting on markets for options and warrants," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(7), pages 758-774, July.
    24. Shaliastovich, Ivan, 2015. "Learning, confidence, and option prices," Journal of Econometrics, Elsevier, vol. 187(1), pages 18-42.
    25. Guidolin, Massimo, 2003. "International asset prices and portfolio choices under Bayesian learning," Research in Economics, Elsevier, vol. 57(4), pages 383-437, December.
    26. Konstantinidi, Eirini & Skiadopoulos, George & Tzagkaraki, Emilia, 2008. "Can the evolution of implied volatility be forecasted? Evidence from European and US implied volatility indices," Journal of Banking & Finance, Elsevier, vol. 32(11), pages 2401-2411, November.
    27. Markopoulou, Chryssa & Skintzi, Vasiliki & Refenes, Apostolos, 2016. "On the predictability of model-free implied correlation," International Journal of Forecasting, Elsevier, vol. 32(2), pages 527-547.
    28. Wang, Jinzhong & Chen, Shijiang & Tao, Qizhi & Zhang, Ting, 2017. "Modelling the implied volatility surface based on Shanghai 50ETF options," Economic Modelling, Elsevier, vol. 64(C), pages 295-301.
    29. Anais Maillet, 2015. "Food price volatility and farmers' production decisions under imperfect information," FOODSECURE Technical papers 8, LEI Wageningen UR.
    30. Shengli Chen & Zili Zhang, 2019. "Forecasting Implied Volatility Smile Surface via Deep Learning and Attention Mechanism," Papers 1912.11059, arXiv.org.
    31. A. A. Brown & L. C. G. Rogers, 2009. "Heterogeneous Beliefs with Finite-Lived Agents," Papers 0907.4953, arXiv.org.
    32. Chatrath, Arjun & Miao, Hong & Ramchander, Sanjay, 2014. "Crude oil moments and PNG stock returns," Energy Economics, Elsevier, vol. 44(C), pages 222-235.
    33. Massimo Guidolin & Kai Wang, 2022. "The Empirical Performance of Option Implied Volatility Surface-Driven Optimal Portfolios," BAFFI CAREFIN Working Papers 22190, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    34. Bedendo, Mascia & Hodges, Stewart D., 2009. "The dynamics of the volatility skew: A Kalman filter approach," Journal of Banking & Finance, Elsevier, vol. 33(6), pages 1156-1165, June.
    35. Élise PAYZAN LE NESTOUR, 2010. "Bayesian Learning in UnstableSettings: Experimental Evidence Based on the Bandit Problem," Swiss Finance Institute Research Paper Series 10-28, Swiss Finance Institute.
    36. Angus A Brown & L C G Rogers, 2010. "Diverse Beliefs," Papers 1001.1450, arXiv.org.
    37. Bernales, Alejandro & Guidolin, Massimo, 2015. "Learning to smile: Can rational learning explain predictable dynamics in the implied volatility surface?," Journal of Financial Markets, Elsevier, vol. 26(C), pages 1-37.
    38. Paruolo Paolo, 2004. "Automated Inference and the Future of Econometrics: A comment," Economics and Quantitative Methods qf04025, Department of Economics, University of Insubria.
    39. Tao Li, 2013. "Investors' Heterogeneity and Implied Volatility Smiles," Management Science, INFORMS, vol. 59(10), pages 2392-2412, October.
    40. Bernales, Alejandro & Verousis, Thanos & Voukelatos, Nikolaos, 2020. "Do investors follow the herd in option markets?," Journal of Banking & Finance, Elsevier, vol. 119(C).
    41. Quaye, Enoch & Tunaru, Radu, 2022. "The stock implied volatility and the implied dividend volatility," Journal of Economic Dynamics and Control, Elsevier, vol. 134(C).
    42. Xue-Zhong He & Lei Shi, 2016. "A Binomial Model of Asset and Option Pricing with Heterogeneous Beliefs," Published Paper Series 2016-4, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    43. Liu, Yi-Fang & Zhang, Wei & Xu, Hai-Chuan, 2014. "Collective behavior and options volatility smile: An agent-based explanation," Economic Modelling, Elsevier, vol. 39(C), pages 232-239.
    44. Nielsen, Carsten Krabbe, 2008. "On rationally confident beliefs and rational overconfidence," Mathematical Social Sciences, Elsevier, vol. 55(3), pages 381-404, May.

  42. Timmermann, Allan, 2001. "Structural Breaks, Incomplete Information and Stock Prices," University of California at San Diego, Economics Working Paper Series qt1sn269d7, Department of Economics, UC San Diego.

    Cited by:

    1. Martin Lettau & Stijn Van Nieuwerburgh, 2006. "Reconciling the Return Predictability Evidence," 2006 Meeting Papers 29, Society for Economic Dynamics.
    2. Londoño Yarce, Juan Miguel & Regúlez Castillo, Marta & Vázquez Pérez, Jesús, 2014. "An Alternative View of the US Price-Dividend Ratio Dynamics," DFAEII Working Papers 1988-088X, University of the Basque Country - Department of Foundations of Economic Analysis II.
    3. Pesaran, M.H. & Pettenuzzo, D. & Timmermann, A., 2006. "Learning, Structural Instability and Present Value Calculations," Cambridge Working Papers in Economics 0602, Faculty of Economics, University of Cambridge.
    4. Michail Karoglou & Bruce Morley & Dennis Thomas, 2013. "Risk and Structural Instability in US House Prices," The Journal of Real Estate Finance and Economics, Springer, vol. 46(3), pages 424-436, April.
    5. Smith, Aaron, 2005. "Level Shifts and the Illusion of Long Memory in Economic Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 321-335, July.
    6. Andrew Ang & Allan Timmermann, 2011. "Regime Changes and Financial Markets," NBER Working Papers 17182, National Bureau of Economic Research, Inc.
    7. Smith, Aaron & Naik, Prasad A. & Tsai, Chih-Ling, 2006. "Markov-switching model selection using Kullback-Leibler divergence," Journal of Econometrics, Elsevier, vol. 134(2), pages 553-577, October.
    8. Zhou, Yinggang, 2014. "Modeling the joint dynamics of risk-neutral stock index and bond yield volatilities," Journal of Banking & Finance, Elsevier, vol. 38(C), pages 216-228.
    9. Pesaran, M. Hashem & Timmermann, Allan, 2004. "How costly is it to ignore breaks when forecasting the direction of a time series?," International Journal of Forecasting, Elsevier, vol. 20(3), pages 411-425.
    10. Massimo Guidolin, 2006. "High equity premia and crash fears - Rational foundations," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 28(3), pages 693-708, August.
    11. J. Doyne Farmer & John Geanakoplos, 2008. "The Virtues and Vices of Equilibrium and the Future of Financial Economics," Levine's Working Paper Archive 122247000000002067, David K. Levine.
    12. Bernales, Alejandro & Chen, Louisa & Valenzuela, Marcela, 2017. "Learning and forecasts about option returns through the volatility risk premium," Journal of Economic Dynamics and Control, Elsevier, vol. 82(C), pages 312-330.
    13. Guidolin, Massimo & Timmermann, Allan, 2007. "Properties of equilibrium asset prices under alternative learning schemes," Journal of Economic Dynamics and Control, Elsevier, vol. 31(1), pages 161-217, January.
    14. Abhimanyu Gupta & Myung Hwan Seo, 2023. "Robust Inference on Infinite and Growing Dimensional Time‐Series Regression," Econometrica, Econometric Society, vol. 91(4), pages 1333-1361, July.
    15. Hyein Shim & Hyeyoen Kim & Sunghyun Kim & Doojin Ryu, 2016. "Testing the relative purchasing power parity hypothesis: the case of Korea," Applied Economics, Taylor & Francis Journals, vol. 48(25), pages 2383-2395, May.
    16. Yi Xue & Ramazan Gencay, 2009. "Trading Frequency and Volatility Clustering," Working Paper series 31_09, Rimini Centre for Economic Analysis.
    17. Massimo Guidolin, 2005. "Pessimistic beliefs under rational learning: quantitative implications for the equity premium puzzle," Working Papers 2005-005, Federal Reserve Bank of St. Louis.
    18. Bernales, Alejandro & Guidolin, Massimo, 2014. "Can we forecast the implied volatility surface dynamics of equity options? Predictability and economic value tests," Journal of Banking & Finance, Elsevier, vol. 46(C), pages 326-342.
    19. Roman Frydman & Soren Johansen & Anders Rahbek & Morten Nyboe Tabor, 2021. "Asset Prices Under Knightian Uncertainty," Working Papers Series inetwp172, Institute for New Economic Thinking.
    20. Jean-Marie Dufour & Richard Luger, 2017. "Identification-robust moment-based tests for Markov switching in autoregressive models," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 713-727, October.
    21. Aaron Smith, 2005. "Forecasting in the presence of level shifts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(8), pages 557-574.
    22. Kelly, David L. & Steigerwald, Douglas G, 2003. "Private Information and High-Frequency Stochastic Volatility," University of California at Santa Barbara, Economics Working Paper Series qt00n4h4mw, Department of Economics, UC Santa Barbara.
    23. Elena Andreou & Eric Ghysels, 2004. "The Impact of Sampling Frequency and Volatility Estimators on Change-Point Tests," CIRANO Working Papers 2004s-25, CIRANO.
    24. Smith Aaron, 2012. "Markov Breaks in Regression Models," Journal of Time Series Econometrics, De Gruyter, vol. 4(1), pages 1-35, May.
    25. Hartmann, Daniel & Kempa, Bernd & Pierdzioch, Christian, 2006. "Economic and Financial Crises and the Predictability of U.S. Stock Returns," MPRA Paper 561, University Library of Munich, Germany.
    26. Guidolin, Massimo, 2003. "International asset prices and portfolio choices under Bayesian learning," Research in Economics, Elsevier, vol. 57(4), pages 383-437, December.
    27. Matei Demetrescu, 2007. "Volatility Clustering in High-Frequency Data: A self-fulfilling prophecy?," Economics Bulletin, AccessEcon, vol. 7(15), pages 1-8.
    28. Granger, Clive W.J. & Machina, Mark J., 2006. "Structural attribution of observed volatility clustering," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 15-29.
    29. Pierdzioch, Christian & Risse, Marian & Rohloff, Sebastian, 2014. "The international business cycle and gold-price fluctuations," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(2), pages 292-305.
    30. Londono, Juan M. & Regúlez, Marta & Vázquez, Jesús, 2015. "An alternative view of the US price–dividend ratio dynamics," International Review of Economics & Finance, Elsevier, vol. 38(C), pages 291-307.
    31. Kanungo, Rama Prasad, 2021. "Uncertainty of M&As under asymmetric estimation," Journal of Business Research, Elsevier, vol. 122(C), pages 774-793.
    32. Pietro Veronesi, "undated". "Belief-dependent Utilities, Aversion to State-Uncertainty and Asset Prices,”," CRSP working papers 529, Center for Research in Security Prices, Graduate School of Business, University of Chicago.
    33. Giorgio Valente & Lucio Sarno, 2005. "Modelling and forecasting stock returns: exploiting the futures market, regime shifts and international spillovers," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(3), pages 345-376.
    34. Daniel Andrei & Bruce Carlin & Michael Hasler, 2019. "Asset Pricing with Disagreement and Uncertainty About the Length of Business Cycles," Management Science, INFORMS, vol. 67(6), pages 2900-2923, June.
    35. Massimo Guidolin & Kai Wang, 2022. "The Empirical Performance of Option Implied Volatility Surface-Driven Optimal Portfolios," BAFFI CAREFIN Working Papers 22190, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    36. Asger Lunde & Allan Timmermann, 2005. "Completion time structures of stock price movements," Annals of Finance, Springer, vol. 1(3), pages 293-326, August.
    37. Bernales, Alejandro & Guidolin, Massimo, 2015. "Learning to smile: Can rational learning explain predictable dynamics in the implied volatility surface?," Journal of Financial Markets, Elsevier, vol. 26(C), pages 1-37.
    38. Abbigail J. Chiodo & Massimo Guidolin & Michael T. Owyang & Makoto Shimoji, 2003. "Subjective probabilities: psychological evidence and economic applications," Working Papers 2003-009, Federal Reserve Bank of St. Louis.
    39. Massimiliano De Santis, 2005. "Movements in the Equity Premium: Evidence from a Bayesian Time-Varying VAR," Money Macro and Finance (MMF) Research Group Conference 2005 62, Money Macro and Finance Research Group.
    40. Yang Lu & Michael Siemer, 2013. "Learning, Rare Disasters, and Asset Prices," Finance and Economics Discussion Series 2013-85, Board of Governors of the Federal Reserve System (U.S.).

  43. White, Halbert & Timmermann, Allan & Sullivan, Ryan, 2001. "Forecast Evaluation with Shared Data Sets," CEPR Discussion Papers 3060, C.E.P.R. Discussion Papers.

    Cited by:

    1. Saša ŽIKOVIÆ & Randall K. FILER, 2013. "Ranking of VaR and ES Models: Performance in Developed and Emerging Markets," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 63(4), pages 327-359, August.
    2. Jasdeep S. Banga & B. Wade Brorsen, 2019. "Profitability of alternative methods of combining the signals from technical trading systems," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 26(1), pages 32-45, January.
    3. Lu, Tsung-Hsun, 2014. "The profitability of candlestick charting in the Taiwan stock market," Pacific-Basin Finance Journal, Elsevier, vol. 26(C), pages 65-78.
    4. Park, Cheol-Ho & Irwin, Scott H., 2005. "The Profitability of Technical Trading Rules in US Futures Markets: A Data Snooping Free Test," AgMAS Project Research Reports 14771, University of Illinois at Urbana-Champaign, Department of Agricultural and Consumer Economics.
    5. Gael M. Martin & Andrew Reidy & Jill Wright, 2009. "Does the option market produce superior forecasts of noise-corrected volatility measures?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(1), pages 77-104.
    6. A. Olasolo & M. A. Pérez & V. Ruiz, 2016. "Active investment strategies in the Spanish futures market: a solution to avoid data snooping bias," Applied Economics Letters, Taylor & Francis Journals, vol. 23(9), pages 609-613, June.
    7. Jiali Fang & Ben Jacobsen & Yafeng Qin, 2014. "Predictability of the simple technical trading rules: An out‐of‐sample test," Review of Financial Economics, John Wiley & Sons, vol. 23(1), pages 30-45, January.
    8. Shynkevich, Andrei, 2012. "Short-term predictability of equity returns along two style dimensions," Journal of Empirical Finance, Elsevier, vol. 19(5), pages 675-685.
    9. Michael P. Clements & Philip Hans Franses & Norman R. Swanson, 2003. "Forecasting economic and financial time-series with non-linear models," Departmental Working Papers 200309, Rutgers University, Department of Economics.
    10. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    11. Shynkevich, Andrei, 2012. "Performance of technical analysis in growth and small cap segments of the US equity market," Journal of Banking & Finance, Elsevier, vol. 36(1), pages 193-208.
    12. Park, Cheol-Ho & Irwin, Scott H., 2005. "A Reality Check on Technical Trading Rule Profits in US Futures Markets," 2005 Conference, April 18-19, 2005, St. Louis, Missouri 19039, NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    13. Ślepaczuk Robert & Sakowski Paweł & Zakrzewski Grzegorz, 2018. "Investment Strategies that Beat the Market. What Can We Squeeze from the Market?," Financial Internet Quarterly (formerly e-Finanse), Sciendo, vol. 14(4), pages 36-55, December.
    14. Jan G. De Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Monash Econometrics and Business Statistics Working Papers 12/05, Monash University, Department of Econometrics and Business Statistics.
    15. Andrei Shynkevich, 2021. "Impact of bitcoin futures on the informational efficiency of bitcoin spot market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(1), pages 115-134, January.
    16. Cheol‐Ho Park & Scott H. Irwin, 2007. "What Do We Know About The Profitability Of Technical Analysis?," Journal of Economic Surveys, Wiley Blackwell, vol. 21(4), pages 786-826, September.
    17. Shynkevich, Andrei, 2013. "Time-series momentum as an intra- and inter-industry effect: Implications for market efficiency," Journal of Economics and Business, Elsevier, vol. 69(C), pages 64-85.
    18. Robert Ślepaczuk & Grzegorz Zakrzewski & Paweł Sakowski, 2012. "Investment strategies beating the market. What can we squeeze from the market?," Working Papers 2012-04, Faculty of Economic Sciences, University of Warsaw.
    19. Afiruddin Tapa* & Mohd Hasimi Yaacob & Ahmad Husni Hamzah & Yean Soh Chuen, 2018. "Trading Performance Analysis: A Comparisons Between the Original MA Crossover and Modified MA Crossover Strategy," The Journal of Social Sciences Research, Academic Research Publishing Group, pages 933-941:6.

  44. Allan Timmerman & Massimo Guidolin, 2001. "Option prices and implied volatility dynamics under Bayesian learning," CeNDEF Workshop Papers, January 2001 P3, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.

    Cited by:

    1. Alexander David & Pietro Veronesi, 1998. "Option Prices with Uncertain Fundamentals: Theory and Evidence on the Dynamics of Implied Volatilities," CRSP working papers 485, Center for Research in Security Prices, Graduate School of Business, University of Chicago.
    2. Sadayuki Ono, 2007. "Option Pricing under Stochastic Volatility and Trading Volume," Discussion Papers 07/05, Department of Economics, University of York.
    3. A. A. Brown & L. C. G. Rogers, 2009. "Heterogeneous Beliefs with Finite-Lived Agents," Papers 0907.4953, arXiv.org.
    4. René Garcia & Eric Ghysels & Eric Renault, 2004. "The Econometrics of Option Pricing," CIRANO Working Papers 2004s-04, CIRANO.
    5. Angus A Brown & L C G Rogers, 2010. "Diverse Beliefs," Papers 1001.1450, arXiv.org.
    6. Paruolo Paolo, 2004. "Automated Inference and the Future of Econometrics: A comment," Economics and Quantitative Methods qf04025, Department of Economics, University of Insubria.
    7. René Garcia & Richard Luger & Eric Renault, 2001. "Empirical Assessment of an Intertemporal Option Pricing Model with Latent Variables (Note : Nouvelle version Février 2002)," CIRANO Working Papers 2001s-02, CIRANO.

  45. Allan Timmermann & Gabriel Perez-Quiros, 2000. "Business Cycle Asymmetries in Stock Returns: Evidence from Higher Order Moments and Conditional Densities," FMG Discussion Papers dp360, Financial Markets Group.

    Cited by:

    1. Andrew Patton, 2002. "(IAM Series No 001) On the Out-Of-Sample Importance of Skewness and Asymetric Dependence for Asset Allocation," FMG Discussion Papers dp431, Financial Markets Group.
    2. Cem Cakmakli & Richard Paap & Dick J.C. van Dijk, 2011. "Modeling and Estimation of Synchronization in Multistate Markov-Switching Models," Tinbergen Institute Discussion Papers 11-002/4, Tinbergen Institute.
    3. Anthony S. Tay & Aamir R. Hashmi, 2004. "Global and Regional Sources of Risk in Equity Markets: Evidence from Factor Models with Time-Varying Conditional Skewness," Econometric Society 2004 Far Eastern Meetings 634, Econometric Society.
    4. L. Baele & R. Vander Vennet & A. Van Landschoot, 2004. "Bank Risk Strategies and Cyclical Variation in Bank Stock Returns," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 04/217, Ghent University, Faculty of Economics and Business Administration.
    5. Matteo Barigozzi & Daniele Massacci, 2022. "Modelling Large Dimensional Datasets with Markov Switching Factor Models," Papers 2210.09828, arXiv.org, revised Dec 2023.
    6. Andrew Ang & Allan Timmermann, 2011. "Regime Changes and Financial Markets," NBER Working Papers 17182, National Bureau of Economic Research, Inc.
    7. Xuan Vinh Vo & Thi Tuan Anh Tran, 2021. "Higher-order comoments and asset returns: evidence from emerging equity markets," Annals of Operations Research, Springer, vol. 297(1), pages 323-340, February.
    8. Haas, Markus & Mittnik, Stefan, 2008. "Multivariate regimeswitching GARCH with an application to international stock markets," CFS Working Paper Series 2008/08, Center for Financial Studies (CFS).
    9. Nguyen, Hoang & Javed, Farrukh, 2021. "Dynamic relationship between Stock and Bond returns: A GAS MIDAS copula approach," Working Papers 2021:15, Örebro University, School of Business.
    10. Chen, Shiu-Sheng, 2010. "Do higher oil prices push the stock market into bear territory?," Energy Economics, Elsevier, vol. 32(2), pages 490-495, March.
    11. Ferrara, Laurent & Marcellino, Massimiliano & Mogliani, Matteo, 2015. "Macroeconomic forecasting during the Great Recession: The return of non-linearity?," International Journal of Forecasting, Elsevier, vol. 31(3), pages 664-679.
    12. Ayelen Banegas, 2016. "Predictability of Growth in Emerging Markets: Information in Financial Aggregates," International Finance Discussion Papers 1174, Board of Governors of the Federal Reserve System (U.S.).
    13. Javed Farrukh & Podgórski Krzysztof, 2017. "Tail Behavior and Dependence Structure in the APARCH Model," Journal of Time Series Econometrics, De Gruyter, vol. 9(2), pages 1-48, July.
    14. Chang, Kuang-Liang, 2012. "The impacts of regime-switching structures and fat-tailed characteristics on the relationship between inflation and inflation uncertainty," Journal of Macroeconomics, Elsevier, vol. 34(2), pages 523-536.
    15. 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.
    16. Zeng, Jhih-Hong & Peng, Chi-Lu & Chen, Ming-Chi & Lee, Chien-Chiang, 2013. "Wealth effects on the housing markets: Do market liquidity and market states matter?," Economic Modelling, Elsevier, vol. 32(C), pages 488-495.
    17. Opschoor, Anne & van Dijk, Dick & van der Wel, Michel, 2014. "Predicting volatility and correlations with Financial Conditions Indexes," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 435-447.
    18. Andrew J. Patton, 2004. "On the Out-of-Sample Importance of Skewness and Asymmetric Dependence for Asset Allocation," Journal of Financial Econometrics, Oxford University Press, vol. 2(1), pages 130-168.
    19. Isah Wada, 2019. "Dynamic Effects of Crude Oil Price Movements: a Sectoral Examination," Romanian Economic Journal, Department of International Business and Economics from the Academy of Economic Studies Bucharest, vol. 22(71), pages 17-28, March.
    20. Camacho, Maximo & Perez Quiros, Gabriel & Poncela, Pilar, 2014. "Green shoots and double dips in the euro area: A real time measure," International Journal of Forecasting, Elsevier, vol. 30(3), pages 520-535.
    21. Lhuissier Stéphane, 2022. "Financial Conditions and Macroeconomic Downside Risks in the Euro Area," Working papers 863, Banque de France.
    22. Lieven Baele & Geert Bekaert & Koen Inghelbrecht & Min Wei, 2020. "Flights to Safety," The Review of Financial Studies, Society for Financial Studies, vol. 33(2), pages 689-746.
    23. Maximo Camacho & Gabriel Perez-Quiros & Pilar Poncela, 2010. "Green shoots in the euro area. A real time measure," Working Papers 1026, Banco de España.
    24. John M Maheu & Thomas H McCurdy & Yong Song, 2010. "Components of bull and bear markets: bull corrections and bear rallies," Working Papers tecipa-402, University of Toronto, Department of Economics.
    25. Chien-Chiang Lee & Chin-Yu Wang & Jhih-Hong Zeng, 2017. "Housing price–volume correlations and boom–bust cycles," Empirical Economics, Springer, vol. 52(4), pages 1423-1450, June.
    26. Chang, Kuang-Liang, 2009. "Do macroeconomic variables have regime-dependent effects on stock return dynamics? Evidence from the Markov regime switching model," Economic Modelling, Elsevier, vol. 26(6), pages 1283-1299, November.
    27. 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.
    28. Wai‐Sum Chan & Li‐Xin Zhang & Siu Hung Cheung, 2009. "Temporal aggregation of Markov‐switching financial return models," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 25(3), pages 359-383, May.
    29. Cees Diks & Valentyn Panchenko & Dick van Dijk, 2011. "Likelihood-based scoring rules for comparing density forecasts in tails," Post-Print hal-00834423, HAL.
    30. John M. Maheu & Thomas McCurdy, 2003. "News Arrival, Jump Dynamics and Volatility Components for Individual Stock Returns," CIRANO Working Papers 2003s-38, CIRANO.
    31. Duong, Diep & Swanson, Norman R., 2015. "Empirical evidence on the importance of aggregation, asymmetry, and jumps for volatility prediction," Journal of Econometrics, Elsevier, vol. 187(2), pages 606-621.
    32. Guidolin, Massimo & Hyde, Stuart, 2012. "Simple VARs cannot approximate Markov switching asset allocation decisions: An out-of-sample assessment," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3546-3566.
    33. Frédérique BEC & Songlin ZENG, 2013. "Do Stock Returns Rebound After Bear Markets? An Empirical Analysis From Five OECD Countries," THEMA Working Papers 2013-21, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    34. Chen, Shiu-Sheng, 2011. "Lack of consumer confidence and stock returns," Journal of Empirical Finance, Elsevier, vol. 18(2), pages 225-236, March.
    35. 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.
    36. González-Rivera, Gloria & Yoldas, Emre, 2012. "Autocontour-based evaluation of multivariate predictive densities," International Journal of Forecasting, Elsevier, vol. 28(2), pages 328-342.
    37. Shiu‐Sheng Chen, 2007. "Does Monetary Policy Have Asymmetric Effects on Stock Returns?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(2‐3), pages 667-688, March.
    38. Ane, Thierry & Ureche-Rangau, Loredana, 2006. "Stock market dynamics in a regime-switching asymmetric power GARCH model," International Review of Financial Analysis, Elsevier, vol. 15(2), pages 109-129.
    39. José Ferreira Machado, 2006. "Identifying asset price booms and busts with quantile regressions," Working Papers w200608, Banco de Portugal, Economics and Research Department.
    40. Victoria Atanasov, 2016. "Conditional interest rate risk and the cross‐section of excess stock returns," Review of Financial Economics, John Wiley & Sons, vol. 30(1), pages 23-32, September.
    41. Monica Billio & Silvio Di Sanzo, 2015. "Granger-causality in Markov switching models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(5), pages 956-966, May.
    42. Jian Yang & Yinggang Zhou & Zijun Wang, 2010. "Conditional Coskewness in Stock and Bond Markets: Time-Series Evidence," Management Science, INFORMS, vol. 56(11), pages 2031-2049, November.
    43. L. Baele & K. Inghelbrecht, 2006. "Structural versus Temporary Drivers of Country and Industry Risk," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 06/413, Ghent University, Faculty of Economics and Business Administration.
    44. Hondroyiannis, George & Papapetrou, Evangelia, 2006. "Stock returns and inflation in Greece: A Markov switching approach," Review of Financial Economics, Elsevier, vol. 15(1), pages 76-94.
    45. Marco Bazzi & Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2017. "Time-Varying Transition Probabilities for Markov Regime Switching Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(3), pages 458-478, May.
    46. Atanasov, Victoria, 2016. "Conditional interest rate risk and the cross-section of excess stock returns," Review of Financial Economics, Elsevier, vol. 30(C), pages 23-32.
    47. Bijsterbosch, Martin & Guérin, Pierre, 2013. "Characterizing very high uncertainty episodes," Economics Letters, Elsevier, vol. 121(2), pages 239-243.
    48. Christopher S. Withers & Saralees Nadarajah & Shou Hsing Shih, 2015. "Moments and Cumulants of a Mixture," Methodology and Computing in Applied Probability, Springer, vol. 17(3), pages 541-564, September.
    49. Chang, Kuang-Liang, 2010. "House price dynamics, conditional higher-order moments, and density forecasts," Economic Modelling, Elsevier, vol. 27(5), pages 1029-1039, September.
    50. Peñaranda, Francisco, 2003. "Evaluation of joint density forecasts of stock and bond returns: predictability and parameter uncertainty," LSE Research Online Documents on Economics 24857, London School of Economics and Political Science, LSE Library.
    51. Shiu-Sheng Chen, 2012. "Consumer confidence and stock returns over market fluctuations," Quantitative Finance, Taylor & Francis Journals, vol. 12(10), pages 1585-1597, October.
    52. Juan Reboredo, 2010. "Nonlinear effects of oil shocks on stock returns: a Markov-switching approach," Applied Economics, Taylor & Francis Journals, vol. 42(29), pages 3735-3744.
    53. David Nawrocki & Tonis Vaga, 2014. "A bifurcation model of market returns," Quantitative Finance, Taylor & Francis Journals, vol. 14(3), pages 509-528, March.
    54. Esfandiar Maasoumi & Jeffrey Racine, 2009. "A Robust Entropy-Based Test of Asymmetry for Discrete and Continuous Processes," Econometric Reviews, Taylor & Francis Journals, vol. 28(1-3), pages 246-261.
    55. John M Maheu & Thomas H McCurdy & Yong Song, 2009. "Extracting bull and bear markets from stock returns," Working Papers tecipa-369, University of Toronto, Department of Economics.
    56. 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.
    57. Hess, Martin K., 2003. "What drives Markov regime-switching behavior of stock markets? The Swiss case," International Review of Financial Analysis, Elsevier, vol. 12(5), pages 527-543.
    58. Coakley, Jerry & Fuertes, Ana-Maria, 2006. "Testing for sign and amplitude asymmetries using threshold autoregressions," Journal of Economic Dynamics and Control, Elsevier, vol. 30(4), pages 623-654, April.
    59. Maciejowska, Katarzyna, 2013. "Assessing the number of components in a normal mixture: an alternative approach," MPRA Paper 50303, University Library of Munich, Germany.
    60. Giorgio Valente & Lucio Sarno, 2005. "Modelling and forecasting stock returns: exploiting the futures market, regime shifts and international spillovers," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(3), pages 345-376.
    61. Baele, Lieven & Inghelbrecht, Koen, 2009. "Time-varying Integration and International diversification strategies," Journal of Empirical Finance, Elsevier, vol. 16(3), pages 368-387, June.
    62. Hashmi, Aamir R. & Tay, Anthony S., 2007. "Global regional sources of risk in equity markets: Evidence from factor models with time-varying conditional skewness," Journal of International Money and Finance, Elsevier, vol. 26(3), pages 430-453, April.
    63. KIANI, Khurshid M., 2007. "Business Cycle Asymmetries In Stock Returns: Robust Evidence," International Journal of Applied Econometrics and Quantitative Studies, Euro-American Association of Economic Development, vol. 4(2), pages 99-120.
    64. Guidolin, Massimo & Hyde, Stuart, 2012. "Can VAR models capture regime shifts in asset returns? A long-horizon strategic asset allocation perspective," Journal of Banking & Finance, Elsevier, vol. 36(3), pages 695-716.
    65. Anne Opschoor & Dick van Dijk & Michel van der Wel, 2013. "Predicting Covariance Matrices with Financial Conditions Indexes," Tinbergen Institute Discussion Papers 13-113/III, Tinbergen Institute.
    66. Martin Hess, 2006. "Timing and diversification: A state-dependent asset allocation approach," The European Journal of Finance, Taylor & Francis Journals, vol. 12(3), pages 189-204.
    67. Mai Shibata, 2014. "The Influence of Japan’s Unsecured Overnight Call Rate on Bull and Bear Markets and Market Turns," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 21(4), pages 331-349, November.
    68. Wee, Damien C.H. & Chen, Feng & Dunsmuir, William T.M., 2022. "Likelihood inference for Markov switching GARCH(1,1) models using sequential Monte Carlo," Econometrics and Statistics, Elsevier, vol. 21(C), pages 50-68.
    69. Chan, Raymond H. & Chow, Sheung-Chi & Guo, Xu & Wong, Wing-Keung, 2022. "Central moments, stochastic dominance, moment rule, and diversification with an application," Chaos, Solitons & Fractals, Elsevier, vol. 161(C).
    70. Katarzyna Maciejowska, 2010. "Estimation Methods Comparison of SVAR Models with a Mixture of Two Normal Distributions," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 2(4), pages 279-314, September.
    71. Kim, Tae-Hwan & White, Halbert, 2004. "On more robust estimation of skewness and kurtosis," Finance Research Letters, Elsevier, vol. 1(1), pages 56-73, March.
    72. Geweke, John, 2007. "Interpretation and inference in mixture models: Simple MCMC works," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3529-3550, April.
    73. Massacci, Daniele, 2013. "A switching model with flexible threshold variable: With an application to nonlinear dynamics in stock returns," Economics Letters, Elsevier, vol. 119(2), pages 199-203.
    74. Ayben Koy, 2017. "Modelling Nonlinear Dynamics of Oil Futures Market," Econometric Research in Finance, SGH Warsaw School of Economics, Collegium of Economic Analysis, vol. 2(1), pages 23-42, June.
    75. Bali, Turan G. & Demirtas, K. Ozgur & Levy, Haim, 2008. "Nonlinear mean reversion in stock prices," Journal of Banking & Finance, Elsevier, vol. 32(5), pages 767-782, May.
    76. Jun Tu, 2010. "Is Regime Switching in Stock Returns Important in Portfolio Decisions?," Management Science, INFORMS, vol. 56(7), pages 1198-1215, July.
    77. Chang, Kuang-Liang, 2012. "Volatility regimes, asymmetric basis effects and forecasting performance: An empirical investigation of the WTI crude oil futures market," Energy Economics, Elsevier, vol. 34(1), pages 294-306.
    78. Richard D. F. Harris & Murat Mazibas, 2022. "A component Markov regime‐switching autoregressive conditional range model," Bulletin of Economic Research, Wiley Blackwell, vol. 74(2), pages 650-683, April.
    79. Chiu-Lan Chang & Paul L. Hsueh, 2013. "An Investigation of the Flight-to-Quality Effect: Evidence from Asia-Pacific Countries," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 49(S4), pages 53-69, September.
    80. Shum, Wai Yan, 2020. "Modelling conditional skewness: Heterogeneous beliefs, short sale restrictions and market declines," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    81. Klaus Grobys, 2012. "Active PortofolioManagement in the Presence of Regime Switching: What Are the Benefits of Defensive Asset Allocation Strategies If the Investor Faces Bear Markets?," 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. 4(1), pages 015-031, June.
    82. Vanden, Joel M., 2005. "Equilibrium analysis of volatility clustering," Journal of Empirical Finance, Elsevier, vol. 12(3), pages 374-417, June.

  46. Allan Timmermann, 1999. "Moments of Markov Switching Models," FMG Discussion Papers dp323, Financial Markets Group.

    Cited by:

    1. Cem Cakmakli & Richard Paap & Dick J.C. van Dijk, 2011. "Modeling and Estimation of Synchronization in Multistate Markov-Switching Models," Tinbergen Institute Discussion Papers 11-002/4, Tinbergen Institute.
    2. Giorgio Canarella & WenShwo Fang & Stephen M. Miller & Stephen K. Pollard, 2008. "Is the Great Moderation Ending? UK and US Evidence," Working papers 2008-24, University of Connecticut, Department of Economics.
    3. Nelson Areal & Maria Cortez & Florinda Silva, 2013. "The conditional performance of US mutual funds over different market regimes: do different types of ethical screens matter?," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 27(4), pages 397-429, December.
    4. Alexander Arimond & Damian Borth & Andreas Hoepner & Michael Klawunn & Stefan Weisheit, 2020. "Neural Networks and Value at Risk," Papers 2005.01686, arXiv.org, revised May 2020.
    5. Andrew Ang & Allan Timmermann, 2011. "Regime Changes and Financial Markets," NBER Working Papers 17182, National Bureau of Economic Research, Inc.
    6. Don Harding & Adrian Pagan, 2000. "Disecting the Cycle: A Methodological Investigation," Econometric Society World Congress 2000 Contributed Papers 1164, Econometric Society.
    7. Erik Kole & Dick Dijk, 2017. "How to Identify and Forecast Bull and Bear Markets?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(1), pages 120-139, January.
    8. Carrasco, Marine, 2002. "Misspecified Structural Change, Threshold, and Markov-switching models," Journal of Econometrics, Elsevier, vol. 109(2), pages 239-273, August.
    9. Mototsugu Shintani, 2003. "Nonlinear Forecasting Analysis Using Diffusion Indexes: An Application to Japan," Vanderbilt University Department of Economics Working Papers 0322, Vanderbilt University Department of Economics, revised Apr 2004.
    10. Massimo Guidolin & Giovanna Nicodano, 2007. "Managing international portfolios with small capitalization stocks," Working Papers 2007-030, Federal Reserve Bank of St. Louis.
    11. Nidhaleddine Ben Cheikh & Younes Ben Zaied, 2021. "A new look at carbon dioxide emissions in MENA countries," Climatic Change, Springer, vol. 166(3), pages 1-22, June.
    12. Haas, Markus & Mittnik, Stefan, 2008. "Multivariate regimeswitching GARCH with an application to international stock markets," CFS Working Paper Series 2008/08, Center for Financial Studies (CFS).
    13. van Dijk, D.J.C. & Terasvirta, T. & Franses, Ph.H.B.F., 2000. "Smooth transition autoregressive models - A survey of recent developments," Econometric Institute Research Papers EI 2000-23/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    14. Chan, Kalok & Yang, Jian & Zhou, Yinggang, 2018. "Conditional co-skewness and safe-haven currencies: A regime switching approach," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 58-80.
    15. Meenagh, David & Minford, Patrick & Peel, David, 2007. "Simulating stock returns under switching regimes - A new test of market efficiency," Economics Letters, Elsevier, vol. 94(2), pages 235-239, February.
    16. Zhang, Yue-Jun & Yao, Ting & He, Ling-Yun & Ripple, Ronald, 2019. "Volatility forecasting of crude oil market: Can the regime switching GARCH model beat the single-regime GARCH models?," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 302-317.
    17. 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.
    18. Leland E. Farmer & Lawrence Schmidt & Allan Timmermann, 2023. "Pockets of Predictability," Journal of Finance, American Finance Association, vol. 78(3), pages 1279-1341, June.
    19. Massimo Guidolin & Allan Timmermann, 2008. "International asset allocation under regime switching, skew, and kurtosis preferences," The Review of Financial Studies, Society for Financial Studies, vol. 21(2), pages 889-935, April.
    20. Niels Haldrup & Robinson Kruse & Timo Teräsvirta & Rasmus T. Varneskov, 2012. "Unit roots, nonlinearities and structural breaks," CREATES Research Papers 2012-14, Department of Economics and Business Economics, Aarhus University.
    21. Guidolin, Massimo & Hyde, Stuart, 2008. "Equity portfolio diversification under time-varying predictability: Evidence from Ireland, the US, and the UK," Journal of Multinational Financial Management, Elsevier, vol. 18(4), pages 293-312, October.
    22. Emmanouil Platanakis & Athanasios Sakkas & Charles Sutcliffe, 2017. "Harmful Diversification: Evidence from Alternative Investments," ICMA Centre Discussion Papers in Finance icma-dp2017-09, Henley Business School, University of Reading.
    23. Chris Stivers & Licheng Sun, 2013. "Market Cycles and the Performance of Relative Strength Strategies," Financial Management, Financial Management Association International, vol. 42(2), pages 263-290, June.
    24. Chih-Nan Chen & Chien-Hsiu Lin, 2022. "Optimal carry trade portfolio choice under regime shifts," Review of Quantitative Finance and Accounting, Springer, vol. 59(2), pages 483-506, August.
    25. Ryan Lemand, 2003. "The Contagion Effect Between the Volatilities of the NASDAQ-100 and the IT.CA :A Univariate and A Bivariate Switching Approach," Econometrics 0307002, University Library of Munich, Germany, revised 07 Dec 2020.
    26. Yun Xie & Yixiang Tian & Zhuang Xiao & Xiangyun Zhou, 2018. "Dependence of credit spread and macro-conditions based on an alterable structure model," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-15, May.
    27. Massimo Guidolin, 2011. "Markov Switching Models in Empirical Finance," Working Papers 415, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    28. Frédérick Demers & Ryan Macdonald, 2007. "The Canadian Business Cycle: A Comparison of Models," Staff Working Papers 07-38, Bank of Canada.
    29. Chan, Wai-Sum & Chan, Yin-Ting, 2008. "A note on the autocorrelation properties of temporally aggregated Markov switching Gaussian models," Statistics & Probability Letters, Elsevier, vol. 78(6), pages 728-735, April.
    30. Pål Nicolai Henriksen, 2011. "Pricing barrier options by a regime switching model," Quantitative Finance, Taylor & Francis Journals, vol. 11(8), pages 1221-1231.
    31. Lhuissier Stéphane, 2022. "Financial Conditions and Macroeconomic Downside Risks in the Euro Area," Working papers 863, Banque de France.
    32. Pérez-Quirós, Gabriel & Poncela, Pilar & Camacho, Máximo, 2012. "Extracting nonlinear signals from several economic indicators," CEPR Discussion Papers 8865, C.E.P.R. Discussion Papers.
    33. Prukumpai, Suthawan, 2015. "Time-varying Industrial Portfolio Betas under the Regime-switching Model:Evidence from the Stock Exchange of Thailand," Asian Journal of Applied Economics, Kasetsart University, Center for Applied Economics Research, vol. 22(2), December.
    34. Kaihua Deng, 2018. "Another Look at Large-Cap Stock Return Comovement: A Semi-Markov-Switching Approach," Computational Economics, Springer;Society for Computational Economics, vol. 51(2), pages 227-262, February.
    35. Chan, Wai-Sum, 2022. "On temporal aggregation of some nonlinear time-series models," Econometrics and Statistics, Elsevier, vol. 21(C), pages 38-49.
    36. 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.
    37. Bekaert, Geert & Hodrick, Robert J. & Zhang, Xiaoyan, 2012. "Aggregate Idiosyncratic Volatility," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 47(6), pages 1155-1185, December.
    38. Lin, Shih-Kuei & Lin, Chien-Hsiu & Chuang, Ming-Che & Chou, Chia-Yu, 2014. "A recursive formula for a participating contract embedding a surrender option under regime-switching model with jump risks: Evidence from stock indices," Economic Modelling, Elsevier, vol. 38(C), pages 341-350.
    39. Vikram Krishnamurthy & Elisabeth Leoff & Jorn Sass, 2016. "Filterbased Stochastic Volatility in Continuous-Time Hidden Markov Models," Papers 1602.05323, arXiv.org.
    40. Wai‐Sum Chan & Li‐Xin Zhang & Siu Hung Cheung, 2009. "Temporal aggregation of Markov‐switching financial return models," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 25(3), pages 359-383, May.
    41. Kuang‐Liang Chang & Chi‐Wei He, 2010. "Does The Magnitude Of The Effect Of Inflation Uncertainty On Output Growth Depend On The Level Of Inflation?," Manchester School, University of Manchester, vol. 78(2), pages 126-148, March.
    42. Kaihua Deng, 2015. "Power Attrition of Asymmetric Tail Comovement Test," Economics Bulletin, AccessEcon, vol. 35(4), pages 2813-2819.
    43. Duong, Diep & Swanson, Norman R., 2015. "Empirical evidence on the importance of aggregation, asymmetry, and jumps for volatility prediction," Journal of Econometrics, Elsevier, vol. 187(2), pages 606-621.
    44. Yue-Jun Zhang & Ting Yao & Ling-Yun He, 2015. "Forecasting crude oil market volatility: can the Regime Switching GARCH model beat the single-regime GARCH models?," Papers 1512.01676, arXiv.org.
    45. 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.
    46. John M. Maheu & Tom McCurdy, 2000. "Volatility Dynamics Under Duration-Dependent Mixing," Econometric Society World Congress 2000 Contributed Papers 1427, Econometric Society.
    47. Stavros Degiannakis & Christos Floros & Enrique Salvador & Dimitrios Vougas, 2022. "On the stationarity of futures hedge ratios," Operational Research, Springer, vol. 22(3), pages 2281-2303, July.
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    1. Kurmaş Akdoğan, 2017. "Unemployment hysteresis and structural change in Europe," Empirical Economics, Springer, vol. 53(4), pages 1415-1440, December.
    2. Goodness C. Aye & Mehmet Balcilar & Rangan Gupta, 2015. "International Stock Return Predictability: Is the Role of U.S. Time-Varying?," Working Papers 201524, University of Pretoria, Department of Economics.
    3. Yang K. Lu & Pierre Perron, 2008. "Modeling and Forecasting Stock Return Volatility Using a Random Level Shift Model," Boston University - Department of Economics - Working Papers Series wp2008-012, Boston University - Department of Economics.
    4. Altissimo, Filippo & Corradi, Valentina, 2003. "Strong rules for detecting the number of breaks in a time series," Journal of Econometrics, Elsevier, vol. 117(2), pages 207-244, December.
    5. Kurmaş Akdoğan, 2015. "Unemployment Hysteresis and Structural Change in Europe," EY International Congress on Economics II (EYC2015), November 5-6, 2015, Ankara, Turkey 266, Ekonomik Yaklasim Association.
    6. Liew, Freddy, 2012. "Forecasting inflation in Asian economies," MPRA Paper 36781, University Library of Munich, Germany.
    7. Kurmaş Akdoğan, 2015. "Asymmetric Behaviour of Inflation around the Target in Inflation-Targeting Countries," Scottish Journal of Political Economy, Scottish Economic Society, vol. 62(5), pages 486-504, November.

  48. Allan Timmermann & Gabriel Perez-Quiros, 1999. "Firm Size and Cyclical Variations in Stock Returns," FMG Discussion Papers dp335, Financial Markets Group.

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    1. Francisco Covas & Wouter Denhaan, 2006. "The role of debt and equity finance over the business cycle," 2006 Meeting Papers 407, Society for Economic Dynamics.
    2. Puneet Handa, 2006. "Does Stock Return Predictability Imply Improved Asset Allocation and Performance? Evidence from the U.S. Stock Market (1954–2002)," The Journal of Business, University of Chicago Press, vol. 79(5), pages 2423-2468, September.
    3. Paulo Maio, 2014. "Another Look at the Stock Return Response to Monetary Policy Actions," Review of Finance, European Finance Association, vol. 18(1), pages 321-371.
    4. Abdul Karim, Zulkefly & Zaidi, Mohd Azlan Shah & Karim, Bakri, 2011. "Does Firm-Level Equity Return Respond to Domestic and International Monetary Policy Shocks? A Panel Data Study of Malaysia," Jurnal Ekonomi Malaysia, Faculty of Economics and Business, Universiti Kebangsaan Malaysia, vol. 45, pages 21-31.
    5. Pandey I M, 2005. "What Drives the Shareholer Value?," IIMA Working Papers WP2005-09-04, Indian Institute of Management Ahmedabad, Research and Publication Department.
    6. Cem Cakmakli & Richard Paap & Dick J.C. van Dijk, 2011. "Modeling and Estimation of Synchronization in Multistate Markov-Switching Models," Tinbergen Institute Discussion Papers 11-002/4, Tinbergen Institute.
    7. Hur, Jungshik & Pettengill, Glenn & Singh, Vivek, 2014. "Market states and the risk-based explanation of the size premium," Journal of Empirical Finance, Elsevier, vol. 28(C), pages 139-150.
    8. Alessandra Guariglia & Marina-Eliza Spaliara & Serafeim Tsoukas, 2016. "To What Extent Does the Interest Burden Affect Firm Survival? Evidence from a Panel of UK Firms during the Recent Financial Crisis," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(4), pages 576-594, August.
    9. Alexandros Kontonikas & Alexandros Kostakis, 2013. "On Monetary Policy and Stock Market Anomalies," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 40(7-8), pages 1009-1042, September.
    10. Nguyen, Duc Binh Benno & Prokopczuk, Marcel & Sibbertsen, Philipp, 2017. "The Memory of Stock Return Volatility: Asset Pricing Implications," Hannover Economic Papers (HEP) dp-613, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    11. Carol Alexander & Anca Dimitriu, 2003. "Equity Indexing: Conitegration and Stock Price Dispersion: A Regime Switiching Approach to market Efficiency," ICMA Centre Discussion Papers in Finance icma-dp2003-02, Henley Business School, University of Reading.
    12. Don Bredin & Stuart Hyde, 2008. "Regime Change and the Role of International Markets on the Stock Returns of Small Open Economies," European Financial Management, European Financial Management Association, vol. 14(2), pages 315-346, March.
    13. Eijffinger, S.C.W. & Mahieu, R.J. & Raes, L.B.D., 2012. "Can the Fed talk the Hind Legs off the Stock Market? (replaces CentER DP 2011-072)," Other publications TiSEM 347a970d-4a05-416f-a351-1, Tilburg University, School of Economics and Management.
    14. L. Baele & R. Vander Vennet & A. Van Landschoot, 2004. "Bank Risk Strategies and Cyclical Variation in Bank Stock Returns," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 04/217, Ghent University, Faculty of Economics and Business Administration.
    15. Renatas Kizys & Peter Spencer, 2007. "Assessing the Relation between Equity Risk Premium and Macroeconomic Volatilities in the UK," Discussion Papers 07/13, Department of Economics, University of York.
    16. Matteo Barigozzi & Daniele Massacci, 2022. "Modelling Large Dimensional Datasets with Markov Switching Factor Models," Papers 2210.09828, arXiv.org, revised Dec 2023.
    17. David McMillan & Alan Speight, 2006. "Non-linear long horizon returns predictability: evidence from six south-east Asian markets," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 13(2), pages 95-111, June.
    18. 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.
    19. 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.
    20. Andrew Ang & Allan Timmermann, 2011. "Regime Changes and Financial Markets," NBER Working Papers 17182, National Bureau of Economic Research, Inc.
    21. 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.
    22. Lorenzo Cerboni Baiardi & Massimo Costabile & Domenico De Giovanni & Fabio Lamantia & Arturo Leccadito & Ivar Massabó & Massimiliano Menzietti & Marco Pirra & Emilio Russo & Alessandro Staino, 2020. "The Dynamics of the S&P 500 under a Crisis Context: Insights from a Three-Regime Switching Model," Risks, MDPI, vol. 8(3), pages 1-15, July.
    23. Erik Kole & Dick Dijk, 2017. "How to Identify and Forecast Bull and Bear Markets?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(1), pages 120-139, January.
    24. Atanasov, Victoria & Nitschka, Thomas, 2017. "Firm size, economic risks, and the cross-section of international stock returns," The North American Journal of Economics and Finance, Elsevier, vol. 39(C), pages 110-126.
    25. Wu-Jen Chuang & Liang-Yuh Ou-Yang & Wen-Chen Lo, 2009. "Nonlinear Market Dynamics Between Stock Returns And Trading Volume: Empirical Evidences From Asian Stock Markets," Analele Stiintifice ale Universitatii "Alexandru Ioan Cuza" din Iasi - Stiinte Economice (1954-2015), Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, vol. 56, pages 621-634, November.
    26. Ali Ozdagli & Mihail Velikov, 2016. "Show me the money: the monetary policy risk premium," Working Papers 16-27, Federal Reserve Bank of Boston.
    27. Pesaran, M. Hashem & Timmermann, Allan, 2004. "How costly is it to ignore breaks when forecasting the direction of a time series?," International Journal of Forecasting, Elsevier, vol. 20(3), pages 411-425.
    28. Lucia BALDI & Massimo PERI & Daniela VANDONE, 2010. "Is wine a financial parachute?," Departmental Working Papers 2010-01, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    29. Chang-Chih Chen & Chia-Chien Chang, 2019. "How Big are the Ambiguity-Based Premiums on Mortgage Insurances?," The Journal of Real Estate Finance and Economics, Springer, vol. 58(1), pages 133-157, January.
    30. Massimo Guidolin & Francesco Ravazzolo & Andrea Tortora, 2014. "Myths and Facts about the Alleged Over-Pricing of U.S. Real Estate," The Journal of Real Estate Finance and Economics, Springer, vol. 49(4), pages 477-523, November.
    31. Carol Alexander & Anca Dimitriu, 2005. "Indexing, cointegration and equity market regimes," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 10(3), pages 213-231.
    32. Massimo Guidolin & Giovanna Nicodano, 2007. "Managing international portfolios with small capitalization stocks," Working Papers 2007-030, Federal Reserve Bank of St. Louis.
    33. Chen, Shiu-Sheng, 2012. "Revisiting the empirical linkages between stock returns and trading volume," Journal of Banking & Finance, Elsevier, vol. 36(6), pages 1781-1788.
    34. Cao, Yue & Dong, Yizhe & Ma, Diandian & Sun, Li, 2021. "Customer concentration and corporate risk-taking," Journal of Financial Stability, Elsevier, vol. 54(C).
    35. Betz, Frank & Ravasan, Farshad R., 2016. "Collateral regimes and missing job creation in the MENA region," EIB Working Papers 2016/03, European Investment Bank (EIB).
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    249. Mototsugu Shintani & Tomoyoshi Yabu & Daisuke Nagakura, 2008. "Spurious Regressions in Technical Trading: Momentum or Contrarian?," IMES Discussion Paper Series 08-E-09, Institute for Monetary and Economic Studies, Bank of Japan.
    250. Hoffmann, Arvid O.I. & Shefrin, Hersh, 2014. "Technical analysis and individual investors," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PB), pages 487-511.
    251. Vincent, Kendro & Hsu, Yu-Chin & Lin, Hsiou-Wei, 2021. "Investment styles and the multiple testing of cross-sectional stock return predictability," Journal of Financial Markets, Elsevier, vol. 56(C).
    252. Jin, Xiaoye, 2021. "What do we know about the popularity of technical analysis in foreign exchange markets? A skewness preference perspective," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 71(C).
    253. Cao, Ji & Muhl, Stefan & Rieger, Marc Oliver & Chen, Hung-Ling, 2023. "Sign matters: Stock-movement-based trading decisions of individual investors," Journal of Banking & Finance, Elsevier, vol. 148(C).
    254. Shynkevich, Andrei, 2013. "Time-series momentum as an intra- and inter-industry effect: Implications for market efficiency," Journal of Economics and Business, Elsevier, vol. 69(C), pages 64-85.
    255. Dichtl, Hubert, 2020. "Forecasting excess returns of the gold market: Can we learn from stock market predictions?," Journal of Commodity Markets, Elsevier, vol. 19(C).
    256. Konstandinos Chourmouziadis & Dimitra K. Chourmouziadou & Prodromos D. Chatzoglou, 2021. "Embedding Four Medium-Term Technical Indicators to an Intelligent Stock Trading Fuzzy System for Predicting: A Portfolio Management Approach," Computational Economics, Springer;Society for Computational Economics, vol. 57(4), pages 1183-1216, April.
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    261. Strobel, Marcus & Auer, Benjamin R., 2018. "Does the predictive power of variable moving average rules vanish over time and can we explain such tendencies?," International Review of Economics & Finance, Elsevier, vol. 53(C), pages 168-184.
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    263. M. A. H. Dempster & C. M. Jones, 2002. "Can channel pattern trading be profitably automated?," The European Journal of Finance, Taylor & Francis Journals, vol. 8(3), pages 275-301.
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    265. Anarkulova, Aizhan & Cederburg, Scott & O’Doherty, Michael S., 2022. "Stocks for the long run? Evidence from a broad sample of developed markets," Journal of Financial Economics, Elsevier, vol. 143(1), pages 409-433.
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  50. Lunde, Asger & Timmermann, Allan & Blake, David, 1998. "The Hazards of Mutual Fund Underperformance: A Cox Regression Analysis," University of California at San Diego, Economics Working Paper Series qt1pd3z1hm, Department of Economics, UC San Diego.

    Cited by:

    1. A. Colin Cameron & Anthony D. Hall, 2003. "A Survival Analysis of Australian Equity Mutual Funds," Australian Journal of Management, Australian School of Business, vol. 28(2), pages 209-226, September.
    2. Ma, Tiejun & Tang, Leilei & McGroarty, Frank & Sung, Ming-Chien & Johnson, Johnnie E. V, 2016. "Time is money: Costing the impact of duration misperception in market prices," European Journal of Operational Research, Elsevier, vol. 255(2), pages 397-410.
    3. Bank for International Settlements, 2003. "Incentive structures in institutional asset management and their implications for financial markets," CGFS Papers, Bank for International Settlements, number 21, december.
    4. Stephen Brown & William Goetzmann & James Park, 1998. "Conditions for Survival: Changing Risk and the Performance of Hedge Fund Managers and CTAs," Yale School of Management Working Papers ysm83, Yale School of Management, revised 01 Apr 2008.
    5. Darolles, Serge & Florens, Jean-Pierre & Simon, Guillaume, 2010. "Nonparametric Analysis of Hedge Funds Lifetimes," IDEI Working Papers 620, Institut d'Économie Industrielle (IDEI), Toulouse.
    6. Mohammad Mojtahedi & Sidney Newton & Jason Meding, 2017. "Predicting the resilience of transport infrastructure to a natural disaster using Cox’s proportional hazards regression model," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 85(2), pages 1119-1133, January.
    7. Jung-Min KIM, 2015. "Failure Risk and the Cross-Section of Hedge Fund Returns," Working Papers 2015-13, Economic Research Institute, Bank of Korea.
    8. Cogneau, Philippe & Hübner, Georges, 2015. "The prediction of fund failure through performance diagnostics," Journal of Banking & Finance, Elsevier, vol. 50(C), pages 224-241.
    9. Yehong Liu & Guosheng Yin, 2018. "Average Holding Price," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 13(01), pages 1-20, March.
    10. Bessler, Wolfgang & Blake, David & Lückoff, Peter & Tonks, Ian, 2010. "Why does mutual fund performance not persist? The impact and interaction of fund flows and manager changes," MPRA Paper 34185, University Library of Munich, Germany.
    11. Hanke, Bernd & Keswani, Aneel & Quigley, Garrett & Zagonov, Maxim, 2018. "Survivorship bias and comparability of UK open-ended fund databases," Economics Letters, Elsevier, vol. 172(C), pages 110-114.
    12. Peter A. F. Fraser‐Mackenzie & Tiejun Ma & Ming‐Chien Sung & Johnnie E. V. Johnson, 2019. "Let's Call it Quits: Break‐Even Effects in the Decision to Stop Taking Risks," Risk Analysis, John Wiley & Sons, vol. 39(7), pages 1560-1581, July.
    13. Alex Grecu & Burton G. Malkiel & Atanu Saha, 2006. "Why Do Hedge Funds Stop Reporting Their Performance?," Working Papers 78, Princeton University, Department of Economics, Center for Economic Policy Studies..
    14. Xisong Jin & Francisco Nadal De Simone, 2015. "Investment funds? vulnerabilities: A tail-risk dynamic CIMDO approach," BCL working papers 95, Central Bank of Luxembourg.
    15. Jin, Xisong & Nadal De Simone, Francisco, 2014. "A framework for tracking changes in the intensity of investment funds' systemic risk," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 343-368.
    16. Zhao, Xinge, 2004. "Why are some mutual funds closed to new investors?," Journal of Banking & Finance, Elsevier, vol. 28(8), pages 1867-1887, August.
    17. Emmanuel Mamatzakis & Mike G. Tsionas, 2021. "Testing for persistence in US mutual funds’ performance: a Bayesian dynamic panel model," Annals of Operations Research, Springer, vol. 299(1), pages 1203-1233, April.
    18. Kozo Kiyota & Miho Takizawa, 2007. "The Shadow of Death: Pre-exit Performance of Firms in Japan," Hi-Stat Discussion Paper Series d06-204, Institute of Economic Research, Hitotsubashi University.
    19. Blake, David & Cairns, Andrew & Dowd, Kevin, 2008. "Turning pension plans into pension planes: What investment strategy designers of defined contribution pension plans can learn from commercial aircraft designers," MPRA Paper 33749, University Library of Munich, Germany.
    20. Qiang Bu & Nelson Lacey, 2009. "On understanding mutual fund terminations," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 33(1), pages 80-99, January.
    21. Emmanuel Mamatzakis & Mike Tsionas, 2018. "A Bayesian dynamic model to test persistence in funds' performance," Working Paper series 18-23, Rimini Centre for Economic Analysis.
    22. Fletcher, Jonathan & Forbes, David, 2002. "An exploration of the persistence of UK unit trust performance," Journal of Empirical Finance, Elsevier, vol. 9(5), pages 475-493, December.
    23. Juan Yao & Graham Partington & Max Stevenson, 2005. "Run length and the predictability of stock price reversals," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 45(4), pages 653-671, December.
    24. Matallín-Sáez, Juan Carlos & Soler-Domínguez, Amparo & Tortosa-Ausina, Emili, 2016. "On the robustness of persistence in mutual fund performance," The North American Journal of Economics and Finance, Elsevier, vol. 36(C), pages 192-231.
    25. Carree, Martin A., 2003. "A hazard rate analysis of Russian commercial banks in the period 1994-1997," Economic Systems, Elsevier, vol. 27(3), pages 255-269, September.
    26. Boldron, François & Fève, Frédérique & Florens, Jean-Pierre & Panet-Amaro, C. & Valognes, C., 2010. "Econometric Models and the Evolution of Post-Offices Network," IDEI Working Papers 626, Institut d'Économie Industrielle (IDEI), Toulouse.
    27. Boyson, Nicole M., 2010. "Implicit incentives and reputational herding by hedge fund managers," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 283-299, June.
    28. Naohiko Baba & Hiromichi Goko, 2006. "Survival Analysis of Hedge Funds," Bank of Japan Working Paper Series 06-E-5, Bank of Japan.
    29. Cumming, Douglas & Dai, Na & Johan, Sofia, 2015. "Are hedge funds registered in Delaware different?," Journal of Corporate Finance, Elsevier, vol. 35(C), pages 232-246.
    30. Carree, M.A., 2000. "Interest and Hazard Rates of Russian Saving Banks," ERIM Report Series Research in Management ERS-2000-26-STR, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    31. Yamashita, Takashi, 2007. "House price appreciation, liquidity constraints, and second mortgages," Journal of Urban Economics, Elsevier, vol. 62(3), pages 424-440, November.

  51. Sullivan, Ryan & Timmermann, Allan & White, Halbert, 1998. "Dangers of Data-Driven Inference: The Case of Calendar Effects in Stock Returns," University of California at San Diego, Economics Working Paper Series qt2z02z6d9, Department of Economics, UC San Diego.

    Cited by:

    1. Goran Karanovic & Bisera Karanovic, 2018. "The Day-of-the-Week Effect: Evidence from Selected Balkan Markets," Scientific Annals of Economics and Business (continues Analele Stiintifice), Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, vol. 65(1), pages 1-11, March.
    2. Michael P. Clements & Philip Hans Franses & Norman R. Swanson, 2003. "Forecasting economic and financial time-series with non-linear models," Departmental Working Papers 200309, Rutgers University, Department of Economics.
    3. Edwin D. Maberly & Daniel F. Waggoner, 2000. "Closing the question on the continuation of turn-of-the-month effects: evidence from the S&P 500 Index futures contract," FRB Atlanta Working Paper 2000-11, Federal Reserve Bank of Atlanta.
    4. Sasidharan, Anand, 2009. "Does seasonality persists in Indian stock markets?," MPRA Paper 24185, University Library of Munich, Germany, revised Aug 2010.
    5. Ayman Abdalmajeed Ahmad Al-Smadi & Mahmoud Khalid Almsafir & Nur Hanis Hazwani Binti Husni, 2018. "Trends And Calendar Effects In Malaysia’S Stock Market," Romanian Economic Business Review, Romanian-American University, vol. 13(2), pages 15-22, June.
    6. Hendry, David F., 2001. "Achievements and challenges in econometric methodology," Journal of Econometrics, Elsevier, vol. 100(1), pages 7-10, January.
    7. Kunkel, Robert A. & Compton, William S. & Beyer, Scott, 2003. "The turn-of-the-month effect still lives: the international evidence," International Review of Financial Analysis, Elsevier, vol. 12(2), pages 207-221.
    8. Philip Kostov & Seamus McErlean, 2004. "Estimating the probability of large negative stock market," Finance 0409011, University Library of Munich, Germany.
    9. Lee, Tae-Hwy & Saltoglu, Burak, 2002. "Assessing the risk forecasts for Japanese stock market," Japan and the World Economy, Elsevier, vol. 14(1), pages 63-85, January.

  52. Blake, David & Lehmann, Bruce N & Timmermann, Allan G, 1997. "Performance Measurement using Multiple Asset Class Portfolio Data," CEPR Discussion Papers 1618, C.E.P.R. Discussion Papers.

    Cited by:

    1. Whitehouse, Edward, 2000. "Pension reform, financial literacy and public information : a case study of the United Kingdom," Social Protection Discussion Papers and Notes 21312, The World Bank.
    2. Whitehouse, Edward, 2000. "Administrative charges for funded pensions : an international comparison and assessment," Social Protection Discussion Papers and Notes 23140, The World Bank.
    3. Whitehouse, Edward, 2000. "Paying for pensions: An international comparison of administrative charges in funded retirement-income systems," MPRA Paper 14171, University Library of Munich, Germany.
    4. Claudio Borio & Craig Furfine & Philip Lowe, 2001. "Procyclicality of the financial system and financial stability: issues and policy options," BIS Papers chapters, in: Bank for International Settlements (ed.), Marrying the macro- and micro-prudential dimensions of financial stability, volume 1, pages 1-57, Bank for International Settlements.
    5. Srinivas, P.S. & Whitehouse, Edward & Yermo, Juan, 2000. "Regulating private pension funds’ structure, performance and investments: cross-country evidence," MPRA Paper 14753, University Library of Munich, Germany.
    6. Manuel Ammann & Andreas Zingg, 2008. "Investment Performance of Swiss Pension Funds and Investment Foundations," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 144(II), pages 153-195, June.

  53. Pesaran, M. H. & Timmermann, A., 1996. "A Recursive Modelling Approach to Predicting UK Stock Returns'," Cambridge Working Papers in Economics 9625, Faculty of Economics, University of Cambridge.

    Cited by:

    1. 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.
    2. Alan Gregory, 2011. "The Expected Cost of Equity and the Expected Risk Premium in the UK," Review of Behavioral Finance, Emerald Group Publishing Limited, vol. 3(1), pages 1-26, April.
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    4. Groenewold, Nicolaas & Kan Tang, Sam Hak & Wu, Yanrui, 2008. "The profitability of regression-based trading rules for the Shanghai stock market," International Review of Financial Analysis, Elsevier, vol. 17(2), pages 411-430.
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    1. Carl Chiarella & Xue-Zhong He & Cars Hommes, 2004. "A Dynamic Analysis of Moving Average Rules," Research Paper Series 133, Quantitative Finance Research Centre, University of Technology, Sydney.
    2. M. Hashem Pesaran & Simon M. Potter, 1993. "Equilibrium Asset Pricing Models and Predictability of Excess Returns," UCLA Economics Working Papers 694, UCLA Department of Economics.
    3. Granger, C.W.J. & Pesaran, M. H., 1999. "Economic and Statistical Measures of Forecast Accuracy," Cambridge Working Papers in Economics 9910, Faculty of Economics, University of Cambridge.
    4. Stephen E. Satchell & Shaun A. Bond, 2004. "Asymmetry, Loss Aversion and Forecasting," Econometric Society 2004 Australasian Meetings 160, Econometric Society.

  56. Pesaran, M.H. & Timmermann, A., 1990. "A Simple, Non-Parametric Test Of Predictive Performance," Cambridge Working Papers in Economics 9021, Faculty of Economics, University of Cambridge.

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    Cited by:

    1. Shiyi Chen & Kiho Jeong & Wolfgang K. Härdle, 2008. "Recurrent Support Vector Regression for a Nonlinear ARMA Model with Applications to Forecasting Financial Returns," SFB 649 Discussion Papers SFB649DP2008-051, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

Articles

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    4. Andrew Ang & Allan Timmermann, 2011. "Regime Changes and Financial Markets," NBER Working Papers 17182, National Bureau of Economic Research, Inc.
    5. Chiang, Thomas C., 2019. "Empirical analysis of intertemporal relations between downside risks and expected returns—Evidence from Asian markets," Research in International Business and Finance, Elsevier, vol. 47(C), pages 264-278.
    6. Avdis, Efstathios & Wachter, Jessica A., 2017. "Maximum likelihood estimation of the equity premium," Journal of Financial Economics, Elsevier, vol. 125(3), pages 589-609.
    7. 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.
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  2. Pesaran, M. Hashem & Pick, Andreas & Timmermann, Allan, 2011. "Variable selection, estimation and inference for multi-period forecasting problems," Journal of Econometrics, Elsevier, vol. 164(1), pages 173-187, September.

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    1. Leonardo Nogueira Ferreira & Silvia Miranda-Agrippino & Giovanni Ricco, 2023. "Bayesian Local Projections," Working Papers Series 581, Central Bank of Brazil, Research Department.
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    4. Ricco, Giovanni & Miranda-Agrippino, Silvia, 2018. "The Transmission of Monetary Policy Shocks," CEPR Discussion Papers 13396, C.E.P.R. Discussion Papers.
    5. Marcellino, Massimiliano & Kapetanios, George & Dendramis, Yiannis, 2020. "A Similarity-based Approach for Macroeconomic Forecasting," CEPR Discussion Papers 14469, C.E.P.R. Discussion Papers.
    6. Hännikäinen, Jari, 2014. "Multi-step forecasting in the presence of breaks," MPRA Paper 55816, University Library of Munich, Germany.
    7. 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.
    8. Carriero, Andrea & Kapetanios, George & Marcellino, Massimiliano, 2012. "Forecasting government bond yields with large Bayesian vector autoregressions," Journal of Banking & Finance, Elsevier, vol. 36(7), pages 2026-2047.
    9. Hou, Linke & Lv, Yuxia & Geng, Hao & Li, Feiyue, 2019. "To tell the truth or the perceived truth: Structural estimation of peer effects in China’s macroeconomic forecast," Economic Systems, Elsevier, vol. 43(2), pages 1-1.
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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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    32. Boriss Siliverstovs & Daniel S. Wochner, 2021. "State‐dependent evaluation of predictive ability," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(3), pages 547-574, April.
    33. Tanya Araujo & João Dias & Samuel Eleutério & Francisco Louçã, 2012. "How Fama Went Wrong: Measures of Multivariate Kurtosis for the Identification of the Dynamics of a N-Dimensional Market," Working Papers Department of Economics 2012/21, ISEG - Lisbon School of Economics and Management, Department of Economics, Universidade de Lisboa.
    34. International Monetary Fund, 2012. "Short-Term Wholesale Funding and Systemic Risk: A Global Covar Approach," IMF Working Papers 2012/046, International Monetary Fund.
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    36. Mikkel Plagborg-Møller & Christian K. Wolf, 2020. "Local Projections and VARs Estimate the Same Impulse Responses," Working Papers 2020-16, Princeton University. Economics Department..
    37. 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.
    38. Tanya Ara'ujo & Jo~ao Dias & Samuel Eleut'erio & Francisco Louc{c}~a, 2012. "How Fama Went Wrong: Measures of Multivariate Kurtosis for the Identification of the Dynamics of a N-Dimensional Market," Papers 1207.1202, arXiv.org.
    39. Caldeira, João F. & Moura, Guilherme V. & Santos, André A.P., 2016. "Predicting the yield curve using forecast combinations," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 79-98.
    40. Chevillon, Guillaume, 2016. "Multistep forecasting in the presence of location shifts," International Journal of Forecasting, Elsevier, vol. 32(1), pages 121-137.
    41. Germán López-Espinosa & Antonio Moreno & Antonio Rubia & Laura Valderrama, 2012. "Short-term Wholesale Funding and Systemic Risk: A Global CoVaR Approach," Faculty Working Papers 02/12, School of Economics and Business Administration, University of Navarra.
    42. Ng, Serena, 2013. "Variable Selection in Predictive Regressions," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 752-789, Elsevier.
    43. Xu Cheng & Bruce E. Hansen, 2012. "Forecasting with Factor-Augmented Regression: A Frequentist Model Averaging Approach, Second Version," PIER Working Paper Archive 13-061, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 03 Sep 2013.
    44. Pesaran, M.H. & Pick, A. & Pranovich, M., 2011. "Optimal Forecasts in the Presence of Structural Breaks (Updated 14 November 2011)," Cambridge Working Papers in Economics 1163, Faculty of Economics, University of Cambridge.
    45. Ryan R. Brady, 2021. "Direct Forecasting for Applied Regional Analysis," Departmental Working Papers 67, United States Naval Academy Department of Economics.
    46. Venditti, Fabrizio, 2013. "From oil to consumer energy prices: How much asymmetry along the way?," Energy Economics, Elsevier, vol. 40(C), pages 468-473.
    47. Heaton, Chris, 2015. "Testing for multiple-period predictability between serially dependent time series," International Journal of Forecasting, Elsevier, vol. 31(3), pages 587-597.
    48. Boot, Tom & Pick, Andreas, 2020. "Does modeling a structural break improve forecast accuracy?," Journal of Econometrics, Elsevier, vol. 215(1), pages 35-59.

  3. Issler, João Victor & Linton, Oliver & Timmermann, Allan, 2011. "Annals issue on forecasting--Guest editors' introduction," Journal of Econometrics, Elsevier, vol. 164(1), pages 1-3, September.

    Cited by:

    1. Mikkel Plagborg-Møller & Christian K. Wolf, 2020. "Local Projections and VARs Estimate the Same Impulse Responses," Working Papers 2020-16, Princeton University. Economics Department..

  4. Patton, Andrew J. & Timmermann, Allan, 2011. "Predictability of Output Growth and Inflation: A Multi-Horizon Survey Approach," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(3), pages 397-410.

    Cited by:

    1. Kajal Lahiri & Huaming Peng & Xuguang Simon Sheng, 2021. "Measuring Uncertainty of a Combined Forecast and Some Tests for Forecaster Heterogeneity," Working Papers 2021-005, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    2. Hecq, Alain & Jacobs, Jan P.A.M. & Stamatogiannis, Michalis P., 2019. "Testing for news and noise in non-stationary time series subject to multiple historical revisions," Journal of Macroeconomics, Elsevier, vol. 60(C), pages 396-407.
    3. Marcela De Castro-Valderrama & Santiago Forero-Alvarado & Nicolás Moreno-Arias & Sara Naranjo-Saldarriaga, 2021. "Unraveling the Exogenous Forces Behind Analysts’ Macroeconomic Forecasts," Borradores de Economia 1184, Banco de la Republica de Colombia.
    4. William A. Branch, 2014. "Nowcasting and the Taylor Rule," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 46(5), pages 1035-1055, August.
    5. Joscha Beckmann & Robert L. Czudaj, 2022. "Fundamental determinants of exchange rate expectations," Chemnitz Economic Papers 056, Department of Economics, Chemnitz University of Technology, revised Mar 2022.
    6. Joscha Beckmann & Robert L. Czudaj, 2018. "Monetary Policy Shocks, Expectations, And Information Rigidities," Economic Inquiry, Western Economic Association International, vol. 56(4), pages 2158-2176, October.
    7. Feunou Bruno & Fontaine Jean-Sébastien & Jin Jianjian, 2021. "What model for the target rate," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(1), pages 1-23, February.
    8. Andrea Carriero & Galvao, Ana Beatriz & Kapetanios, George, 2016. "A comprehensive evaluation of macroeconomic forecasting methods," EMF Research Papers 10, Economic Modelling and Forecasting Group.
    9. Clements, Michael P., 2012. "Subjective and Ex Post Forecast Uncertainty: US Inflation and Output Growth," Economic Research Papers 270629, University of Warwick - Department of Economics.
    10. Joscha Beckmann & Robert L. Czudaj, 2023. "The role of expectations for currency crisis dynamics—The case of the Turkish lira," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(3), pages 625-642, April.
    11. Timmermann, Allan & Patton, Andrew, 2011. "Forecast Rationality Tests Based on Multi-Horizon Bounds," CEPR Discussion Papers 8194, C.E.P.R. Discussion Papers.
    12. Michael P. Clements, 2020. "Individual Forecaster Perceptions of the Persistence of Shocks to GDP," ICMA Centre Discussion Papers in Finance icma-dp2020-02, Henley Business School, University of Reading.
    13. Timmermann, Allan & Zhu, Yinchu, 2019. "Comparing Forecasting Performance with Panel Data," CEPR Discussion Papers 13746, C.E.P.R. Discussion Papers.
    14. 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.
    15. Czudaj, Robert L., 2020. "Is the negative interest rate policy effective?," Journal of Economic Behavior & Organization, Elsevier, vol. 174(C), pages 75-86.
    16. Michael P Clements, 2014. "Assessing the Evidence of Macro- Forecaster Herding: Forecasts of Inflation and Output Growth," ICMA Centre Discussion Papers in Finance icma-dp2014-12, Henley Business School, University of Reading.
    17. Busetto, Filippo, 2024. "Asymmetric expectations of monetary policy," Bank of England working papers 1058, Bank of England.
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    3. Soojin Jo & Rodrigo Sekkel, 2019. "Macroeconomic Uncertainty Through the Lens of Professional Forecasters," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(3), pages 436-446, July.
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    128. Monica Jain, 2013. "Perceived Inflation Persistence," Staff Working Papers 13-43, Bank of Canada.
    129. Junichi Kikuchi & Yoshiyuki Nakazono, 2023. "The Formation of Inflation Expectations: Microdata Evidence from Japan," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 55(6), pages 1609-1632, September.
    130. Wang, Yiyao & Lee, Tae-Hwy, 2014. "Asymmetric loss in the Greenbook and the Survey of Professional Forecasters," International Journal of Forecasting, Elsevier, vol. 30(2), pages 235-245.
    131. James M. Nason & Gregor W. Smith, 2013. "Reverse Kalman filtering U.S. inflation with sticky professional forecasts," Working Papers 13-34, Federal Reserve Bank of Philadelphia.
    132. Stefano Eusepi & Richard Crump & Emanuel Moench & Philippe Andrade, 2014. "Noisy Information and Fundamental Disagreement," 2014 Meeting Papers 797, Society for Economic Dynamics.
    133. Karlyn Mitchell & Douglas K. Pearce, 2017. "Direct Evidence on Sticky Information from the Revision Behavior of Professional Forecasters," Southern Economic Journal, John Wiley & Sons, vol. 84(2), pages 637-653, October.
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    135. Michael P. Clements, 2020. "Do Survey Joiners and Leavers Differ from Regular Participants? The US SPF GDP Growth and Inflation Forecasts," ICMA Centre Discussion Papers in Finance icma-dp2020-01, Henley Business School, University of Reading.
    136. Dovern, Jonas, 2015. "A multivariate analysis of forecast disagreement: Confronting models of disagreement with survey data," European Economic Review, Elsevier, vol. 80(C), pages 16-35.
    137. Alessandro Barbera & Dora Xia & Sonya Zhu, 2023. "The term structure of inflation forecasts disagreement and monetary policy transmission," BIS Working Papers 1114, Bank for International Settlements.
    138. Carola Binder & Wesley Janson & Randal Verbrugge, 2023. "Out of Bounds: Do SPF Respondents Have Anchored Inflation Expectations?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 55(2-3), pages 559-576, March.
    139. Gabriel Caldas Montes & Igor Mendes Marcelino, 2023. "Uncertainties and disagreements in expectations of professional forecasters: Evidence from an inflation targeting developing country," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 937-956, July.
    140. Gaurav Kumar Singh & Tathagata Bandyopadhyay, 2024. "Determinants of disagreement: Learning from inflation expectations survey of households," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 326-343, March.
    141. Paloviita, Maritta & Virén, Matti, 2014. "Analysis of forecast errors in micro-level survey data," Bank of Finland Research Discussion Papers 8/2014, Bank of Finland.
    142. Baetje, Fabian & Friedrici, Karola, 2016. "Does cross-sectional forecast dispersion proxy for macroeconomic uncertainty? New empirical evidence," Economics Letters, Elsevier, vol. 143(C), pages 38-43.
    143. Krüger, Fabian & Nolte, Ingmar, 2016. "Disagreement versus uncertainty: Evidence from distribution forecasts," Journal of Banking & Finance, Elsevier, vol. 72(S), pages 172-186.
    144. Li, You & Tay, Anthony, 2021. "The role of macroeconomic and policy uncertainty in density forecast dispersion," Journal of Macroeconomics, Elsevier, vol. 67(C).
    145. Breitung, Jörg & Schmeling, Maik, 2011. "Quantifying survey expectations: What's wrong with the probability approach?," Hannover Economic Papers (HEP) dp-485, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    146. Toshitaka Sekine & Frank Packer & Shunichi Yoneyama, 2022. "Individual Trend Inflation," Working Papers on Central Bank Communication 042, University of Tokyo, Graduate School of Economics.
    147. Pohl, Walter & Schmedders, Karl & Wilms, Ole, 2021. "Asset pricing with heterogeneous agents and long-run risk," Journal of Financial Economics, Elsevier, vol. 140(3), pages 941-964.
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    Cited by:

    1. Ruenzi, Stefan & Ungeheuer, Michael & Weigert, Florian, 2020. "Joint extreme events in equity returns and liquidity and their cross-sectional pricing implications," CFR Working Papers 20-01, University of Cologne, Centre for Financial Research (CFR).
    2. Klein, Tobias & Salm, Martin & Upadhyay, Suraj, 2020. "The Response to Dynamic Incentives in Insurance Contracts with a Deductible: Evidence from a Differences-in-Regression-Disconti," CEPR Discussion Papers 14552, C.E.P.R. Discussion Papers.
    3. Ruenzi, Stefan & Ungeheuer, Michael & Weigert, Florian, 2013. "Extreme Downside Liquidity Risk," Working Papers on Finance 1326, University of St. Gallen, School of Finance, revised Jul 2015.
    4. Brendan K. Beare & Lawrence D. W. Schmidt, 2016. "An Empirical Test of Pricing Kernel Monotonicity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(2), pages 338-356, March.
    5. Christian Fieberg & Lars Hornuf & Gerrit Liedtke & Thorsten Poddig, 2020. "Are Characteristics Covariances? A Comment on Instrumented Principal Component Analysis," CESifo Working Paper Series 8377, CESifo.
    6. Zaremba, Adam & Bilgin, Mehmet Huseyin & Long, Huaigang & Mercik, Aleksander & Szczygielski, Jan J., 2021. "Up or down? Short-term reversal, momentum, and liquidity effects in cryptocurrency markets," International Review of Financial Analysis, Elsevier, vol. 78(C).
    7. Jose Renato Haas Ornelas & Antonio Francisco de Almeida Silva Jr, 2014. "Testing the Liquidity Preference Hypothesis using Survey Forecasts," Working Papers Series 353, Central Bank of Brazil, Research Department.
    8. Wan-Ni Lai & Yi-Ting Chen & Edward W. Sun, 2021. "Comonotonicity and low volatility effect," Annals of Operations Research, Springer, vol. 299(1), pages 1057-1099, April.
    9. Russell Davidson & Niels S. Grønborg, 2018. "Time-varying parameters: New test tailored to applications in finance and macroeconomics," CREATES Research Papers 2018-22, Department of Economics and Business Economics, Aarhus University.
    10. Stereńczak, Szymon & Zaremba, Adam & Umar, Zaghum, 2020. "Is there an illiquidity premium in frontier markets?," Emerging Markets Review, Elsevier, vol. 42(C).
    11. José Renato Haas Ornelas, 2014. "Assessing the Forecast Ability of Risk-Neutral Densities and Real-World Densities from Emerging Markets Currencies," Working Papers Series 370, Central Bank of Brazil, Research Department.
    12. Martijn Boons & Frans de Roon & Fernando M. Duarte & Marta Szymanowska, 2013. "Time-Varying Inflation Risk and Stock Returns," Staff Reports 621, Federal Reserve Bank of New York.
    13. Bertrand Groslambert & Wan-Ni Lai, 2020. "Ranking tail risk across international stock markets," Economics Bulletin, AccessEcon, vol. 40(2), pages 1756-1768.
    14. Söderlind, Paul & Dahlquist, Magnus & Martinez, José Vicente, 2012. "Individual Investor Activity and Performance," CEPR Discussion Papers 8744, C.E.P.R. Discussion Papers.
    15. Adam Zaremba, 2019. "The Cross Section of Country Equity Returns: A Review of Empirical Literature," JRFM, MDPI, vol. 12(4), pages 1-26, October.
    16. Xyngis, Georgios, 2017. "Business-cycle variation in macroeconomic uncertainty and the cross-section of expected returns: Evidence for scale-dependent risks," Journal of Empirical Finance, Elsevier, vol. 44(C), pages 43-65.
    17. Liu, Yan, 2021. "Index option returns and generalized entropy bounds," Journal of Financial Economics, Elsevier, vol. 139(3), pages 1015-1036.
    18. Hendershott, Terrence & Livdan, Dmitry & Rösch, Dominik, 2020. "Asset pricing: A tale of night and day," Journal of Financial Economics, Elsevier, vol. 138(3), pages 635-662.
    19. Bakshi, Gurdip & Chabi-Yo, Fousseni, 2011. "Variance Bounds on the Permanent and Transitory Components of Stochastic Discount Factors," Working Paper Series 2011-11, Ohio State University, Charles A. Dice Center for Research in Financial Economics.
    20. Bartram, Söhnke & Djuranovik, Leslie & Garratt, Anthony, 2021. "Currency Anomalies," CEPR Discussion Papers 15653, C.E.P.R. Discussion Papers.
    21. Cao, Ying & von Reibnitz, Anna & Warren, Geoffrey J., 2020. "Return dispersion and fund performance: Australia – The land of opportunity?," Pacific-Basin Finance Journal, Elsevier, vol. 60(C).
    22. Timmermann, Allan & Patton, Andrew, 2011. "Forecast Rationality Tests Based on Multi-Horizon Bounds," CEPR Discussion Papers 8194, C.E.P.R. Discussion Papers.
    23. Nguyen, Duc Binh Benno & Prokopczuk, Marcel & Wese Simen, Chardin, 2017. "International Tail Risk and World Fear," Hannover Economic Papers (HEP) dp-620, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    24. Zaremba, Adam & Long, Huaigang & Karathanasopoulos, Andreas, 2019. "Short-term momentum (almost) everywhere," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 63(C).
    25. Pätäri, Eero & Karell, Ville & Luukka, Pasi & Yeomans, Julian S, 2018. "Comparison of the multicriteria decision-making methods for equity portfolio selection: The U.S. evidence," European Journal of Operational Research, Elsevier, vol. 265(2), pages 655-672.
    26. De Rossi, Giuliano & Steliaros, Michael, 2022. "The Shift from Active to Passive and its Effect on Intraday Stock Dynamics," Journal of Banking & Finance, Elsevier, vol. 143(C).
    27. Pätäri, Eero & Ahmed, Sheraz & Luukka, Pasi & Yeomans, Julian Scott, 2023. "Can monthly-return rank order reveal a hidden dimension of momentum? The post-cost evidence from the U.S. stock markets," The North American Journal of Economics and Finance, Elsevier, vol. 65(C).
    28. Aytek Malkhozov & Philippe Mueller & Andrea Vedolin & Gyuri Venter, 2015. "Mortgage risk and the yield curve," BIS Working Papers 532, Bank for International Settlements.
    29. Sha Wang & Jean-Philippe Vergne, 2017. "Buzz Factor or Innovation Potential: What Explains Cryptocurrencies’ Returns?," PLOS ONE, Public Library of Science, vol. 12(1), pages 1-17, January.
    30. Matias D. Cattaneo & Richard K. Crump & Max H. Farrell & Ernst Schaumburg, 2020. "Characteristic-Sorted Portfolios: Estimation and Inference," The Review of Economics and Statistics, MIT Press, vol. 102(3), pages 531-551, July.
    31. He, Chaohua & Jiang, Cheng & Molyboga, Marat, 2019. "Risk premia in Chinese commodity markets," Journal of Commodity Markets, Elsevier, vol. 15(C), pages 1-1.
    32. Don M. Autore & Jared R. DeLisle, 2016. "Skewness Preference and Seasoned Equity Offers," The Review of Corporate Finance Studies, Society for Financial Studies, vol. 5(2), pages 200-238.
    33. Chetverikov, Denis & Wilhelm, Daniel & Kim, Dongwoo, 2021. "An Adaptive Test Of Stochastic Monotonicity," Econometric Theory, Cambridge University Press, vol. 37(3), pages 495-536, June.
    34. Xiang, Ju & Zhu, Xiaoneng, 2014. "Intraday asymmetric liquidity and asymmetric volatility in FTSE-100 futures market," Journal of Empirical Finance, Elsevier, vol. 25(C), pages 134-148.
    35. Weber, Martin & Ungeheuer, Michael, 2016. "The Perception of Dependence, Investment Decisions, and Stock Prices," CEPR Discussion Papers 11585, C.E.P.R. Discussion Papers.
    36. Kazuhiro Hiraki & George Skiadopoulos, 2023. "The Contribution of Transaction Costs to Expected Stock Returns: A Novel Measure," Working Papers 946, Queen Mary University of London, School of Economics and Finance.
    37. Zaremba, Adam & Bianchi, Robert J. & Mikutowski, Mateusz, 2021. "Long-run reversal in commodity returns: Insights from seven centuries of evidence," Journal of Banking & Finance, Elsevier, vol. 133(C).
    38. Adam Zaremba, 2016. "Has the Long-Term Reversal Reversed? Evidence from Country Equity Indices," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 88-103, March.
    39. Malamud, Semyon & Vilkov, Grigory, 2018. "Non-myopic betas," Journal of Financial Economics, Elsevier, vol. 129(2), pages 357-381.
    40. Timmermann, Allan & Lunde, Asger & Groenborg, Niels & Wermers, Russ, 2017. "Picking Funds with Confidence," CEPR Discussion Papers 11896, C.E.P.R. Discussion Papers.
    41. Joenväärä, Juha & Kosowski, Robert & Tolonen, Pekka, 2019. "The Effect of Investment Constraints on Hedge Fund Investor Returns," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 54(4), pages 1539-1571, August.
    42. Terence Tai-Leung Chong & Sunny Chun Tsui & Wing Hong Chan, 2017. "Factor pricing in commodity futures and the role of liquidity," Quantitative Finance, Taylor & Francis Journals, vol. 17(11), pages 1745-1757, November.
    43. Zaremba, Adam & Kizys, Renatas & Raza, Muhammad Wajid, 2020. "The long-run reversal in the long run: Insights from two centuries of international equity returns," Journal of Empirical Finance, Elsevier, vol. 55(C), pages 177-199.
    44. Artmann, Sabine & Finter, Philipp & Kempf, Alexander & Koch, Stefan & Theissen, Erik, 2010. "The cross-Section of German stock returns: New data and new evidence," CFR Working Papers 10-12, University of Cologne, Centre for Financial Research (CFR).
    45. Patton, Andrew J. & Weller, Brian M., 2020. "What you see is not what you get: The costs of trading market anomalies," Journal of Financial Economics, Elsevier, vol. 137(2), pages 515-549.
    46. Richard D. F. Harris & Xuguang Li & Fang Qiao, 2019. "Option‐implied betas and the cross section of stock returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(1), pages 94-108, January.
    47. David M. Kaplan & Longhao Zhuo, 2018. "Frequentist size of Bayesian inequality tests," Working Papers 1802, Department of Economics, University of Missouri, revised 14 Jul 2019.
    48. Huang, Huichou & MacDonald, Ronald & Zhao, Yang, 2012. "Global Currency Misalignments, Crash Sensitivity, and Downside Insurance Costs," MPRA Paper 53745, University Library of Munich, Germany, revised 18 Nov 2013.
    49. Zaremba, Adam & Czapkiewicz, Anna, 2017. "The cross section of international government bond returns," Economic Modelling, Elsevier, vol. 66(C), pages 171-183.
    50. Klein, Tobias J. & Salm, Martin & Upadhyay, Suraj, 2020. "The Response to Dynamic Incentives in Insurance Contracts with a Deductible: Evidence from a Differences-in-Regression-Discontinuities Design," IZA Discussion Papers 13108, Institute of Labor Economics (IZA).
    51. Horatio Cuesdeanu & Jens Carsten Jackwerth, 2018. "The pricing kernel puzzle: survey and outlook," Annals of Finance, Springer, vol. 14(3), pages 289-329, August.
    52. Zaremba, Adam & Mikutowski, Mateusz & Szczygielski, Jan Jakub & Karathanasopoulos, Andreas, 2021. "The alpha momentum effect in commodity markets," Energy Economics, Elsevier, vol. 93(C).
    53. Ornelas, José Renato Haas, 2016. "The Forecast Ability of Option-implied Densities from Emerging Markets Currencies," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 36(1), March.
    54. Koerniadi, Hardjo & Krishnamurti, Chandrasekhar & Lau, Sie Ting & Tourani-Rad, Alireza & Yang, Ting, 2015. "The role of internal and external certification mechanisms in seasoned equity offerings," Journal of Multinational Financial Management, Elsevier, vol. 30(C), pages 110-127.
    55. Kharrat, Sabrine & Hammami, Yacine & Fatnassi, Ibrahim, 2020. "On the cross-sectional relation between exchange rates and future fundamentals," Economic Modelling, Elsevier, vol. 89(C), pages 484-501.
    56. Romano, Joseph P. & Wolf, Michael, 2013. "Testing for monotonicity in expected asset returns," Journal of Empirical Finance, Elsevier, vol. 23(C), pages 93-116.
    57. Zaremba, Adam & Cakici, Nusret & Bianchi, Robert J. & Long, Huaigang, 2023. "Interest rate changes and the cross-section of global equity returns," Journal of Economic Dynamics and Control, Elsevier, vol. 147(C).
    58. Wan-Ni Lai & Claire Y. T. Chen & Edward W. Sun, 2022. "Risk factor extraction with quantile regression method," Annals of Operations Research, Springer, vol. 316(2), pages 1543-1572, September.
    59. Sullivan, Michael & Zhang, Andrew (Jianzhong), 2011. "Are investment and financing anomalies two sides of the same coin?," Journal of Empirical Finance, Elsevier, vol. 18(4), pages 616-633, September.
    60. Roh, Tai-Yong & Lee, Changjun & Min, Byoung-Kyu, 2019. "Consumption growth predictability and asset prices," Journal of Empirical Finance, Elsevier, vol. 51(C), pages 95-118.
    61. Zaremba, Adam & Karathanasopoulos, Andreas & Maydybura, Alina & Czapkiewicz, Anna & Bagheri, Noushin, 2020. "Dissecting anomalies in Islamic stocks: Integrated or segmented pricing?," Pacific-Basin Finance Journal, Elsevier, vol. 62(C).
    62. Sarno, Lucio & Schmeling, Maik, 2013. "Which Fundamentals Drive Exchange Rates? A Cross-Sectional Perspective," CEPR Discussion Papers 9472, C.E.P.R. Discussion Papers.
    63. Lin, Qi, 2018. "Technical analysis and stock return predictability: An aligned approach," Journal of Financial Markets, Elsevier, vol. 38(C), pages 103-123.
    64. Hoang, Khoa & Cannavan, Damien & Huang, Ronghong & Peng, Xiaowen, 2021. "Predicting stock returns with implied cost of capital: A partial least squares approach," Journal of Financial Markets, Elsevier, vol. 53(C).
    65. Fricke, Daniel, 2018. "Are specialist funds “special”?," LSE Research Online Documents on Economics 91335, London School of Economics and Political Science, LSE Library.
    66. Ahmed, Shamim & Valente, Giorgio, 2015. "Understanding the price of volatility risk in carry trades," Journal of Banking & Finance, Elsevier, vol. 57(C), pages 118-129.
    67. Zaremba, Adam & Umutlu, Mehmet & Karathanasopoulos, Andreas, 2019. "Alpha momentum and alpha reversal in country and industry equity indexes," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 144-161.
    68. Banegas, Ayelen & Gillen, Ben & Timmermann, Allan & Wermers, Russ, 2012. "The cross-section of conditional mutual fund performance in European stock markets," CFR Working Papers 09-03 [rev.], University of Cologne, Centre for Financial Research (CFR).
    69. Sebastian Müller & Martin Weber, 2014. "Evaluating the Rating of Stiftung Warentest: How Good Are Mutual Fund Ratings and Can They Be Improved?," European Financial Management, European Financial Management Association, vol. 20(2), pages 207-235, March.
    70. Berghaus, Betina & Bücher, Axel, 2014. "Nonparametric tests for tail monotonicity," Journal of Econometrics, Elsevier, vol. 180(2), pages 117-126.
    71. Dr. Thomas Nitschka, 2018. "Did China's anti-corruption campaign affect the risk premium on stocks of global luxury goods firms?," Working Papers 2018-09, Swiss National Bank.
    72. Ghysels, Eric & Liu, Hanwei & Raymond, Steve, 2021. "Institutional Investors and Granularity in Equity Markets," CEPR Discussion Papers 15654, C.E.P.R. Discussion Papers.
    73. Hoechle, Daniel & Schmid, Markus & Zimmermann, Heinz, 2017. "Does Unobservable Heterogeneity Matter for Portfolio-Based Asset Pricing Tests?," Working Papers on Finance 1717, University of St. Gallen, School of Finance, revised Mar 2020.
    74. Zaremba, Adam & Szyszka, Adam & Karathanasopoulos, Andreas & Mikutowski, Mateusz, 2021. "Herding for profits: Market breadth and the cross-section of global equity returns," Economic Modelling, Elsevier, vol. 97(C), pages 348-364.
    75. Klinkowska, Olga & Zhao, Yuan, 2023. "Fund flows and performance: New evidence from retail and institutional SRI mutual funds," International Review of Financial Analysis, Elsevier, vol. 87(C).
    76. Nuno Clara, 2018. "Demand Elasticities, Nominal Rigidities and Asset Prices," 2018 Meeting Papers 790, Society for Economic Dynamics.
    77. Vintilă Georgeta & Păunescu Radu Alin, 2015. "Econometric Tests of the CAPM Model for a Portfolio Composed of Companies Listed on Nasdaq and Dow Jones Components," Scientific Annals of Economics and Business, Sciendo, vol. 62(3), pages 453-480, November.
    78. Smith, Simon C. & Timmermann, Allan, 2022. "Have risk premia vanished?," Journal of Financial Economics, Elsevier, vol. 145(2), pages 553-576.
    79. Adam Zaremba, 2017. "Combining Equity Country Selection Strategies," Contemporary Economics, University of Economics and Human Sciences in Warsaw., vol. 11(1), March.
    80. Waszczuk, Antonina, 2013. "A risk-based explanation of return patterns—Evidence from the Polish stock market," Emerging Markets Review, Elsevier, vol. 15(C), pages 186-210.
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    87. Zaremba, Adam & Maydybura, Alina, 2019. "The cross-section of returns in frontier equity markets: Integrated or segmented pricing?," Emerging Markets Review, Elsevier, vol. 38(C), pages 219-238.

  8. Marco Aiolfi & Marius Rodriguez & Allan Timmermann, 2010. "Understanding Analysts' Earnings Expectations: Biases, Nonlinearities, and Predictability," Journal of Financial Econometrics, Oxford University Press, vol. 8(3), pages 305-334, Summer.
    See citations under working paper version above.
  9. Carlos Capistr¡N & 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.
    See citations under working paper version above.
  10. Capistrán, Carlos & Timmermann, Allan, 2009. "Forecast Combination With Entry and Exit of Experts," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 428-440.
    See citations under working paper version above.
  11. Pesaran, M. Hashem & Timmermann, Allan, 2009. "Testing Dependence Among Serially Correlated Multicategory Variables," Journal of the American Statistical Association, American Statistical Association, vol. 104(485), pages 325-337.
    See citations under working paper version above.
  12. Guidolin, Massimo & Timmermann, Allan, 2009. "Forecasts of US short-term interest rates: A flexible forecast combination approach," Journal of Econometrics, Elsevier, vol. 150(2), pages 297-311, June.
    See citations under working paper version above.
  13. Timmermann, Allan, 2008. "Reply to the discussion of Elusive Return Predictability," International Journal of Forecasting, Elsevier, vol. 24(1), pages 29-30.

    Cited by:

    1. Rossi, Barbara & Odendahl, Florens & Sekhposyan, Tatevik, 2020. "Comparing Forecast Performance with State Dependence," CEPR Discussion Papers 15217, C.E.P.R. Discussion Papers.
    2. 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.
    3. Florens Odendahl & Barbara Rossi & Tatevik Sekhposyan, 2021. "Evaluating Forecast Performance with State Dependence," Working Papers 1295, Barcelona School of Economics.
    4. 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.
    5. Nicolas S. Magner & Nicolás Hardy & Tiago Ferreira & Jaime F. Lavin, 2023. "“Agree to Disagree”: Forecasting Stock Market Implied Volatility Using Financial Report Tone Disagreement Analysis," Mathematics, MDPI, vol. 11(7), pages 1-16, March.
    6. Taylor, Mark & Hsu, Po-Hsuan & Wang, Zigan, 2020. "The Out-of-Sample Performance of Carry Trades," CEPR Discussion Papers 15052, C.E.P.R. Discussion Papers.
    7. Leland E. Farmer & Lawrence Schmidt & Allan Timmermann, 2023. "Pockets of Predictability," Journal of Finance, American Finance Association, vol. 78(3), pages 1279-1341, June.
    8. Leopoldo Catania & Anna Gloria Billé, 2016. "Dynamic Spatial Autoregressive Models with Autoregressive and Heteroskedastic Disturbances," CEIS Research Paper 375, Tor Vergata University, CEIS, revised 31 Mar 2016.
    9. Daniel Mantilla-García & Vijay Vaidyanathan, 2017. "Predicting stock returns in the presence of uncertain structural changes and sample noise," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 31(3), pages 357-391, August.
    10. Massimo Guidolin & Manuela Pedio & Milena Petrova, 2019. "The Predictability of Real Estate Excess Returns: An Out-of-Sample Economic Value Analysis," BAFFI CAREFIN Working Papers 19122, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    11. Massacci, Daniele, 2017. "Least squares estimation of large dimensional threshold factor models," Journal of Econometrics, Elsevier, vol. 197(1), pages 101-129.
    12. Thomadakis, Apostolos, 2016. "Do Combination Forecasts Outperform the Historical Average? Economic and Statistical Evidence," MPRA Paper 71589, University Library of Munich, Germany.
    13. Jean-Yves Pitarakis, 2017. "A Simple Approach for Diagnosing Instabilities in Predictive Regressions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(5), pages 851-874, October.
    14. Hammerschmid, Regina & Lohre, Harald, 2018. "Regime shifts and stock return predictability," International Review of Economics & Finance, Elsevier, vol. 56(C), pages 138-160.
    15. Yin, Anwen, 2020. "Equity premium prediction and optimal portfolio decision with Bagging," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    16. Harri Pönkä, 2017. "Predicting the direction of US stock markets using industry returns," Empirical Economics, Springer, vol. 52(4), pages 1451-1480, June.
    17. Sander, Magnus, 2018. "Market timing over the business cycle," Journal of Empirical Finance, Elsevier, vol. 46(C), pages 130-145.
    18. Shailesh Rana & William H. Bommer & G. Michael Phillips, 2020. "Predicting Returns for Growth and Value Stocks: A Forecast Assessment Approach Using Global Asset Pricing Models," International Journal of Economics and Financial Issues, Econjournals, vol. 10(4), pages 88-106.
    19. Marta Matyjaszek & Gregorio Fidalgo Valverde & Alicja Krzemień & Krzysztof Wodarski & Pedro Riesgo Fernández, 2020. "Optimizing Predictor Variables in Artificial Neural Networks When Forecasting Raw Material Prices for Energy Production," Energies, MDPI, vol. 13(8), pages 1-15, April.
    20. Guillaume Belly & Lukas Boeckelmann & Carlos Mateo Caicedo Graciano & Alberto Di Iorio & Klodiana Istrefi & Vasileios Siakoulis & Arthur Stalla‐Bourdillon, 2023. "Forecasting sovereign risk in the Euro area via machine learning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(3), pages 657-684, April.
    21. Çakmaklı, Cem & van Dijk, Dick, 2016. "Getting the most out of macroeconomic information for predicting excess stock returns," International Journal of Forecasting, Elsevier, vol. 32(3), pages 650-668.
    22. Taylor, Mark & Hsu, Po-Hsuan, 2014. "Forty Years, Thirty Currencies and 21,000 Trading Rules: A Large-scale, Data-Snooping Robust Analysis of Technical Trading in t," CEPR Discussion Papers 10018, C.E.P.R. Discussion Papers.
    23. I. Marta Miranda García & María‐Jesús Segovia‐Vargas & Usue Mori & José A. Lozano, 2023. "Early prediction of Ibex 35 movements," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(5), pages 1150-1166, August.
    24. Pincheira Brown, Pablo & Hardy, Nicolás, 2019. "Forecasting base metal prices with the Chilean exchange rate," Resources Policy, Elsevier, vol. 62(C), pages 256-281.
    25. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1203-1324, Elsevier.
    26. Georgiev, Iliyan & Harvey, David I. & Leybourne, Stephen J. & Taylor, A.M. Robert, 2018. "Testing for parameter instability in predictive regression models," Journal of Econometrics, Elsevier, vol. 204(1), pages 101-118.
    27. Harvey, David I & Leybourne, Stephen J & Sollis, Robert & Taylor, AM Robert, 2020. "Real-Time Detection of Regimes of Predictability in the U.S. Equity Premium," Essex Finance Centre Working Papers 27775, University of Essex, Essex Business School.
    28. McMillan, David G., 2019. "Predicting firm level stock returns: Implications for asset pricing and economic links," The British Accounting Review, Elsevier, vol. 51(4), pages 333-351.
    29. Afsaneh Bahrami & Abul Shamsuddin & Katherine Uylangco, 2018. "Out‐of‐sample stock return predictability in emerging markets," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(3), pages 727-750, September.
    30. Baetje, Fabian & Menkhoff, Lukas, 2016. "Equity premium prediction: Are economic and technical indicators unstable?," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1193-1207.
    31. Ellie Birbeck & Dave Cliff, 2018. "Using Stock Prices as Ground Truth in Sentiment Analysis to Generate Profitable Trading Signals," Papers 1811.02886, arXiv.org.
    32. Alexandru Todea & Andrei Rusu, 2014. "Liquidity, information and market efficiency: an intraday approach on a frontier stock market," Economics Bulletin, AccessEcon, vol. 34(4), pages 2303-2307.
    33. Nicolás Magner & Nicolás Hardy, 2022. "Cryptocurrency Forecasting: More Evidence of the Meese-Rogoff Puzzle," Mathematics, MDPI, vol. 10(13), pages 1-27, July.
    34. Yi-Chieh Wen & Bin Li, 2020. "Lagged country returns and international stock return predictability during business cycle recession periods," Applied Economics, Taylor & Francis Journals, vol. 52(46), pages 5005-5019, October.
    35. Barbara Rossi, 2019. "Forecasting in the presence of instabilities: How do we know whether models predict well and how to improve them," Economics Working Papers 1711, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2021.
    36. Andrew Detzel & Jack Strauss, 2018. "Combination Return Forecasts and Portfolio Allocation with the Cross-Section of Book-to-Market Ratios [Illiquidity and stock returns: cross-section and time-series effects]," Review of Finance, European Finance Association, vol. 22(5), pages 1949-1973.
    37. Paulo M.M. Rodrigues & Matei Demetrescu, 2019. "Testing for Episodic Predictability in Stock Returns," Working Papers w201906, Banco de Portugal, Economics and Research Department.
    38. Larry W. Taylor, 2009. "Penalized‐R2 Criteria For Model Selection," Manchester School, University of Manchester, vol. 77(6), pages 699-717, December.
    39. Bätje, Fabian & Menkhoff, Lukas, 2016. "Predicting the equity premium via its components," VfS Annual Conference 2016 (Augsburg): Demographic Change 145789, Verein für Socialpolitik / German Economic Association.
    40. Roberto Gómez‐Cram, 2022. "Late to Recessions: Stocks and the Business Cycle," Journal of Finance, American Finance Association, vol. 77(2), pages 923-966, April.
    41. Baltas, Nick & Karyampas, Dimitrios, 2018. "Forecasting the equity risk premium: The importance of regime-dependent evaluation," Journal of Financial Markets, Elsevier, vol. 38(C), pages 83-102.
    42. Cem Cakmakli & Dick van Dijk, 2010. "Getting the Most out of Macroeconomic Information for Predicting Stock Returns and Volatility," Tinbergen Institute Discussion Papers 10-115/4, Tinbergen Institute.
    43. David G. McMillan, 2017. "Stock return predictability: the role of inflation and threshold dynamics," International Review of Applied Economics, Taylor & Francis Journals, vol. 31(3), pages 357-375, May.
    44. Pincheira, Pablo & Hardy, Nicolas, 2021. "The Mean Squared Prediction Error Paradox," MPRA Paper 107403, University Library of Munich, Germany.
    45. Hsu, Po-Hsuan & Taylor, Mark P. & Wang, Zigan, 2016. "Technical trading: Is it still beating the foreign exchange market?," Journal of International Economics, Elsevier, vol. 102(C), pages 188-208.
    46. Tang, Chor Foon & Lai, Yew Wah & Ozturk, Ilhan, 2015. "How stable is the export-led growth hypothesis? Evidence from Asia's Four Little Dragons," Economic Modelling, Elsevier, vol. 44(C), pages 229-235.
    47. Maderitsch, R., 2015. "Information transmission between stock markets in Hong Kong, Europe and the US: New evidence on time- and state-dependence," Pacific-Basin Finance Journal, Elsevier, vol. 35(PA), pages 13-36.
    48. Giulia Dal Pra & Massimo Guidolin & Manuela Pedio & Fabiola Vasile, 2016. "Do Regimes in Excess Stock Return Predictability Create Economic Value? An Out-of-Sample Portfolio Analysis," BAFFI CAREFIN Working Papers 1637, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    49. Alexandridis, Antonios K. & Apergis, Iraklis & Panopoulou, Ekaterini & Voukelatos, Nikolaos, 2023. "Equity premium prediction: The role of information from the options market," Journal of Financial Markets, Elsevier, vol. 64(C).
    50. Jonathan Iworiso & Spyridon Vrontos, 2020. "On the directional predictability of equity premium using machine learning techniques," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 449-469, April.
    51. Nicolás Magner & Jaime F. Lavín & Mauricio A. Valle, 2022. "Modeling Synchronization Risk among Sustainable Exchange Trade Funds: A Statistical and Network Analysis Approach," Mathematics, MDPI, vol. 10(19), pages 1-30, October.
    52. Salah Abosedra & Chor Foon Tang, 2019. "Are exports a reliable source of economic growth in MENA countries? New evidence from the rolling Granger causality method," Empirical Economics, Springer, vol. 56(3), pages 831-841, March.
    53. Devpura, Neluka & Narayan, Paresh Kumar & Sharma, Susan Sunila, 2018. "Is stock return predictability time-varying?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 52(C), pages 152-172.
    54. Pincheira, Pablo & Hardy, Nicolas, 2018. "Forecasting Base Metal Prices with Commodity Currencies," MPRA Paper 83564, University Library of Munich, Germany.
    55. Pincheira, Pablo & Hardy, Nicolas, 2020. "The Mean Squared Prediction Error Paradox: A summary," MPRA Paper 105020, University Library of Munich, Germany.
    56. 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).
    57. Chor Foon Tang & Eu Chye Tan, 2017. "Re-visiting the Savings-Led Growth Hypothesis and Its Stability in East Asian Economies," International Economic Journal, Taylor & Francis Journals, vol. 31(3), pages 436-447, July.
    58. Jurdi, Doureige J., 2022. "Predicting the Australian equity risk premium," Pacific-Basin Finance Journal, Elsevier, vol. 71(C).
    59. 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.
    60. McMillan, David G., 2019. "Stock return predictability: Using the cyclical component of the price ratio," Research in International Business and Finance, Elsevier, vol. 48(C), pages 228-242.
    61. Chor Foon Tang & Salah Abosedra, 2016. "Tourism and growth in Lebanon: new evidence from bootstrap simulation and rolling causality approaches," Empirical Economics, Springer, vol. 50(2), pages 679-696, March.
    62. Anwen Yin, 2021. "Forecasting the Market Equity Premium: Does Nonlinearity Matter?," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 13(5), pages 1-9, May.
    63. Dai, Zhifeng & Kang, Jie & Wen, Fenghua, 2021. "Predicting stock returns: A risk measurement perspective," International Review of Financial Analysis, Elsevier, vol. 74(C).

  14. Graham Elliott & Ivana Komunjer & Allan Timmermann, 2008. "Biases in Macroeconomic Forecasts: Irrationality or Asymmetric Loss?," Journal of the European Economic Association, MIT Press, vol. 6(1), pages 122-157, March.
    See citations under working paper version above.
  15. Massimo Guidolin & Allan Timmermann, 2008. "Size and Value Anomalies under Regime Shifts," Journal of Financial Econometrics, Oxford University Press, vol. 6(1), pages 1-48, Winter.

    Cited by:

    1. Alexandros Kontonikas & Alexandros Kostakis, 2013. "On Monetary Policy and Stock Market Anomalies," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 40(7-8), pages 1009-1042, September.
    2. Argyropoulos, Christos & Candelon, Bertrand & Hasse, Jean-Baptiste & Panopoulou, Ekaterini, 2020. "Toward a macroprudential regulatory framework for mutual funds," LIDAM Discussion Papers LFIN 2020008, Université catholique de Louvain, Louvain Finance (LFIN).
    3. Andrew Ang & Allan Timmermann, 2011. "Regime Changes and Financial Markets," NBER Working Papers 17182, National Bureau of Economic Research, Inc.
    4. Jinjarak, Yothin, 2014. "Equity prices and financial globalization," International Review of Financial Analysis, Elsevier, vol. 33(C), pages 49-57.
    5. Massimo Guidolin & Giovanna Nicodano, 2007. "Managing international portfolios with small capitalization stocks," Working Papers 2007-030, Federal Reserve Bank of St. Louis.
    6. 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.
    7. Carol Alexander & Anca Dimitriu, 2005. "Detecting Switching Strategies in Equity Hedge Funds," ICMA Centre Discussion Papers in Finance icma-dp2005-07, Henley Business School, University of Reading.
    8. Chih-Nan Chen & Chien-Hsiu Lin, 2022. "Optimal carry trade portfolio choice under regime shifts," Review of Quantitative Finance and Accounting, Springer, vol. 59(2), pages 483-506, August.
    9. Carolina Fugazza & Massimo Guidolin & Giovanna Nicodano, 2010. "1/N and long run optimal portfolios: results for mixed asset menus," Working Papers 2010-003, Federal Reserve Bank of St. Louis.
    10. Pettenuzzo, Davide & Timmermann, Allan, 2011. "Predictability of stock returns and asset allocation under structural breaks," Journal of Econometrics, Elsevier, vol. 164(1), pages 60-78, September.
    11. Azamat Abdymomunov, 2013. "Regime-switching measure of systemic financial stress," Annals of Finance, Springer, vol. 9(3), pages 455-470, August.
    12. Campani, Carlos Heitor & Garcia, René & Lewin, Marcelo, 2021. "Optimal portfolio strategies in the presence of regimes in asset returns," Journal of Banking & Finance, Elsevier, vol. 123(C).
    13. 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.
    14. Carmine Trecroci, 2010. "Multifactors risk loadings and abnormal returns under uncertainty and learning," Working Papers 1011, University of Brescia, Department of Economics.
    15. Huseyin Gulen & Yuhang Xing & Lu Zhang, 2011. "Value versus Growth: Time‐Varying Expected Stock Returns," Financial Management, Financial Management Association International, vol. 40(2), pages 381-407, June.
    16. Massimo Guidolin & Federica Ria, 2011. "Regime shifts in mean-variance efficient frontiers: Some international evidence," Journal of Asset Management, Palgrave Macmillan, vol. 12(5), pages 322-349, November.
    17. Hwang, Soosung & Rubesam, Alexandre, 2013. "A behavioral explanation of the value anomaly based on time-varying return reversals," Journal of Banking & Finance, Elsevier, vol. 37(7), pages 2367-2377.
    18. Urga, Giovanni & Wang, Fa, 2022. "Estimation and inference for high dimensional factor model with regime switching," MPRA Paper 113172, University Library of Munich, Germany.
    19. González-Rivera, Gloria & Yoldas, Emre, 2012. "Autocontour-based evaluation of multivariate predictive densities," International Journal of Forecasting, Elsevier, vol. 28(2), pages 328-342.
    20. Dewandaru, Ginanjar & Masih, Rumi & Bacha, Obiyathulla I. & Masih, A. Mansur M., 2014. "The Role of Islamic Asset Classes in the Diversified Portfolios: Mean Variance Spanning Test," MPRA Paper 56857, University Library of Munich, Germany.
    21. Massimo Guidolin & Giovanna Nicodano, 2010. "Ex Post Portfolio Performance with Predictable Skewness and Kurtosis," Carlo Alberto Notebooks 191, Collegio Carlo Alberto.
    22. Shaw, Charles, 2018. "Regime-Switching And Levy Jump Dynamics In Option-Adjusted Spreads," MPRA Paper 94154, University Library of Munich, Germany, revised 27 May 2019.
    23. 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.
    24. Chung, San-Lin & Hung, Chi-Hsiou & Yeh, Chung-Ying, 2012. "When does investor sentiment predict stock returns?," Journal of Empirical Finance, Elsevier, vol. 19(2), pages 217-240.
    25. Turtle, H.J. & Zhang, Chengping, 2012. "Time-varying performance of international mutual funds," Journal of Empirical Finance, Elsevier, vol. 19(3), pages 334-348.
    26. Mendes, Fernando Henrique de Paula e Silva & Caldeira, João Frois & Moura, Guilherme Valle, 2018. "Evidence of Bull and Bear Markets in the Bovespa index: An application of Markovian regime-switching Models with Duration Dependence," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 38(1), May.
    27. Massimo Guidolin & Giovanna Nicodano, 2009. "Small caps in international equity portfolios: the effects of variance risk," Annals of Finance, Springer, vol. 5(1), pages 15-48, January.
    28. Guidolin, Massimo & Hyde, Stuart, 2012. "Can VAR models capture regime shifts in asset returns? A long-horizon strategic asset allocation perspective," Journal of Banking & Finance, Elsevier, vol. 36(3), pages 695-716.
    29. Francesco Chincoli & Massimo Guidolin, 2017. "Linear and nonlinear predictability in investment style factors: multivariate evidence," Journal of Asset Management, Palgrave Macmillan, vol. 18(6), pages 476-509, October.
    30. Lioui, Abraham & Tarelli, Andrea, 2020. "Factor Investing for the Long Run," Journal of Economic Dynamics and Control, Elsevier, vol. 117(C).
    31. Yoldas Emre, 2012. "Threshold Asymmetries in Equity Return Distributions: Statistical Tests and Investment Implications," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 16(5), pages 1-37, December.
    32. Erdemlioglu, Deniz & Joliet, Robert, 2019. "Long-term asset allocation, risk tolerance and market sentiment," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 62(C), pages 1-19.
    33. Elizabeth Fons & Paula Dawson & Jeffrey Yau & Xiao-jun Zeng & John Keane, 2019. "A novel dynamic asset allocation system using Feature Saliency Hidden Markov models for smart beta investing," Papers 1902.10849, arXiv.org.
    34. Urga, Giovanni & Wang, Fa, 2022. "Estimation and Inference for High Dimensional Factor Model with Regime Switching," MPRA Paper 117012, University Library of Munich, Germany, revised 10 Apr 2023.
    35. Massimo Guidolin, 2013. "Markov switching models in asset pricing research," Chapters, in: Adrian R. Bell & Chris Brooks & Marcel Prokopczuk (ed.), Handbook of Research Methods and Applications in Empirical Finance, chapter 1, pages 3-44, Edward Elgar Publishing.
    36. Carolina Fugazza & Massimo Guidolin & Giovanna Nicodano, 2015. "Equally Weighted vs. Long†Run Optimal Portfolios," European Financial Management, European Financial Management Association, vol. 21(4), pages 742-789, September.
    37. Nyberg, Henri, 2013. "Predicting bear and bull stock markets with dynamic binary time series models," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3351-3363.
    38. Jieting Chen & Yuichiro Kawaguchi, 2018. "Multi-Factor Asset-Pricing Models under Markov Regime Switches: Evidence from the Chinese Stock Market," IJFS, MDPI, vol. 6(2), pages 1-19, May.
    39. Klaus Grobys, 2012. "Active PortofolioManagement in the Presence of Regime Switching: What Are the Benefits of Defensive Asset Allocation Strategies If the Investor Faces Bear Markets?," 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. 4(1), pages 015-031, June.

  16. Graham Elliott & Allan Timmermann, 2008. "Economic Forecasting," Journal of Economic Literature, American Economic Association, vol. 46(1), pages 3-56, March.
    See citations under working paper version above.
  17. Timmermann, Allan, 2008. "Elusive return predictability," International Journal of Forecasting, Elsevier, vol. 24(1), pages 1-18.

    Cited by:

    1. Rossi, Barbara & Odendahl, Florens & Sekhposyan, Tatevik, 2020. "Comparing Forecast Performance with State Dependence," CEPR Discussion Papers 15217, C.E.P.R. Discussion Papers.
    2. Schrimpf, Andreas, 2008. "International Stock Return Predictability Under Model Uncertainty," ZEW Discussion Papers 08-048, ZEW - Leibniz Centre for European Economic Research.
    3. Poncela, Pilar & Ruiz Ortega, Esther, 2012. "More is not always better : back to the Kalman filter in dynamic factor models," DES - Working Papers. Statistics and Econometrics. WS ws122317, Universidad Carlos III de Madrid. Departamento de Estadística.
    4. 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.
    5. Florens Odendahl & Barbara Rossi & Tatevik Sekhposyan, 2021. "Evaluating Forecast Performance with State Dependence," Working Papers 1295, Barcelona School of Economics.
    6. 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.
    7. Nicolas S. Magner & Nicolás Hardy & Tiago Ferreira & Jaime F. Lavin, 2023. "“Agree to Disagree”: Forecasting Stock Market Implied Volatility Using Financial Report Tone Disagreement Analysis," Mathematics, MDPI, vol. 11(7), pages 1-16, March.
    8. 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.
    9. Taylor, Mark & Hsu, Po-Hsuan & Wang, Zigan, 2020. "The Out-of-Sample Performance of Carry Trades," CEPR Discussion Papers 15052, C.E.P.R. Discussion Papers.
    10. Leland E. Farmer & Lawrence Schmidt & Allan Timmermann, 2023. "Pockets of Predictability," Journal of Finance, American Finance Association, vol. 78(3), pages 1279-1341, June.
    11. Leopoldo Catania & Anna Gloria Billé, 2016. "Dynamic Spatial Autoregressive Models with Autoregressive and Heteroskedastic Disturbances," CEIS Research Paper 375, Tor Vergata University, CEIS, revised 31 Mar 2016.
    12. Daniel Mantilla-García & Vijay Vaidyanathan, 2017. "Predicting stock returns in the presence of uncertain structural changes and sample noise," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 31(3), pages 357-391, August.
    13. Massimo Guidolin & Stuart Hyde & David McMillan & Sadayuki Ono, 2010. "Does the macroeconomy predict U.K. asset returns in a nonlinear fashion? comprehensive out-of-sample evidence," Working Papers 2010-039, Federal Reserve Bank of St. Louis.
    14. Massimo Guidolin & Manuela Pedio & Milena Petrova, 2019. "The Predictability of Real Estate Excess Returns: An Out-of-Sample Economic Value Analysis," BAFFI CAREFIN Working Papers 19122, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    15. Massacci, Daniele, 2017. "Least squares estimation of large dimensional threshold factor models," Journal of Econometrics, Elsevier, vol. 197(1), pages 101-129.
    16. Thomadakis, Apostolos, 2016. "Do Combination Forecasts Outperform the Historical Average? Economic and Statistical Evidence," MPRA Paper 71589, University Library of Munich, Germany.
    17. Jean-Yves Pitarakis, 2017. "A Simple Approach for Diagnosing Instabilities in Predictive Regressions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(5), pages 851-874, October.
    18. Hammerschmid, Regina & Lohre, Harald, 2018. "Regime shifts and stock return predictability," International Review of Economics & Finance, Elsevier, vol. 56(C), pages 138-160.
    19. Yin, Anwen, 2020. "Equity premium prediction and optimal portfolio decision with Bagging," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    20. Harri Pönkä, 2017. "Predicting the direction of US stock markets using industry returns," Empirical Economics, Springer, vol. 52(4), pages 1451-1480, June.
    21. Gonzalo, Jesus & Pitarakis, Jean-Yves, 2010. "Regime Specific Predictability in Predictive Regressions," MPRA Paper 29190, University Library of Munich, Germany.
    22. Erik Hillebrand & Tae-Hwy Lee & Marcelo Cunha Medeiros, 2012. "Let´s do it again: bagging equity premium predictors," Textos para discussão 604, Department of Economics PUC-Rio (Brazil).
    23. Sander, Magnus, 2018. "Market timing over the business cycle," Journal of Empirical Finance, Elsevier, vol. 46(C), pages 130-145.
    24. Gao, Yan & Li, Honggang, 2011. "A consolidated model of self-fulfilling expectations and self-destroying expectations in financial markets," Journal of Economic Behavior & Organization, Elsevier, vol. 77(3), pages 368-381, March.
    25. Giacomini, Raffaella & Rossi, Barbara, 2008. "Forecast Comparisons in Unstable Environments," Working Papers 08-04, Duke University, Department of Economics.
    26. Kevin Rink, 2023. "The predictive ability of technical trading rules: an empirical analysis of developed and emerging equity markets," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 37(4), pages 403-456, December.
    27. Shailesh Rana & William H. Bommer & G. Michael Phillips, 2020. "Predicting Returns for Growth and Value Stocks: A Forecast Assessment Approach Using Global Asset Pricing Models," International Journal of Economics and Financial Issues, Econjournals, vol. 10(4), pages 88-106.
    28. Marta Matyjaszek & Gregorio Fidalgo Valverde & Alicja Krzemień & Krzysztof Wodarski & Pedro Riesgo Fernández, 2020. "Optimizing Predictor Variables in Artificial Neural Networks When Forecasting Raw Material Prices for Energy Production," Energies, MDPI, vol. 13(8), pages 1-15, April.
    29. Guidolin, Massimo & Hyde, Stuart, 2012. "Simple VARs cannot approximate Markov switching asset allocation decisions: An out-of-sample assessment," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3546-3566.
    30. Guillaume Belly & Lukas Boeckelmann & Carlos Mateo Caicedo Graciano & Alberto Di Iorio & Klodiana Istrefi & Vasileios Siakoulis & Arthur Stalla‐Bourdillon, 2023. "Forecasting sovereign risk in the Euro area via machine learning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(3), pages 657-684, April.
    31. Çakmaklı, Cem & van Dijk, Dick, 2016. "Getting the most out of macroeconomic information for predicting excess stock returns," International Journal of Forecasting, Elsevier, vol. 32(3), pages 650-668.
    32. Tang, Chor Foon & Lai, Yew Wah, 2011. "The Stability of Export-led Growth Hypothesis: Evidence from Asia's Four Little Dragons," MPRA Paper 27962, University Library of Munich, Germany.
    33. Taylor, Mark & Hsu, Po-Hsuan, 2014. "Forty Years, Thirty Currencies and 21,000 Trading Rules: A Large-scale, Data-Snooping Robust Analysis of Technical Trading in t," CEPR Discussion Papers 10018, C.E.P.R. Discussion Papers.
    34. I. Marta Miranda García & María‐Jesús Segovia‐Vargas & Usue Mori & José A. Lozano, 2023. "Early prediction of Ibex 35 movements," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(5), pages 1150-1166, August.
    35. Pincheira Brown, Pablo & Hardy, Nicolás, 2019. "Forecasting base metal prices with the Chilean exchange rate," Resources Policy, Elsevier, vol. 62(C), pages 256-281.
    36. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1203-1324, Elsevier.
    37. Georgiev, Iliyan & Harvey, David I. & Leybourne, Stephen J. & Taylor, A.M. Robert, 2018. "Testing for parameter instability in predictive regression models," Journal of Econometrics, Elsevier, vol. 204(1), pages 101-118.
    38. Juan Reboredo & José Matías & Raquel Garcia-Rubio, 2012. "Nonlinearity in Forecasting of High-Frequency Stock Returns," Computational Economics, Springer;Society for Computational Economics, vol. 40(3), pages 245-264, October.
    39. Harvey, David I & Leybourne, Stephen J & Sollis, Robert & Taylor, AM Robert, 2020. "Real-Time Detection of Regimes of Predictability in the U.S. Equity Premium," Essex Finance Centre Working Papers 27775, University of Essex, Essex Business School.
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    6. Thomas Jobert & Lionel Persyn, 2012. "Quelques constats sur les prévisions conjoncturelles de la croissance française," Revue d'économie politique, Dalloz, vol. 122(6), pages 833-849.
    7. Mihaela SIMIONESCU, 2015. "The Evaluation of Global Accuracy of Romanian Inflation Rate Predictions Using Mahalanobis Distance," Management Dynamics in the Knowledge Economy, College of Management, National University of Political Studies and Public Administration, vol. 3(1), pages 133-149, March.
    8. Behrens, Christoph & Pierdzioch, Christian & Risse, Marian, 2018. "Testing the optimality of inflation forecasts under flexible loss with random forests," Economic Modelling, Elsevier, vol. 72(C), pages 270-277.
    9. Robert Lehmann, 2015. "Survey-based indicators vs. hard data: What improves export forecasts in Europe?," ifo Working Paper Series 196, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    10. Burgess, Matthew G. & Langendorf, Ryan E. & Ippolito, Tara & Pielke, Roger Jr, 2020. "Optimistically biased economic growth forecasts and negatively skewed annual variation," SocArXiv vndqr, Center for Open Science.
    11. Paulo Júlio & Pedro M. Esperança, 2012. "Evaluating the forecast quality of GDP components: An application to G7," GEE Papers 0047, Gabinete de Estratégia e Estudos, Ministério da Economia, revised Apr 2012.
    12. Tsuchiya, Yoichi, 2023. "Assessing the World Bank’s growth forecasts," Economic Analysis and Policy, Elsevier, vol. 77(C), pages 64-84.
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    18. Zeyyad Mandalinci, 2015. "Forecasting Inflation in Emerging Markets: An Evaluation of Alternative Models," CReMFi Discussion Papers 3, CReMFi, School of Economics and Finance, QMUL.
    19. Fernando M. Martin & Juan M. Sanchez & Olivia Wilkinson, 2022. "The Economic Impact of COVID-19 around the World," Working Papers 2022-030, Federal Reserve Bank of St. Louis.
    20. 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.
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    22. Paulina Ziembińska, 2021. "Quality of Tests of Expectation Formation for Revised Data," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 13(4), pages 405-453, December.
    23. Heinisch, Katja & Lindner, Axel, 2018. "For how long do IMF forecasts of world economic growth stay up-to-date?," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, issue Latest ar, pages 1-6.
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    27. Ildeberta Abreu, 2011. "International organisations’ vs. private analysts’ forecasts: an evaluation," Working Papers w201120, Banco de Portugal, Economics and Research Department.
    28. Nordvik, Frode Martin, 2022. "Inflation news and the poor: The role of ethnic heterogeneity," World Development, Elsevier, vol. 151(C).
    29. H.O. Stekler & Huixia Zhang, 2013. "An evaluation of Chinese economic forecasts," Journal of Chinese Economic and Business Studies, Taylor & Francis Journals, vol. 11(4), pages 251-259, November.
    30. Eicher, Theo S. & Kawai, Reina, 2023. "IMF trade forecasts for crisis countries: Bias, inefficiency, and their origins," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1615-1639.
    31. Dovern, Jonas & Weisser, Johannes, 2011. "Accuracy, unbiasedness and efficiency of professional macroeconomic forecasts: An empirical comparison for the G7," International Journal of Forecasting, Elsevier, vol. 27(2), pages 452-465, April.
    32. Timmermann, Allan & Qu, Ritong & Zhu, Yinchu, 2019. "Do Any Economists Have Superior Forecasting Skills?," CEPR Discussion Papers 14112, C.E.P.R. Discussion Papers.
    33. Metodij Hadzi-Vaskov & Mr. Luca A Ricci & Alejandro Mariano Werner & Rene Zamarripa, 2021. "Patterns in IMF Growth Forecast Revisions: A Panel Study at Multiple Horizons," IMF Working Papers 2021/136, International Monetary Fund.
    34. Jungjin Lee & Mr. Abdul d Abiad & Mr. Prakash Kannan, 2009. "Evaluating Historical CGER Assessments: How Well Have They Predicted Subsequent Exchange Rate Movements?," IMF Working Papers 2009/032, International Monetary Fund.
    35. Winkelried, Diego, 2014. "Inferring inflation expectations from fixed-event forecasts," Working Papers 2014-016, Banco Central de Reserva del Perú.
    36. Carabotta, Laura & Paluzie, Elisenda & Ramos, Raul, 2017. "Does fiscal responsibility matter? Evidence from public and private forecasters in Italy," International Journal of Forecasting, Elsevier, vol. 33(3), pages 694-706.
    37. Masahito Ambashi & Fusanori Iwasaki & Keita Oikawa, 2021. "Prediction Errors of Macroeconomic Indicators and Economic Shocks for ASEAN Member States," Working Papers DP-2022-02, Economic Research Institute for ASEAN and East Asia (ERIA).
    38. Winkelried, Diego, 2023. "Simple interpolations of inflation expectations," Economics Letters, Elsevier, vol. 229(C).
    39. Merola, Rossana & Pérez, Javier J., 2014. "Fiscal Forecast Errors: Governments Versus Independent Agencies?," Papers RB2014/1/1, Economic and Social Research Institute (ESRI).
    40. Aromí, J. Daniel, 2019. "Medium term growth forecasts: Experts vs. simple models," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1085-1099.
    41. MORIKAWA Masayuki, 2019. "Uncertainty in Long-Term Macroeconomic Forecasts: Ex post Evaluation of Forecasts by Economics Researchers," Discussion papers 19084, Research Institute of Economy, Trade and Industry (RIETI).
    42. Julien Champagne & Guillaume Poulin-Bellisle & Rodrigo Sekkel, 2018. "Evaluating the Bank of Canada Staff Economic Projections Using a New Database of Real-Time Data and Forecasts," Staff Working Papers 18-52, Bank of Canada.
    43. Jin-Kyu Jung & Manasa Patnam & Anna Ter-Martirosyan, 2018. "An Algorithmic Crystal Ball: Forecasts-based on Machine Learning," IMF Working Papers 2018/230, International Monetary Fund.
    44. Yoichi Tsuchiya, 2021. "Thirty‐year assessment of Asian Development Bank's forecasts," Asian-Pacific Economic Literature, The Crawford School, The Australian National University, vol. 35(2), pages 18-40, November.
    45. Paulo Júlio & Pedro M. Esperança & João C. Fonseca, 2011. "Evaluating the forecast quality of GDP components," GEE Papers 0041 Classification-C52, , Gabinete de Estratégia e Estudos, Ministério da Economia, revised Oct 2011.
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    1. Stan Hurn & Jing Tian & Lina Xu, 2021. "Assessing the Informational Content of Official Australian Bureau of Meteorology Forecasts of Wind Speed," The Economic Record, The Economic Society of Australia, vol. 97(319), pages 525-547, December.
    2. Capistrán, Carlos & López-Moctezuma, Gabriel, 2014. "Forecast revisions of Mexican inflation and GDP growth," International Journal of Forecasting, Elsevier, vol. 30(2), pages 177-191.
    3. Sinclair, Tara M. & Gamber, Edward N. & Stekler, Herman & Reid, Elizabeth, 2012. "Jointly evaluating the Federal Reserve’s forecasts of GDP growth and inflation," International Journal of Forecasting, Elsevier, vol. 28(2), pages 309-314.
    4. Shea, Paul, 2015. "Red herrings and revelations: does learning about a new variable worsen forecasts?," Economic Modelling, Elsevier, vol. 49(C), pages 395-406.
    5. Emilio Zanetti Chini, 2018. "Forecaster’s utility and forecasts coherence," CREATES Research Papers 2018-01, Department of Economics and Business Economics, Aarhus University.
    6. 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.
    7. Pierdzioch, Christian & Rülke, Jan-Christoph, 2013. "Do inflation targets anchor inflation expectations?," Economic Modelling, Elsevier, vol. 35(C), pages 214-223.
    8. Lima, Luiz Renato & Meng, Fanning & Godeiro, Lucas, 2020. "Quantile forecasting with mixed-frequency data," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1149-1162.
    9. Bauer, Christian & Neuenkirch, Matthias, 2017. "Forecast uncertainty and the Taylor rule," Journal of International Money and Finance, Elsevier, vol. 77(C), pages 99-116.
    10. Pablo Pincheira B. & Nicolás Fernández, 2011. "Jaque Mate a las Proyecciones de Consenso," Working Papers Central Bank of Chile 630, Central Bank of Chile.
    11. Jens J. Krüger, 2014. "A multivariate evaluation of German output growth and inflation forecasts," Economics Bulletin, AccessEcon, vol. 34(3), pages 1410-1418.
    12. Rebekka Gätjen & Melanie Schienle, 2015. "Measuring Connectedness of Euro Area Sovereign Risk," SFB 649 Discussion Papers SFB649DP2015-019, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    13. Anatolyev, Stanislav, 2009. "Dynamic modeling under linear-exponential loss," Economic Modelling, Elsevier, vol. 26(1), pages 82-89, January.
    14. Coroneo, Laura & Iacone, Fabrizio & Paccagnini, Alessia & Santos Monteiro, Paulo, 2023. "Testing the predictive accuracy of COVID-19 forecasts," International Journal of Forecasting, Elsevier, vol. 39(2), pages 606-622.
    15. William A. Branch, 2014. "Nowcasting and the Taylor Rule," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 46(5), pages 1035-1055, August.
    16. Sun, Yuying & Wang, Shouyang & Zhang, Xun, 2018. "How efficient are China's macroeconomic forecasts? Evidences from a new forecasting evaluation approach," Economic Modelling, Elsevier, vol. 68(C), pages 506-513.
    17. Fritsche, Ulrich & Pierdzioch, Christian & Rülke, Jan-Christoph & Stadtmann, Georg, 2015. "Forecasting the Brazilian real and the Mexican peso: Asymmetric loss, forecast rationality, and forecaster herding," International Journal of Forecasting, Elsevier, vol. 31(1), pages 130-139.
    18. Jalles, João Tovar, 2017. "On the rationality and efficiency of inflation forecasts: Evidence from advanced and emerging market economies," Research in International Business and Finance, Elsevier, vol. 40(C), pages 175-189.
    19. Alp, Tansel & Demetrescu, Matei, 2010. "Joint forecasts of Dow Jones stocks under general multivariate loss function," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2360-2371, November.
    20. Joanna Bruzda, 2020. "Multistep quantile forecasts for supply chain and logistics operations: bootstrapping, the GARCH model and quantile regression based approaches," 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. 28(1), pages 309-336, March.
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    22. Faust, Jon & Wright, Jonathan H., 2013. "Forecasting Inflation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 2-56, Elsevier.
    23. Conrad, Christian, 2017. "When does information on forecast variance improve the performance of a combined forecast?," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168200, Verein für Socialpolitik / German Economic Association.
    24. Demetrescu, Matei & Hacıoğlu Hoke, Sinem, 2019. "Predictive regressions under asymmetric loss: Factor augmentation and model selection," International Journal of Forecasting, Elsevier, vol. 35(1), pages 80-99.
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    26. Andrea Betancor & Pablo Pincheira, 2008. "Forecasting Inflation Forecast Errors," Working Papers Central Bank of Chile 477, Central Bank of Chile.
    27. Xinglin Yang & Peng Wang, 2018. "VIX futures pricing with conditional skewness," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(9), pages 1126-1151, September.
    28. G. Kontogeorgos & K. Lambrias, 2022. "Evaluating the Eurosystem/ECB staff macroeconomic projections: The first 20 years," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 213-229, March.
    29. João Henrique Gonçalves Mazzeu & Esther Ruiz & Helena Veiga, 2018. "Uncertainty And Density Forecasts Of Arma Models: Comparison Of Asymptotic, Bayesian, And Bootstrap Procedures," Journal of Economic Surveys, Wiley Blackwell, vol. 32(2), pages 388-419, April.
    30. Barbara Rossi, 2011. "Comment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 25-29, August.
    31. Siddhartha S. Bora & Ani L. Katchova & Todd H. Kuethe, 2021. "The Rationality of USDA Forecasts under Multivariate Asymmetric Loss," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(3), pages 1006-1033, May.
    32. Bourmpoula, Evangelia. & Wieser, Christina., 2014. "An accuracy assessment of the global employment trends' unemployment rate forecasts," ILO Working Papers 994888903402676, International Labour Organization.
    33. Rodríguez-Vargas, Adolfo, 2020. "Forecasting Costa Rican inflation with machine learning methods," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 1(1).
    34. Xinyu Zhang & Alan T. K. Wan & Sherry Z. Zhou, 2011. "Focused Information Criteria, Model Selection, and Model Averaging in a Tobit Model With a Nonzero Threshold," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 132-142, June.
    35. Federico Bassetti & Roberto Casarin & Marco Del Negro, 2022. "A Bayesian Approach to Inference on Probabilistic Surveys," Staff Reports 1025, Federal Reserve Bank of New York.
    36. Ildeberta Abreu, 2011. "International organisations’ vs. private analysts’ forecasts: an evaluation," Working Papers w201120, Banco de Portugal, Economics and Research Department.
    37. Franses, Ph.H.B.F. & McAleer, M.J. & Legerstee, R., 2008. "Expert opinion versus expertise in forecasting," Econometric Institute Research Papers EI 2008-30, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    38. Roman Huptas, 2019. "Point forecasting of intraday volume using Bayesian autoregressive conditional volume models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(4), pages 293-310, July.
    39. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1203-1324, Elsevier.
    40. Luetkepohl Helmut & Xu Fang, 2011. "Forecasting Annual Inflation with Seasonal Monthly Data: Using Levels versus Logs of the Underlying Price Index," Journal of Time Series Econometrics, De Gruyter, vol. 3(1), pages 1-23, February.
    41. Michael W. McCracken & Giorgio Valente, 2012. "Asymptotic Inference for Performance Fees and the Predictability of Asset Returns," Working Papers 2012-049, Federal Reserve Bank of St. Louis.
    42. Thiago De Oliveira Souza, 2011. "Forecasting Investment-Grade Credit-Spreads. A Regularized Approach," Working Papers ECARES ECARES 2011-037, ULB -- Universite Libre de Bruxelles.
    43. Massimo Guidolin & Stuart Hyde & David McMillan & Sadayuki Ono, 2009. "Non-linear predictability in stock and bond returns: when and where is it exploitable?," Working Papers 2008-010, Federal Reserve Bank of St. Louis.
    44. Kontogeorgos, Georgios & Lambrias, Kyriacos, 2019. "An analysis of the Eurosystem/ECB projections," Working Paper Series 2291, European Central Bank.
    45. 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.
    46. Olga Isengildina‐Massa & Berna Karali & Todd H. Kuethe & Ani L. Katchova, 2021. "Joint Evaluation of the System of USDA's Farm Income Forecasts," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 43(3), pages 1140-1160, September.
    47. Donayre, Luiggi & Panovska, Irina, 2016. "Nonlinearities in the U.S. wage Phillips curve," Journal of Macroeconomics, Elsevier, vol. 48(C), pages 19-43.
    48. Capistrán Carlos, 2007. "Optimality Tests for Multi-Horizon Forecasts," Working Papers 2007-14, Banco de México.
    49. 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.
    50. Christian Pierdzioch & Jan-Christoph Rülke & Peter Tillmann, 2013. "Using forecasts to uncover the loss function of FOMC members," MAGKS Papers on Economics 201302, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    51. Mehmet Pinar & Thanasis Stengos & M. Ege Yazgan, 2018. "Quantile forecast combination using stochastic dominance," Empirical Economics, Springer, vol. 55(4), pages 1717-1755, December.
    52. Timmermann Allan & Capistrán Carlos, 2006. "Disagreement and Biases in Inflation Expectations," Working Papers 2006-07, Banco de México.
    53. Nazaria Solferino & Robert Waldmann, 2010. "Predicting the signs of forecast errors," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(5), pages 476-485.
    54. Cui, Qiurong & Xu, Yuqing & Zhang, Zhengjun & Chan, Vincent, 2021. "Max-linear regression models with regularization," Journal of Econometrics, Elsevier, vol. 222(1), pages 579-600.
    55. 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.
    56. Wang, Yiyao & Lee, Tae-Hwy, 2014. "Asymmetric loss in the Greenbook and the Survey of Professional Forecasters," International Journal of Forecasting, Elsevier, vol. 30(2), pages 235-245.
    57. 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.
    58. 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.
    59. Chevillon, Guillaume, 2016. "Multistep forecasting in the presence of location shifts," International Journal of Forecasting, Elsevier, vol. 32(1), pages 121-137.
    60. Gneiting, Tilmann, 2011. "Quantiles as optimal point forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 197-207, April.
    61. Florian Peters & Simas Kucinskas, 2018. "Measuring Biases in Expectation Formation," Tinbergen Institute Discussion Papers 18-058/IV, Tinbergen Institute.
    62. Demetrescu, Matei & Golosnoy, Vasyl & Titova, Anna, 2020. "Bias corrections for exponentially transformed forecasts: Are they worth the effort?," International Journal of Forecasting, Elsevier, vol. 36(3), pages 761-780.
    63. 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.
    64. Bovi, Maurizio, 2019. "A Time-Varying Expectations Formation Mechanism," MPRA Paper 97624, University Library of Munich, Germany.
    65. Bruzda, Joanna, 2019. "Quantile smoothing in supply chain and logistics forecasting," International Journal of Production Economics, Elsevier, vol. 208(C), pages 122-139.
    66. 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.
    67. Kuethe, Todd H. & Regmi, Hari, 2023. "An Evaluation of Congressional Budget Office’s Baseline Projections of USDA Mandatory Farm and Nutrition Programs," 2023 Annual Meeting, July 23-25, Washington D.C. 335690, Agricultural and Applied Economics Association.
    68. Lillestøl, Jostein & Sinding-Larsen, Richard, 2015. "Best estimate reporting with asymmetric loss," Discussion Papers 2015/7, Norwegian School of Economics, Department of Business and Management Science.
    69. Patton, Andrew J., 2011. "Volatility forecast comparison using imperfect volatility proxies," Journal of Econometrics, Elsevier, vol. 160(1), pages 246-256, January.
    70. Chia-Lin Chang & Philip Hans Franses & Michael McAleer, 2009. "How Accurate are Government Forecasts of Economic Fundamentals? The Case of Taiwan," CIRJE F-Series CIRJE-F-637, CIRJE, Faculty of Economics, University of Tokyo.
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    73. Giovannelli, Alessandro & Pericoli, Filippo Maria, 2020. "Are GDP forecasts optimal? Evidence on European countries," International Journal of Forecasting, Elsevier, vol. 36(3), pages 963-973.
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    76. Gneiting, Tilmann, 2011. "Quantiles as optimal point forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 197-207.
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  22. Guidolin, Massimo & Timmermann, Allan, 2007. "Properties of equilibrium asset prices under alternative learning schemes," Journal of Economic Dynamics and Control, Elsevier, vol. 31(1), pages 161-217, January.

    Cited by:

    1. Volker Wieland & Christos Koulovatianos, 2011. "Asset Pricing under Rational Learning about Rare Disasters," 2011 Meeting Papers 1417, Society for Economic Dynamics.
    2. Massimo Guidolin, 2006. "High equity premia and crash fears - Rational foundations," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 28(3), pages 693-708, August.
    3. Koulovatianos, Christos, 2010. "A Paradox of Environmental Awareness Campaigns," MPRA Paper 27260, University Library of Munich, Germany.
    4. Fabio Milani, 2008. "Learning about the Interdependence between the Macroeconomy and the Stock Market," Working Papers 070819, University of California-Irvine, Department of Economics.
    5. Bernales, Alejandro & Chen, Louisa & Valenzuela, Marcela, 2017. "Learning and forecasts about option returns through the volatility risk premium," Journal of Economic Dynamics and Control, Elsevier, vol. 82(C), pages 312-330.
    6. Subrahmanyam, Avanidhar, 2008. "Learning from experience and trading volume," Review of Financial Economics, Elsevier, vol. 17(4), pages 245-260, December.
    7. Hommes, C.H. & Zhu, M., 2012. "Behavioral Learning Equilibria," CeNDEF Working Papers 12-09, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    8. Massimo Guidolin, 2005. "Pessimistic beliefs under rational learning: quantitative implications for the equity premium puzzle," Working Papers 2005-005, Federal Reserve Bank of St. Louis.
    9. Boudoukh, Jacob & Israel, Ronen & Richardson, Matthew, 2022. "Biases in long-horizon predictive regressions," Journal of Financial Economics, Elsevier, vol. 145(3), pages 937-969.
    10. Geoffrey J. Warren, 2008. "Implications for Asset Pricing Puzzles of a Roll‐over Assumption for the Risk‐Free Asset," International Review of Finance, International Review of Finance Ltd., vol. 8(3‐4), pages 125-157, September.
    11. Timmermann, Allan, 2008. "Elusive return predictability," International Journal of Forecasting, Elsevier, vol. 24(1), pages 1-18.
    12. Lei Shi, 2010. "Portfolio Analysis and Equilibrium Asset Pricing with Heterogeneous Beliefs," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 2-2010.
    13. Avanidhar Subrahmanyam, 2008. "Learning from experience and trading volume," Review of Financial Economics, John Wiley & Sons, vol. 17(4), pages 245-260, December.
    14. Christos Koulovatianos, 2015. "Strategic Exploitation of a Common-Property Resource Under Rational Learning About its Reproduction," Dynamic Games and Applications, Springer, vol. 5(1), pages 94-119, March.
    15. Avanidhar Subrahmanyam, 2009. "Optimal financial education," Review of Financial Economics, John Wiley & Sons, vol. 18(1), pages 1-9, January.
    16. Subrahmanyam, Avanidhar, 2009. "Optimal financial education," Review of Financial Economics, Elsevier, vol. 18(1), pages 1-9, January.
    17. Bullard, J.B. & Suda, J., 2011. "The Stability of Macroeconomic Systems with Bayesian Learners," Working papers 332, Banque de France.
    18. Du, Kai, 2019. "Investor expectations, earnings management, and asset prices," Journal of Economic Dynamics and Control, Elsevier, vol. 105(C), pages 134-157.
    19. Bernales, Alejandro & Guidolin, Massimo, 2015. "Learning to smile: Can rational learning explain predictable dynamics in the implied volatility surface?," Journal of Financial Markets, Elsevier, vol. 26(C), pages 1-37.
    20. Quaye, Enoch & Tunaru, Radu, 2022. "The stock implied volatility and the implied dividend volatility," Journal of Economic Dynamics and Control, Elsevier, vol. 134(C).
    21. Xue-Zhong He & Lei Shi, 2016. "A Binomial Model of Asset and Option Pricing with Heterogeneous Beliefs," Published Paper Series 2016-4, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    22. Consiglio, Andrea & Russino, Annalisa, 2007. "How does learning affect market liquidity? A simulation analysis of a double-auction financial market with portfolio traders," Journal of Economic Dynamics and Control, Elsevier, vol. 31(6), pages 1910-1937, June.
    23. Brianzoni, Serena & Campisi, Giovanni, 2020. "Dynamical analysis of a financial market with fundamentalists, chartists, and imitators," Chaos, Solitons & Fractals, Elsevier, vol. 130(C).
    24. Gandré, Pauline, 2020. "US stock prices and recency-biased learning in the run-up to the Global Financial Crisis and its aftermath," Journal of International Money and Finance, Elsevier, vol. 104(C).

  23. Patton, Andrew J. & Timmermann, Allan, 2007. "Testing Forecast Optimality Under Unknown Loss," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 1172-1184, December.

    Cited by:

    1. 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.
    2. 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.
    3. Sinclair, Tara M. & Gamber, Edward N. & Stekler, Herman & Reid, Elizabeth, 2012. "Jointly evaluating the Federal Reserve’s forecasts of GDP growth and inflation," International Journal of Forecasting, Elsevier, vol. 28(2), pages 309-314.
    4. Wieland, Volker & Wolters, Maik, 2013. "Forecasting and Policy Making," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 239-325, Elsevier.
    5. Aretz, Kevin & Bartram, Söhnke M. & Pope, Peter F., 2011. "Asymmetric Loss Functions and the Rationality of Expected Stock Returns," MPRA Paper 47343, University Library of Munich, Germany.
    6. Emilio Zanetti Chini, 2018. "Forecaster’s utility and forecasts coherence," CREATES Research Papers 2018-01, Department of Economics and Business Economics, Aarhus University.
    7. 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.
    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.
    9. Matteo Iacopini & Francesco Ravazzolo & Luca Rossini, 2020. "Proper scoring rules for evaluating asymmetry in density forecasting," Working Papers No 06/2020, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    10. Knüppel, Malte & Schultefrankenfeld, Guido, 2018. "Assessing the uncertainty in central banks' inflation outlooks," Discussion Papers 56/2018, Deutsche Bundesbank.
    11. Ulrich Fritsche & Artur Tarassow, 2017. "Vergleichende Evaluation der Konjunkturprognosen des Instituts für Makroökonomie und Konjunkturforschung an der Hans-Böckler-Stiftung für den Zeitraum 2005-2014," IMK Studies 54-2017, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
    12. Michael P. Clements, 2022. "Forecaster Efficiency, Accuracy, and Disagreement: Evidence Using Individual‐Level Survey Data," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(2-3), pages 537-568, March.
    13. Clements, Michael P., 2019. "Do forecasters target first or later releases of national accounts data?," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1240-1249.
    14. Luiz Renato Regis de Oliveira Lima & Wagner Piazza Gaglianone, 2012. "Constructing Optimal Density Forecasts from Point Forecast Combinations," Série Textos para Discussão (Working Papers) 5, Programa de Pós-Graduação em Economia - PPGE, Universidade Federal da Paraíba.
    15. Chini, Emilio Zanetti, 2023. "Can we estimate macroforecasters’ mis-behavior?," Journal of Economic Dynamics and Control, Elsevier, vol. 149(C).
    16. Christian Pierdzioch & Monique B. Reid & Rangan Gupta, 2014. "Forecasting the South African Inflation Rate: On Asymmetric Loss and Forecast Rationality," Working Papers 201475, University of Pretoria, Department of Economics.
    17. 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.
    18. Fritsche, Ulrich & Pierdzioch, Christian & Rülke, Jan-Christoph & Stadtmann, Georg, 2015. "Forecasting the Brazilian real and the Mexican peso: Asymmetric loss, forecast rationality, and forecaster herding," International Journal of Forecasting, Elsevier, vol. 31(1), pages 130-139.
    19. Behrens, Christoph & Pierdzioch, Christian & Risse, Marian, 2018. "Testing the optimality of inflation forecasts under flexible loss with random forests," Economic Modelling, Elsevier, vol. 72(C), pages 270-277.
    20. Patrick Schmidt & Matthias Katzfuss & Tilmann Gneiting, 2021. "Interpretation of point forecasts with unknown directive," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(6), pages 728-743, September.
    21. Tsuchiya, Yoichi, 2023. "Assessing the World Bank’s growth forecasts," Economic Analysis and Policy, Elsevier, vol. 77(C), pages 64-84.
    22. Dimitriadis, Timo & Schnaitmann, Julie, 2021. "Forecast encompassing tests for the expected shortfall," International Journal of Forecasting, Elsevier, vol. 37(2), pages 604-621.
    23. Lieli, Robert P. & Stinchcombe, Maxwell B. & Grolmusz, Viola M., 2019. "Unrestricted and controlled identification of loss functions: Possibility and impossibility results," International Journal of Forecasting, Elsevier, vol. 35(3), pages 878-890.
    24. 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.
    25. Demetrescu, Matei & Hacıoğlu Hoke, Sinem, 2019. "Predictive regressions under asymmetric loss: Factor augmentation and model selection," International Journal of Forecasting, Elsevier, vol. 35(1), pages 80-99.
    26. Christoph Behrens, 2019. "A Nonparametric Evaluation of the Optimality of German Export and Import Growth Forecasts under Flexible Loss," Economies, MDPI, vol. 7(3), pages 1-23, September.
    27. Tsuchiya, Yoichi, 2015. "Herding behavior and loss functions of exchange rate forecasters over interventions and financial crises," International Review of Economics & Finance, Elsevier, vol. 39(C), pages 266-276.
    28. Lima, Luiz Renato Regis de Oliveira & Issler, João Victor, 2007. "A panel data approach to economic forecasting: the bias-corrected average forecast," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 650, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    29. Timmermann, Allan & Patton, Andrew, 2011. "Forecast Rationality Tests Based on Multi-Horizon Bounds," CEPR Discussion Papers 8194, C.E.P.R. Discussion Papers.
    30. Issler, João Victor & Rodrigues, Claudia & Burjack, Rafael, 2014. "Using common features to understand the behavior of metal-commodity prices and forecast them at different horizons," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 310-335.
    31. G. Kontogeorgos & K. Lambrias, 2022. "Evaluating the Eurosystem/ECB staff macroeconomic projections: The first 20 years," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 213-229, March.
    32. Dovern, Jonas & Jannsen, Nils, 2015. "Systematic errors in growth expectations over the business cycle," Kiel Working Papers 1989, Kiel Institute for the World Economy (IfW Kiel).
    33. Debopam Bhattacharya, 2012. "Evaluating Treatment Protocols using Data Combination," Economics Series Working Papers 609, University of Oxford, Department of Economics.
    34. Miah, Fazlul & Khalifa, Ahmed Ali & Hammoudeh, Shawkat, 2016. "Further evidence on the rationality of interest rate expectations: A comprehensive study of developed and emerging economies," Economic Modelling, Elsevier, vol. 54(C), pages 574-590.
    35. Higgins, Matthew L. & Mishra, Sagarika, 2012. "State dependent asymmetric loss and the consensus forecast of real U.S. GDP growth," Working Papers fe_2012_10, Deakin University, Department of Economics.
    36. Franses, Ph.H.B.F. & Welz, M., 2018. "Evaluating heterogeneous forecasts for vintages of macroeconomic variables," Econometric Institute Research Papers EI2018-47, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    37. Manzanares, Andrés & Garcí­a, Juan Angel, 2007. "Reporting biases and survey results: evidence from European professional forecasters," Working Paper Series 836, European Central Bank.
    38. Henk Kranendonk & Debby Lanser & P.H. Franses, 2007. "On the optimality of expert-adjusted forecasts," CPB Discussion Paper 92, CPB Netherlands Bureau for Economic Policy Analysis.
    39. Wagner Piazza Gaglianone & João Victor Issler & Silvia Maria Matos, 2017. "Applying a microfounded-forecasting approach to predict Brazilian inflation," Empirical Economics, Springer, vol. 53(1), pages 137-163, August.
    40. Wagner Piazza Gaglianone & João Victor Issler, 2014. "Microfounded Forecasting," Working Papers Series 372, Central Bank of Brazil, Research Department.
    41. Joerg Doepke & Ulrich Fritsche & Boriss Siliverstovs, 2009. "Evaluating German business cycle forecasts under an asymmetric loss function," KOF Working papers 09-237, KOF Swiss Economic Institute, ETH Zurich.
    42. Michael P Clements, 2014. "Assessing the Evidence of Macro- Forecaster Herding: Forecasts of Inflation and Output Growth," ICMA Centre Discussion Papers in Finance icma-dp2014-12, Henley Business School, University of Reading.
    43. Alexander Foltas & Christian Pierdzioch, 2022. "Business-cycle reports and the efficiency of macroeconomic forecasts for Germany," Applied Economics Letters, Taylor & Francis Journals, vol. 29(10), pages 867-872, June.
    44. Wagner Piazza Gaglianone & Luiz Renato Lima, 2012. "Constructing Density Forecasts from Quantile Regressions," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(8), pages 1589-1607, December.
    45. Baghestani, Hamid & Khallaf, Ashraf, 2012. "Predictions of growth in U.S. corporate profits: Asymmetric vs. symmetric loss," International Review of Economics & Finance, Elsevier, vol. 22(1), pages 222-229.
    46. Franses, Ph.H.B.F. & McAleer, M.J. & Legerstee, R., 2008. "Expert opinion versus expertise in forecasting," Econometric Institute Research Papers EI 2008-30, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    47. Sarah Miller & Patrick Sabourin, 2023. "What consistent responses on future inflation by consumers can reveal," Discussion Papers 2023-7, Bank of Canada.
    48. Maurizio Bovi & Roy Cerqueti, 2016. "Forecasting macroeconomic fundamentals in economic crises," Annals of Operations Research, Springer, vol. 247(2), pages 451-469, December.
    49. Lena Dräger & Jan-Oliver Menz & Ulrich Fritsche, 2011. "Perceived Inflation under Loss Aversion," Macroeconomics and Finance Series 201105, University of Hamburg, Department of Socioeconomics.
    50. Kontogeorgos, Georgios & Lambrias, Kyriacos, 2019. "An analysis of the Eurosystem/ECB projections," Working Paper Series 2291, European Central Bank.
    51. Graham Elliott & Allan Timmermann, 2016. "Forecasting in Economics and Finance," Annual Review of Economics, Annual Reviews, vol. 8(1), pages 81-110, October.
    52. Mont'Alverne Duarte, Angelo & Gaglianone, Wagner Piazza & de Carvalho Guillén, Osmani Teixeira & Issler, João Victor, 2021. "Commodity prices and global economic activity: A derived-demand approach," Energy Economics, Elsevier, vol. 96(C).
    53. 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.
    54. 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.
    55. Christian Pierdzioch & Jan-Christoph Rülke & Peter Tillmann, 2013. "Using forecasts to uncover the loss function of FOMC members," MAGKS Papers on Economics 201302, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    56. 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.
    57. Chia-Lin Chang & Philip Hans Franses & Michael McAleer, 2010. "Combining Non-Replicable Forecasts," Working Papers in Economics 10/35, University of Canterbury, Department of Economics and Finance.
    58. Andrew J. Patton & Allan Timmermann, 2008. "The Resolution of Macroeconomic Uncertainty: Evidence from Survey Forecast," CREATES Research Papers 2008-54, Department of Economics and Business Economics, Aarhus University.
    59. Michael P. Clements, 2018. "Do Macroforecasters Herd?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(2-3), pages 265-292, March.
    60. Timmermann Allan & Capistrán Carlos, 2006. "Disagreement and Biases in Inflation Expectations," Working Papers 2006-07, Banco de México.
    61. Robert P. Lieli & Augusto Nieto-Barthaburu, 2023. "Forecasting with Feedback," Papers 2308.15062, arXiv.org, revised Jan 2024.
    62. Pierdzioch, Christian & Rülke, Jan-Christoph & Stadtmann, Georg, 2012. "On the loss function of the Bank of Canada: A note," Economics Letters, Elsevier, vol. 115(2), pages 155-159.
    63. Wang, Yiyao & Lee, Tae-Hwy, 2014. "Asymmetric loss in the Greenbook and the Survey of Professional Forecasters," International Journal of Forecasting, Elsevier, vol. 30(2), pages 235-245.
    64. 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.
    65. Michael P. Clements, 2020. "Do Survey Joiners and Leavers Differ from Regular Participants? The US SPF GDP Growth and Inflation Forecasts," ICMA Centre Discussion Papers in Finance icma-dp2020-01, Henley Business School, University of Reading.
    66. Gneiting, Tilmann, 2011. "Quantiles as optimal point forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 197-207, April.
    67. Timo Dimitriadis & Julie Schnaitmann, 2019. "Forecast Encompassing Tests for the Expected Shortfall," Papers 1908.04569, arXiv.org, revised Aug 2020.
    68. Efthymios G. Pavlidis & Ivan Paya & David A. Peel, 2018. "Using Market Expectations to Test for Speculative Bubbles in the Crude Oil Market," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(5), pages 833-856, August.
    69. Matei Demetrescu & Christoph Roling & Anna Titova, 2021. "Reevaluating the prudence of economic forecasts in the EU: The role of instrument persistence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(1), pages 151-161, January.
    70. Bruzda, Joanna, 2019. "Quantile smoothing in supply chain and logistics forecasting," International Journal of Production Economics, Elsevier, vol. 208(C), pages 122-139.
    71. Nakazono, Yoshiyuki, 2013. "Strategic behavior of Federal Open Market Committee board members: Evidence from members’ forecasts," Journal of Economic Behavior & Organization, Elsevier, vol. 93(C), pages 62-70.
    72. Boskabadi, Elahe, 2022. "Economic policy uncertainty and forecast bias in the survey of professional forecasters," MPRA Paper 115081, University Library of Munich, Germany.
    73. Chia-Lin Chang & Philip Hans Franses & Michael McAleer, 2009. "How Accurate are Government Forecasts of Economic Fundamentals? The Case of Taiwan," CIRJE F-Series CIRJE-F-637, CIRJE, Faculty of Economics, University of Tokyo.
    74. Bruzda, Joanna, 2020. "Demand forecasting under fill rate constraints—The case of re-order points," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1342-1361.
    75. Peter, Eckley, 2015. "(Non)rationality of consumer inflation perceptions," MPRA Paper 77082, University Library of Munich, Germany.
    76. 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.
    77. Giovannelli, Alessandro & Pericoli, Filippo Maria, 2020. "Are GDP forecasts optimal? Evidence on European countries," International Journal of Forecasting, Elsevier, vol. 36(3), pages 963-973.
    78. Sizova, Natalia, 2011. "Integrated variance forecasting: Model based vs. reduced form," Journal of Econometrics, Elsevier, vol. 162(2), pages 294-311, June.
    79. 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.
    80. Gneiting, Tilmann, 2011. "Quantiles as optimal point forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 197-207.
    81. Sung No & Michael Salassi, 2009. "A Sequential Rationality Test of USDA Preliminary Price Estimates for Selected Program Crops: Rice, Soybeans, and Wheat," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 15(4), pages 470-482, November.
    82. 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.
    83. Komunjer, Ivana, 2013. "Quantile Prediction," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 961-994, Elsevier.
    84. Rülke, Jan-Christoph & Silgoner, Maria & Wörz, Julia, 2016. "Herding behavior of business cycle forecasters," International Journal of Forecasting, Elsevier, vol. 32(1), pages 23-33.

  24. Hashem Pesaran & Davide Pettenuzzo & Allan Timmermann, 2007. "Learning, Structural Instability, and Present Value Calculations," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 253-288.
    See citations under working paper version above.
  25. Pesaran, M. Hashem & Timmermann, Allan, 2007. "Selection of estimation window in the presence of breaks," Journal of Econometrics, Elsevier, vol. 137(1), pages 134-161, March.

    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. Konstantakis, Konstantinos N. & Michaelides, Panayotis G. & Mariolis, Theodore, 2018. "A non-linear post-Keynesian Goodwin-type endogenous model of the cycle for the USA," MPRA Paper 90036, University Library of Munich, Germany.
    3. Yin, Anwen, 2015. "Forecasting and model averaging with structural breaks," ISU General Staff Papers 201501010800005727, Iowa State University, Department of Economics.
    4. 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.
    5. Chen, Guojin & Liu, Yanzhen & Zhang, Yu, 2020. "Can systemic risk measures predict economic shocks? Evidence from China," China Economic Review, Elsevier, vol. 64(C).
    6. Xiu Xu & Andrija Mihoci & Wolfgang Karl Hardle, 2020. "lCARE -- localizing Conditional AutoRegressive Expectiles," Papers 2009.13215, arXiv.org.
    7. Hansen, Bruce E., 2010. "Averaging estimators for autoregressions with a near unit root," Journal of Econometrics, Elsevier, vol. 158(1), pages 142-155, September.
    8. 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.
    9. Tae-Hwy Lee & Shahnaz Parsaeian & Aman Ullah, 2022. "Forecasting under Structural Breaks Using Improved Weighted Estimation," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202212, University of Kansas, Department of Economics.
    10. Do, Linh Phuong Catherine & Lin, Kuan-Heng & Molnár, Peter, 2016. "Electricity consumption modelling: A case of Germany," Economic Modelling, Elsevier, vol. 55(C), pages 92-101.
    11. Edda Claus, 2011. "Seven Leading Indexes of New Zealand Employment," The Economic Record, The Economic Society of Australia, vol. 87(276), pages 76-89, March.
    12. Marta Boczon, 2018. "Balanced Growth Approach to Forecasting Recessions," Working Paper 6487, Department of Economics, University of Pittsburgh.
    13. Jing Tian & Heather M. Anderson, 2011. "Forecasting Under Strucural Break Uncertainty," Monash Econometrics and Business Statistics Working Papers 8/11, Monash University, Department of Econometrics and Business Statistics.
    14. David E. Rapach & Jack K. Strauss, 2008. "Structural breaks and GARCH models of exchange rate volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(1), pages 65-90.
    15. Andersen, Torben G. & Varneskov, Rasmus T., 2022. "Testing for parameter instability and structural change in persistent predictive regressions," Journal of Econometrics, Elsevier, vol. 231(2), pages 361-386.
    16. Erhard Reschenhofer, 2010. "Forecasting volatility: double averaging and weighted medians," International Journal of Computational Economics and Econometrics, Inderscience Enterprises Ltd, vol. 1(3/4), pages 317-326.
    17. João F. Caldeira & Guilherme V. Moura & Francisco J. Nogales & André A. P. Santos, 2017. "Combining Multivariate Volatility Forecasts: An Economic-Based Approach," Journal of Financial Econometrics, Oxford University Press, vol. 15(2), pages 247-285.
    18. Cho, Haeran & Korkas, Karolos K., 2022. "High-dimensional GARCH process segmentation with an application to Value-at-Risk," Econometrics and Statistics, Elsevier, vol. 23(C), pages 187-203.
    19. Luca Nocciola, "undated". "Finite sample forecast properties and window length under breaks in cointegrated systems," Discussion Papers 19/07, University of Nottingham, Granger Centre for Time Series Econometrics.
    20. Tom Boot & Andreas Pick, 2017. "A near optimal test for structural breaks when forecasting under square error loss," Tinbergen Institute Discussion Papers 17-039/III, Tinbergen Institute.
    21. Tahir, Suleiman & Adegbite, Emmanuel & Guney, Yilmaz, 2017. "An international examination of the economic effectiveness of banking recapitalization," International Business Review, Elsevier, vol. 26(3), pages 417-434.
    22. 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.
    23. Karolina Konopczak & Aleksander Łożykowski, 2021. "Efekt fiskalny uszczelniania systemu podatkowego w Polsce: próba oszacowania w zakresie podatku CIT," Ekonomista, Polskie Towarzystwo Ekonomiczne, issue 1, pages 25-55.
    24. Salisu, Afees A. & Adekunle, Wasiu & Alimi, Wasiu A. & Emmanuel, Zachariah, 2019. "Predicting exchange rate with commodity prices: New evidence from Westerlund and Narayan (2015) estimator with structural breaks and asymmetries," Resources Policy, Elsevier, vol. 62(C), pages 33-56.
    25. John M. Maheu & Stephen Gordon, 2004. "Learning, Forecasting and Structural Breaks," Cahiers de recherche 0422, CIRPEE.
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    1. Panopoulou, Ekaterini & Vrontos, Spyridon, 2015. "Hedge fund return predictability; To combine forecasts or combine information?," Journal of Banking & Finance, Elsevier, vol. 56(C), pages 103-122.
    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. Hsiao, Cheng & Wan, Shui Ki, 2014. "Is there an optimal forecast combination?," Journal of Econometrics, Elsevier, vol. 178(P2), pages 294-309.
    4. George Papadopoulos & Savas Papadopoulos & Thomas Sager, 2016. "Credit risk stress testing for EU15 banks: a model combination approach," Working Papers 203, Bank of Greece.
    5. Elena Andreou & Eric Ghysels & Andros Kourtellos, 2010. "Should macroeconomic forecasters use daily financial data and how?," University of Cyprus Working Papers in Economics 09-2010, University of Cyprus Department of Economics.
    6. Cristiana Belu Manescu & Ine Van Robays, 2016. "Forecasting the Brent Oil Price: Addressing Time-Variation in Forecast Performance," CESifo Working Paper Series 6242, CESifo.
    7. Masayoshi Hayashi, 2012. "Forecasting Welfare Caseloads: The Case of the Japanese Public Assistance Program," CIRJE F-Series CIRJE-F-846, CIRJE, Faculty of Economics, University of Tokyo.
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    9. Bravo, Jorge M. & Ayuso, Mercedes & Holzmann, Robert & Palmer, Edward, 2021. "Addressing the life expectancy gap in pension policy," Insurance: Mathematics and Economics, Elsevier, vol. 99(C), pages 200-221.
    10. Hilde C. Bjørnland & Karsten Gerdrup & Anne Sofie Jore & Christie Smith & Leif Anders Thorsrud, 2012. "Does Forecast Combination Improve Norges Bank Inflation Forecasts?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 74(2), pages 163-179, April.
    11. Jan R. Magnus & Wendun Wang & Xinyu Zhang, 2016. "Weighted-Average Least Squares Prediction," Econometric Reviews, Taylor & Francis Journals, vol. 35(6), pages 1040-1074, June.
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    42. David Rapach & Jack Strauss, 2010. "Bagging or Combining (or Both)? An Analysis Based on Forecasting U.S. Employment Growth," Econometric Reviews, Taylor & Francis Journals, vol. 29(5-6), pages 511-533.
    43. Nikolsko-Rzhevskyy, Alex, 2008. "Monetary Policy Evaluation in Real Time: Forward-Looking Taylor Rules Without Forward-Looking Data," MPRA Paper 11352, University Library of Munich, Germany.
    44. Beltrán, Sergio & Castro, Alain & Irizar, Ion & Naveran, Gorka & Yeregui, Imanol, 2022. "Framework for collaborative intelligence in forecasting day-ahead electricity price," Applied Energy, Elsevier, vol. 306(PA).
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    46. Mawuli Segnon & Stelios Bekiros, 2020. "Forecasting volatility in bitcoin market," Annals of Finance, Springer, vol. 16(3), pages 435-462, September.
    47. Park, Jin Suk & Newaz, Mohammad Khaleq, 2021. "Liquidity and short-run predictability: Evidence from international stock markets," Global Finance Journal, Elsevier, vol. 50(C).
    48. 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.
    49. Dr. Alain Galli & Dr. Christian Hepenstrick & Dr. Rolf Scheufele, 2017. "Mixed-frequency models for tracking short-term economic developments in Switzerland," Working Papers 2017-02, Swiss National Bank.
    50. Segnon, Mawuli & Lux, Thomas & Gupta, Rangan, 2015. "Modeling and Forecasting Carbon Dioxide Emission Allowance Spot Price Volatility: Multifractal vs. GARCH-type Volatility Models," FinMaP-Working Papers 46, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    51. Matsypura, Dmytro & Thompson, Ryan & Vasnev, Andrey L., 2018. "Optimal selection of expert forecasts with integer programming," Omega, Elsevier, vol. 78(C), pages 165-175.
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    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.
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    65. Davide Pettenuzzo & Allan Timmermann & Rossen Valkanov, 2013. "Forecasting Stock Returns under Economic Constraints," Working Papers 57, Brandeis University, Department of Economics and International Business School.
    66. Stephan Jank, 2015. "Changes in the Composition of Publicly Traded Firms: Implications for the Dividend-Price Ratio and Return Predictability," Management Science, INFORMS, vol. 61(6), pages 1362-1377, June.
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    127. Victoria Atanasov & Stig V. Møller & Richard Priestley, 2020. "Consumption Fluctuations and Expected Returns," Journal of Finance, American Finance Association, vol. 75(3), pages 1677-1713, June.
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    130. Jonathan Iworiso & Spyridon Vrontos, 2020. "On the directional predictability of equity premium using machine learning techniques," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 449-469, April.
    131. Verdickt, Gertjan, 2020. "Is fertility a leading indicator for stock returns?," Finance Research Letters, Elsevier, vol. 33(C).
    132. Jiawen Xu & Pierre Perron, 2017. "Forecasting in the presence of in and out of sample breaks," Boston University - Department of Economics - Working Papers Series WP2018-014, Boston University - Department of Economics, revised Nov 2018.
    133. Dorra Zouari & Achraf Ghorbel & Sonia Ghorbel-Zouari & Younes Boujelbène, 2014. "Volatility spillovers and dynamic correlation between liquidity risk factors in Tunisian banks," International Journal of Managerial and Financial Accounting, Inderscience Enterprises Ltd, vol. 6(1), pages 1-26.
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    136. David G. McMillan, 2021. "Forecasting sector stock market returns," Journal of Asset Management, Palgrave Macmillan, vol. 22(4), pages 291-300, July.
    137. Luo, Shikong & Yan, Xinyan & Yang, Haoyi, 2021. "Let’s take a smooth break: Stock return predictability revisited," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 300-314.
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    143. Diaz, Juan & Duarte, Diogo & Galindo, Hamilton & Montecinos, Alexis & Truffa, Santiago, 2021. "The importance of large shocks to return predictability," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    144. Hui Hong & Zhicun Bian & Chien-Chiang Lee, 2021. "COVID-19 and instability of stock market performance: evidence from the U.S," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-18, December.
    145. Amit K. Sinha, 2021. "The reliability of geometric Brownian motion forecasts of S&P500 index values," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1444-1462, December.
    146. Yousuf, Kashif & Ng, Serena, 2021. "Boosting high dimensional predictive regressions with time varying parameters," Journal of Econometrics, Elsevier, vol. 224(1), pages 60-87.
    147. Cenesizoglu, Tolga & Timmermann, Allan, 2012. "Do return prediction models add economic value?," Journal of Banking & Finance, Elsevier, vol. 36(11), pages 2974-2987.
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    149. 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.
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  31. Asger Lunde & Allan Timmermann, 2005. "Completion time structures of stock price movements," Annals of Finance, Springer, vol. 1(3), pages 293-326, August.

    Cited by:

    1. Bastianin, Andrea & Conti, Francesca & Manera, Matteo, 2016. "The Impacts of Oil Price Shocks on Stock Market Volatility: Evidence from the G7 Countries," Energy: Resources and Markets 230682, Fondazione Eni Enrico Mattei (FEEM).
    2. Andrea BASTIANIN & Matteo MANERA, 2015. "How Does Stock Market Volatility React to Oil Shocks?," Departmental Working Papers 2015-09, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    3. Nolte, Ingmar & Voev, Valeri, 2007. "Panel intensity models with latent factors: An application to the trading dynamics on the foreign exchange market," CoFE Discussion Papers 07/02, University of Konstanz, Center of Finance and Econometrics (CoFE).
    4. Hayette Gatfaoui, 2010. "Investigating the Dependence Structure between Credit Default Swap Spreads and the U.S. Financial Market," Post-Print hal-00565525, HAL.
    5. Pedro N. Rodríguez, & Simón Sosvilla-Rivero, 2006. "Forecasting Stock Price Changes: Is it Possible?," Working Papers 2006-22, FEDEA.

  32. Allan Timmermann & David Blake, 2005. "International Asset Allocation with Time-Varying Investment Opportunities," The Journal of Business, University of Chicago Press, vol. 78(1), pages 71-98, January.
    See citations under working paper version above.
  33. Pesaran, M. Hashem & Timmermann, Allan, 2005. "Small sample properties of forecasts from autoregressive models under structural breaks," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 183-217.
    See citations under working paper version above.
  34. Pesaran, Hashem & Timmermann, Allan, 2005. "Real-Time Econometrics," Econometric Theory, Cambridge University Press, vol. 21(1), pages 212-231, February.
    See citations under working paper version above.
  35. Graham Elliott & Allan Timmermann, 2005. "Optimal Forecast Combination Under Regime Switching ," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 46(4), pages 1081-1102, November.
    See citations under working paper version above.
  36. Massimo Guidolin & Allan Timmermann, 2005. "Economic Implications of Bull and Bear Regimes in UK Stock and Bond Returns," Economic Journal, Royal Economic Society, vol. 115(500), pages 111-143, January.

    Cited by:

    1. Michael T. Owyang & Jeremy Piger & Daniel Soques, 2022. "Contagious switching," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(2), pages 415-432, March.
    2. 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.
    3. Fletcher, Jonathan, 2011. "Do optimal diversification strategies outperform the 1/N strategy in U.K. stock returns?," International Review of Financial Analysis, Elsevier, vol. 20(5), pages 375-385.
    4. Heidari , Hassan & Refah-Kahriz, Arash & Hashemi Berenjabadi, Nayyer, 2018. "Dynamic Relationship between Macroeconomic Variables and Stock Return Volatility in Tehran Stock Exchange: Multivariate MS ARMA GARCH Approach," Quarterly Journal of Applied Theories of Economics, Faculty of Economics, Management and Business, University of Tabriz, vol. 5(2), pages 223-250, August.
    5. Don Bredin & Stuart Hyde, 2008. "Regime Change and the Role of International Markets on the Stock Returns of Small Open Economies," European Financial Management, European Financial Management Association, vol. 14(2), pages 315-346, March.
    6. Dai, Zhifeng & Zhang, Xiaotong & Li, Tingyu, 2023. "Forecasting stock return volatility in data-rich environment: A new powerful predictor," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
    7. Thomas J. Flavin & Ekaterini Panopoulou & Deren Unalmis, 2008. "On the Stability of Domestic Financial Market Linkages in the Presence of time-varying Volatility," Working Papers 0810, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    8. Frédérique Bec & Annabelle de Gaye, 2019. "Le modèle autorégressif autorégressif à seuil avec effet rebond : Une application aux rendements boursiers français et américains ," Working Papers hal-02014663, HAL.
    9. Syed Jawad Hussain Shahzad & Saba Ameer & Muhammad Shahbaz, 2016. "Disaggregating the correlation under bearish and bullish markets: A Quantile-quantile approach," Post-Print hal-02013740, HAL.
    10. Zhou, Yinggang, 2014. "Modeling the joint dynamics of risk-neutral stock index and bond yield volatilities," Journal of Banking & Finance, Elsevier, vol. 38(C), pages 216-228.
    11. Massimo Guidolin & Giovanna Nicodano, 2007. "Managing international portfolios with small capitalization stocks," Working Papers 2007-030, Federal Reserve Bank of St. Louis.
    12. Haas, Markus & Mittnik, Stefan, 2008. "Multivariate regimeswitching GARCH with an application to international stock markets," CFS Working Paper Series 2008/08, Center for Financial Studies (CFS).
    13. Chan, Kalok & Yang, Jian & Zhou, Yinggang, 2018. "Conditional co-skewness and safe-haven currencies: A regime switching approach," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 58-80.
    14. John Fender, 2020. "Beyond the efficient markets hypothesis: Towards a new paradigm," Bulletin of Economic Research, Wiley Blackwell, vol. 72(3), pages 333-351, July.
    15. Carolina Fugazza & Massimo Guidolin & Giovanna Nicodano, 2009. "Time and risk diversification in real estate investments: assessing the ex post economic value," Working Papers 2009-001, Federal Reserve Bank of St. Louis.
    16. Meenagh, David & Minford, Patrick & Peel, David, 2007. "Simulating stock returns under switching regimes - A new test of market efficiency," Economics Letters, Elsevier, vol. 94(2), pages 235-239, February.
    17. Donatien Hainaut & Yang Shen & Yan Zeng, 2018. "How do capital structure and economic regime affect fair prices of bank’s equity and liabilities?," Annals of Operations Research, Springer, vol. 262(2), pages 519-545, March.
    18. Jonathan Fletcher, 2011. "An Examination of Dynamic Trading Stategies in UK and US Stock Returns," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 38(9-10), pages 1290-1310, November.
    19. Alfonso Dufour & Andrei Stancu & Simone Varotto, 2014. "The Equity-like Behaviour of Sovereign Bonds," ICMA Centre Discussion Papers in Finance icma-dp2014-16, Henley Business School, University of Reading.
    20. Bulla, Jan, 2009. "Hidden Markov models with t components. Increased persistence and other aspects," MPRA Paper 21830, University Library of Munich, Germany.
    21. Sim, Nicholas, 2016. "Modeling the dependence structures of financial assets through the Copula Quantile-on-Quantile approach," International Review of Financial Analysis, Elsevier, vol. 48(C), pages 31-45.
    22. Roy H. Kwon & Jonathan Y. Li, 2016. "A stochastic semidefinite programming approach for bounds on option pricing under regime switching," Annals of Operations Research, Springer, vol. 237(1), pages 41-75, February.
    23. Guidolin, Massimo & Hyde, Stuart, 2008. "Equity portfolio diversification under time-varying predictability: Evidence from Ireland, the US, and the UK," Journal of Multinational Financial Management, Elsevier, vol. 18(4), pages 293-312, October.
    24. Chang, Kuang-Liang, 2012. "The impacts of regime-switching structures and fat-tailed characteristics on the relationship between inflation and inflation uncertainty," Journal of Macroeconomics, Elsevier, vol. 34(2), pages 523-536.
    25. Hainaut, Donatien, 2014. "Impulse control of pension fund contributions, in a regime switching economy," European Journal of Operational Research, Elsevier, vol. 239(3), pages 810-819.
    26. Massimo Guidolin & Stuart Hyde & David McMillan & Sadayuki Ono, 2010. "Does the macroeconomy predict U.K. asset returns in a nonlinear fashion? comprehensive out-of-sample evidence," Working Papers 2010-039, Federal Reserve Bank of St. Louis.
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    74. Carolina Fugazza & Massimo Guidolin & Giovanna Nicodano, 2008. "Diversifying in public real estate: The ex-post performance," Journal of Asset Management, Palgrave Macmillan, vol. 8(6), pages 361-373, February.
    75. Anandadeep Mandal & Sunil S. Poshakwale & Gabriel J. Power, 2021. "Do investors gain from forecasting the asymmetric return co‐movements of financial and real assets?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 3246-3268, July.
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    78. Flavin, Thomas J. & Lagoa-Varela, Dolores, 2021. "On the stability of stock-bond comovements across market conditions in the Eurozone periphery," Global Finance Journal, Elsevier, vol. 49(C).
    79. Wang Pu & Yixiang Chen & Feng Ma, 2016. "Forecasting the realized volatility in the Chinese stock market: further evidence," Applied Economics, Taylor & Francis Journals, vol. 48(33), pages 3116-3130, July.
    80. Misheck Mutize & Sean J. Gossel, 2019. "Sovereign Credit Rating Announcement Effects on Foreign Currency Denominated Bond and Equity Markets in Africa," Journal of African Business, Taylor & Francis Journals, vol. 20(1), pages 135-152, January.
    81. Muhl, Stefan & Talpsepp, Tõnn, 2018. "Faster learning in troubled times: How market conditions affect the disposition effect," The Quarterly Review of Economics and Finance, Elsevier, vol. 68(C), pages 226-236.
    82. Massimo Guidolin & Giovanna Nicodano, 2009. "Small caps in international equity portfolios: the effects of variance risk," Annals of Finance, Springer, vol. 5(1), pages 15-48, January.
    83. Yao Zheng & Peihwang Wei & Eric Osmer, 2022. "The relation between earnings and price momentum: Does it vary across regimes?," Review of Quantitative Finance and Accounting, Springer, vol. 58(3), pages 1145-1213, April.
    84. Donatien Hainaut & Yan Shen & Yan Zeng, 2016. "How do capital structure and economic regime affect fair prices of bank's equity and liabilities?," Post-Print hal-01394133, HAL.
    85. Rui Fan & Stephen J. Taylor & Matteo Sandri, 2018. "Density forecast comparisons for stock prices, obtained from high‐frequency returns and daily option prices," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(1), pages 83-103, January.
    86. 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.
    87. José Dias & Sofia Ramos, 2014. "The aftermath of the subprime crisis: a clustering analysis of world banking sector," Review of Quantitative Finance and Accounting, Springer, vol. 42(2), pages 293-308, February.
    88. Stavros Degiannakis & Andreas Andrikopoulos & Timotheos Angelidis & Christos Floros, 2013. "Return dispersion, stock market liquidity and aggregate economic activity," Working Papers 166, Bank of Greece.
    89. Fiorentini, Gabriele & Planas, Christophe & Rossi, Alessandro, 2016. "Skewness and kurtosis of multivariate Markov-switching processes," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 153-159.
    90. John Fender, 2015. "Towards a General Theory of the Stock Market," Discussion Papers 15-15, Department of Economics, University of Birmingham.
    91. Manuel Ammann & Michael Verhofen, 2006. "The Effect of Market Regimes on Style Allocation," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 20(3), pages 309-337, September.
    92. Coakley, Jerry & Fuertes, Ana-Maria, 2006. "Valuation ratios and price deviations from fundamentals," Journal of Banking & Finance, Elsevier, vol. 30(8), pages 2325-2346, August.
    93. Roy Kwon & Jonathan Li, 2016. "A stochastic semidefinite programming approach for bounds on option pricing under regime switching," Annals of Operations Research, Springer, vol. 237(1), pages 41-75, February.
    94. Joe Brocato & Kenneth Smith, 2012. "Sudden equity price declines and the flight-to-safety phenomenon: additional evidence using daily data," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 36(3), pages 712-727, July.
    95. Carolina Fugazza & Massimo Guidolin & Giovanna Nicodano, 2007. "Investing for the Long-run in European Real Estate," The Journal of Real Estate Finance and Economics, Springer, vol. 34(1), pages 35-80, January.
    96. Angelos Kanas, 2009. "The relation between the equity risk premium and the bond maturity premium in the UK: 1900–2006," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 33(2), pages 111-127, April.
    97. Wai-Mun Chia & Mengling Li & Huanhuan Zheng, 2017. "Behavioral heterogeneity in the Australian housing market," Applied Economics, Taylor & Francis Journals, vol. 49(9), pages 872-885, February.
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  37. Sandeep Kapur & Allan Timmermann, 2005. "Relative Performance Evaluation Contracts and Asset Market Equilibrium," Economic Journal, Royal Economic Society, vol. 115(506), pages 1077-1102, October.
    See citations under working paper version above.
  38. 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.
    See citations under working paper version above.
  39. Pesaran, M. Hashem & Timmermann, Allan, 2004. "How costly is it to ignore breaks when forecasting the direction of a time series?," International Journal of Forecasting, Elsevier, vol. 20(3), pages 411-425.
    See citations under working paper version above.
  40. Lunde A. & Timmermann A., 2004. "Duration Dependence in Stock Prices: An Analysis of Bull and Bear Markets," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 253-273, July.
    See citations under working paper version above.
  41. Timmermann, Allan & Granger, Clive W. J., 2004. "Efficient market hypothesis and forecasting," International Journal of Forecasting, Elsevier, vol. 20(1), pages 15-27.
    See citations under working paper version above.
  42. Massimo Guidolin & Allan Timmermann, 2003. "Recursive Modeling of Nonlinear Dynamics in UK Stock Returns," Manchester School, University of Manchester, vol. 71(4), pages 381-395, July.

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    1. Don Bredin & Stuart Hyde, 2008. "Regime Change and the Role of International Markets on the Stock Returns of Small Open Economies," European Financial Management, European Financial Management Association, vol. 14(2), pages 315-346, March.
    2. Massimo Guidolin & Stuart Hyde & David McMillan & Sadayuki Ono, 2010. "Does the macroeconomy predict U.K. asset returns in a nonlinear fashion? comprehensive out-of-sample evidence," Working Papers 2010-039, Federal Reserve Bank of St. Louis.
    3. Massimo Guidolin & Stuart Hyde, 2007. "What tames the Celtic tiger? portfolio implications from a multivariate Markov switching model," Working Papers 2006-029, Federal Reserve Bank of St. Louis.
    4. N Aslanidis & D R Osborn & M Sensier, 2003. "Explaining Movements in UK Stock Prices: How Important is the US Market?," Economics Discussion Paper Series 0305, Economics, The University of Manchester.
    5. Massimo Guidolin & Stuart Hyde & David McMillan & Sadayuki Ono, 2009. "Non-linear predictability in stock and bond returns: when and where is it exploitable?," Working Papers 2008-010, Federal Reserve Bank of St. Louis.
    6. Nektarios Aslanidis & Denise R. Osborn & Marianne Sensier, 2008. "Comovements between US and UK stock prices: the roles of macroeconomic information and timevarying conditional correlations," Economics Discussion Paper Series 0805, Economics, The University of Manchester.
    7. Nektarios Aslanidis & Denise Osborn & Marianne Sensier, 2003. "Explaining movements in UK stock prices:," Working Papers 0302, University of Crete, Department of Economics.
    8. Apostolos Thomadakis, 2012. "Contagion or Flight-to-Quality Phenomena in Stock and Bond Returns," School of Economics Discussion Papers 0612, School of Economics, University of Surrey.
    9. Aslanidis, Nektarios & Osborn, Denise R. & Sensier, Marianne, 2008. "Co-movements between US and UK stock prices: the roles of macroeconomic information and time-series varying conditional correlations," Working Papers 2072/8950, Universitat Rovira i Virgili, Department of Economics.
    10. Nektarios Aslanidis & Denise R. Osborn & Marianne Sensier, 2010. "Co-movements between US and UK stock prices: the role of time-varying conditional correlations," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 15(4), pages 366-380.

  43. Sullivan, Ryan & Timmermann, Allan & White, Halbert, 2003. "Forecast evaluation with shared data sets," International Journal of Forecasting, Elsevier, vol. 19(2), pages 217-227.
    See citations under working paper version above.
  44. Guidolin, Massimo & Timmermann, Allan, 2003. "Option prices under Bayesian learning: implied volatility dynamics and predictive densities," Journal of Economic Dynamics and Control, Elsevier, vol. 27(5), pages 717-769, March.
    See citations under working paper version above.
  45. Pesaran, M. Hashem & Timmermann, Allan, 2002. "Market timing and return prediction under model instability," Journal of Empirical Finance, Elsevier, vol. 9(5), pages 495-510, December.
    See citations under working paper version above.
  46. Sullivan, Ryan & Timmermann, Allan & White, Halbert, 2001. "Dangers of data mining: The case of calendar effects in stock returns," Journal of Econometrics, Elsevier, vol. 105(1), pages 249-286, November.

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    2. Kam Fong Chan & John G. Powell & Jing Shi & Tom Smith, 2018. "Dividend persistence and dividend behaviour," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(1), pages 127-147, March.
    3. Egbers, Tom & Swinkels, Laurens, 2015. "Can implied volatility predict returns on the currency carry trade?," Journal of Banking & Finance, Elsevier, vol. 59(C), pages 14-26.
    4. Ryans Bartens & Shakill Hassan, 2009. "Value, Size and Momentum Portfolios in Real Time: The Cross-Section of South African Stocks," Working Papers 154, Economic Research Southern Africa.
    5. Andrew Y. Chen & Tom Zimmermann, 2018. "Publication Bias and the Cross-Section of Stock Returns," Finance and Economics Discussion Series 2018-033, Board of Governors of the Federal Reserve System (U.S.).
    6. William Ziemba, 2011. "Investing in the turn-of-the-year effect," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 25(4), pages 455-472, December.
    7. Meenagh, David & Minford, Patrick & Peel, David, 2007. "Simulating stock returns under switching regimes - A new test of market efficiency," Economics Letters, Elsevier, vol. 94(2), pages 235-239, February.
    8. Thomas Lux, 2009. "Applications of Statistical Physics in Finance and Economics," Chapters, in: J. Barkley Rosser Jr. (ed.), Handbook of Research on Complexity, chapter 9, Edward Elgar Publishing.
    9. Chatzitzisi, Evanthia & Fountas, Stilianos & Panagiotidis, Theodore, 2021. "Another look at calendar anomalies," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 823-840.
    10. Doron Avramov & Guy Kaplanski & Avanidhar Subrahmanyam, 2022. "Postfundamentals Price Drift in Capital Markets: A Regression Regularization Perspective," Management Science, INFORMS, vol. 68(10), pages 7658-7681, October.
    11. Hsu, Po-Hsuan & Han, Qiheng & Wu, Wensheng & Cao, Zhiguang, 2018. "Asset allocation strategies, data snooping, and the 1 / N rule," Journal of Banking & Finance, Elsevier, vol. 97(C), pages 257-269.
    12. Yoon-Jae Whang & Young-Hyun Cho & Oliver Linton, 2006. "Are there Monday effects in Stock Returns: A Stochastic Dominance Approach," FMG Discussion Papers dp568, Financial Markets Group.
    13. Linton, Oliver & Wu, Jianbin, 2020. "A coupled component DCS-EGARCH model for intraday and overnight volatility," Journal of Econometrics, Elsevier, vol. 217(1), pages 176-201.
    14. Chan, Kam Fong & Gray, Philip & Gray, Stephen & Zhong, Angel, 2020. "Political uncertainty, market anomalies and Presidential honeymoons," Journal of Banking & Finance, Elsevier, vol. 113(C).
    15. Rebecca M. Baker & Tahani Coolen-Maturi & Frank P. A. Coolen, 2017. "Nonparametric predictive inference for stock returns," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(8), pages 1333-1349, June.
    16. Gleason, Katherine I. & Klock, Mark, 2006. "Intangible capital in the pharmaceutical and chemical industry," The Quarterly Review of Economics and Finance, Elsevier, vol. 46(2), pages 300-314, May.
    17. Linton, O. & Wu, J., 2016. "A coupled component GARCH model for intraday and overnight volatility," Cambridge Working Papers in Economics 1671, Faculty of Economics, University of Cambridge.
    18. Kim-Leng Goh & Kim-Lian Kok, 2006. "Beating the Random Walk: Intraday Seasonality and Volatility in a Developing Stock Market," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 5(1), pages 41-59, April.
    19. Pesaran, M.H. & Timmermann, A., 2004. "‘Real Time Econometrics’," Cambridge Working Papers in Economics 0432, Faculty of Economics, University of Cambridge.
    20. Powell, John G. & Shi, Jing & Smith, Tom & Whaley, Robert E., 2009. "Political regimes, business cycles, seasonalities, and returns," Journal of Banking & Finance, Elsevier, vol. 33(6), pages 1112-1128, June.
    21. Joseph P & Romano & Azeem M. Shaikh & Michael Wolf, 2005. "Formalized Data Snooping Based on Generalized Error Rates," IEW - Working Papers 259, Institute for Empirical Research in Economics - University of Zurich.
    22. Oded Galor & Omer Moav, 2005. "Land Inequality and the Origin of Divergence and Overtaking in the Growth Process: Theory and Evidence," 2005 Meeting Papers 24, Society for Economic Dynamics.
    23. Cummins, Mark & Dowling, Michael & Lucey, Brian M., 2015. "Behavioral influences in non-ferrous metals prices," Resources Policy, Elsevier, vol. 45(C), pages 9-22.
    24. Adam Zaremba & Jacob Koby Shemer, 2018. "Price-Based Investment Strategies," Springer Books, Springer, number 978-3-319-91530-2, September.
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    61. Dragan Tevdovski & Martin Mihajlov & Igor Sazdovski, 2012. "The Day Of The Week Effect In South Eastern Europe Stock Markets," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 3, pages 20-24, September.
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    67. Baur, Dirk G. & Dichtl, Hubert & Drobetz, Wolfgang & Wendt, Viktoria-Sophie, 2020. "Investing in gold – Market timing or buy-and-hold?," International Review of Financial Analysis, Elsevier, vol. 71(C).
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  47. Perez-Quiros, Gabriel & Timmermann, Allan, 2001. "Business cycle asymmetries in stock returns: Evidence from higher order moments and conditional densities," Journal of Econometrics, Elsevier, vol. 103(1-2), pages 259-306, July.
    See citations under working paper version above.
  48. Timmermann, Allan, 2001. "Structural Breaks, Incomplete Information, and Stock Prices," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(3), pages 299-314, July.
    See citations under working paper version above.
  49. Pesaran, M Hashem & Timmermann, Allan, 2000. "A Recursive Modelling Approach to Predicting UK Stock Returns," Economic Journal, Royal Economic Society, vol. 110(460), pages 159-191, January.
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  50. Timmermann, Allan, 2000. "Moments of Markov switching models," Journal of Econometrics, Elsevier, vol. 96(1), pages 75-111, May.
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  51. Lunde, Asger & Timmermann, Allan & Blake, David, 1999. "The hazards of mutual fund underperformance: A Cox regression analysis," Journal of Empirical Finance, Elsevier, vol. 6(2), pages 121-152, April.
    See citations under working paper version above.
  52. Clive Granger & Allan Timmermann, 1999. "Data mining with local model specification uncertainty: a discussion of Hoover and Perez," Econometrics Journal, Royal Economic Society, vol. 2(2), pages 220-225.

    Cited by:

    1. Teodosio Perez-Amaral & Giampiero M. Gallo & Halbert White, 2003. "Flexible Tool for Model Building: the Relevant Transformation of the Inputs Network Approach (RETINA)," Documentos de Trabajo del ICAE 0309, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    2. Lorenzo Bencivelli & Massimiliano Marcellino & Gianluca Moretti, 2017. "Forecasting economic activity by Bayesian bridge model averaging," Empirical Economics, Springer, vol. 53(1), pages 21-40, August.
    3. Marco Aiolfi & Carlo Ambrogio Favero, "undated". "Model Uncertainty, Thick Modelling and the predictability of Stock Returns," Working Papers 221, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    4. Beenstock, Michael & Szpiro, George, 2002. "Specification search in nonlinear time-series models using the genetic algorithm," Journal of Economic Dynamics and Control, Elsevier, vol. 26(5), pages 811-835, May.
    5. Bauwens, Luc & Sucarrat, Genaro, 2010. "General-to-specific modelling of exchange rate volatility: A forecast evaluation," International Journal of Forecasting, Elsevier, vol. 26(4), pages 885-907, October.
    6. Alvaro Escribano & Genaro Sucarrat, 2011. "Automated model selection in finance: General-to-speci c modelling of the mean and volatility speci cations," Working Papers 2011-09, Instituto Madrileño de Estudios Avanzados (IMDEA) Ciencias Sociales.
    7. Genaro Sucarrat & Alvaro Escribano, 2012. "Automated Model Selection in Finance: General-to-Specific Modelling of the Mean and Volatility Specifications," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 74(5), pages 716-735, October.
    8. Sucarrat, Genaro & Escribano, Álvaro, 2009. "Automated financial multi-path GETS modelling," UC3M Working papers. Economics we093620, Universidad Carlos III de Madrid. Departamento de Economía.
    9. Bonnier, Jean-Baptiste, 2022. "Forecasting crude oil volatility with exogenous predictors: As good as it GETS?," Energy Economics, Elsevier, vol. 111(C).

  53. Blake, David & Lehmann, Bruce N & Timmermann, Allan, 1999. "Asset Allocation Dynamics and Pension Fund Performance," The Journal of Business, University of Chicago Press, vol. 72(4), pages 429-461, October.

    Cited by:

    1. Kirsten L MacDonald & Robert J Bianchi & Michael E Drew, 2014. "Equity risk versus retirement adequacy: Asset allocation solutions for KiwiSaver," Discussion Papers in Finance finance:201402, Griffith University, Department of Accounting, Finance and Economics.
    2. Bijapur, Mohan & Croci, Manuela & Zaidi, Rida, 2012. "Do asset regulations impede portfolio diversification? evidence from European life insurance funds," LSE Research Online Documents on Economics 56618, London School of Economics and Political Science, LSE Library.
    3. Basu, Anup & Drew, Michael, 2006. "Appropriateness of Default Investment Options in Defined Contribution Plans: The Australian Evidence," MPRA Paper 3314, University Library of Munich, Germany, revised 02 Nov 2006.
    4. Akshentseva, Ksenya (Акшенцева, Ксения) & Abramov, Alexander (Абрамов, Александр) & Chernovа, Maria (Чернова, Мария), 2015. "Problems of Formation and Evaluation of Strategies for Portfolio Investment of Pension Reserves, Accruals and Collective Investments in Russia [Проблемы Формирования И Оценки Результативности Страт," Published Papers mn24, Russian Presidential Academy of National Economy and Public Administration.
    5. Mercedes Alda, 2021. "The dilemma between fund‐style consistency and active management over the economic cycle. Evidence from pension funds," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2219-2240, April.
    6. Darolles, Serge & Vaissié, Mathieu, 2012. "The alpha and omega of fund of hedge fund added value," Journal of Banking & Finance, Elsevier, vol. 36(4), pages 1067-1078.
    7. Tonks, Ian, 2002. "Performance persistence of pension fund managers," LSE Research Online Documents on Economics 24942, London School of Economics and Political Science, LSE Library.
    8. Xiaohong Huang & Ronald Mahieu, 2012. "Performance Persistence of Dutch Pension Funds," De Economist, Springer, vol. 160(1), pages 17-34, March.
    9. Matthew Spiegel & Harry Mamaysky & Hong Zhang, 2005. "Improved Forecasting of Mutual Fund Alphas and Betas," Yale School of Management Working Papers amz2361, Yale School of Management, revised 01 Mar 2006.
    10. Alda, Mercedes & Vicente, Ruth, 2020. "Behavioural analysis of socially responsible investment managers: specialists versus non-specialists," Research in International Business and Finance, Elsevier, vol. 54(C).
    11. Fabrice Hervé, 2006. "Famille de fonds de pension, performance et persistance de la performance," Working Papers CREGO 1060903, Université de Bourgogne - CREGO EA7317 Centre de recherches en gestion des organisations.
    12. Jacobs, Heiko & Müller, Sebastian & Weber, Martin, 2014. "How should individual investors diversify? An empirical evaluation of alternative asset allocation policies," Journal of Financial Markets, Elsevier, vol. 19(C), pages 62-85.
    13. Lawrence Kryzanowski & Abdul Rahman, 2008. "Portfolio performance ambiguity and benchmark inefficiency revisited," Journal of Asset Management, Palgrave Macmillan, vol. 9(5), pages 321-332, December.
    14. Blake, David, 2003. "The United Kingdom pension system: key issues," LSE Research Online Documents on Economics 24851, London School of Economics and Political Science, LSE Library.
    15. Jiang, George J. & Yao, Tong & Yu, Tong, 2007. "Do mutual funds time the market? Evidence from portfolio holdings," Journal of Financial Economics, Elsevier, vol. 86(3), pages 724-758, December.
    16. Clare, Andrew & Sherman, Meadhbh Brid & Thomas, Steve, 2016. "Multi-asset class mutual funds: Can they time the market? Evidence from the US, UK and Canada," Research in International Business and Finance, Elsevier, vol. 36(C), pages 212-221.
    17. Harry Mamaysky & Matthew Spiegel & Hong Zhang, 2008. "Estimating the Dynamics of Mutual Fund Alphas and Betas," The Review of Financial Studies, Society for Financial Studies, vol. 21(1), pages 233-264, January.
    18. Blake, David & Timmermann, Allan & Tonks, Ian & Wermers, Russ, 2010. "Decentralized investment management: evidence from the pension fund industry," MPRA Paper 35767, University Library of Munich, Germany.
    19. Ian Tonks, 2002. "(UBS Pensions Series 1) Performance Persistence of Pension Fund Managers," FMG Discussion Papers dp423, Financial Markets Group.
    20. Keith Cuthbertson & Dirk Nitzsche & Niall O' Sullivan, 2004. "UK Mutual Fund Performance: Genuine Stock-Picking Ability or Luck," Money Macro and Finance (MMF) Research Group Conference 2004 55, Money Macro and Finance Research Group.
    21. MacLean, Leonard & Zhao, Yonggan & Ziemba, William, 2006. "Dynamic portfolio selection with process control," Journal of Banking & Finance, Elsevier, vol. 30(2), pages 317-339, February.
    22. Willie Dion Reddic, 2021. "Under pressure: investment behaviour of insurers under different financial and regulatory conditions," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 46(1), pages 1-20, January.
    23. Fischer, Andreas & Greminger, Rafael P. & Grisse, Christian & Kaufmann, Sylvia, 2021. "Portfolio rebalancing in times of stress," CEPR Discussion Papers 15777, C.E.P.R. Discussion Papers.
    24. Bijapur, Mohan & Croci, Manuela & Zaidi, Rida, 2012. "Do Asset Regulations Impede Portfolio Diversification? Evidence from European Life Insurance Funds," MPRA Paper 54265, University Library of Munich, Germany.
    25. Gökçen, Umut & Yalçın, Atakan, 2015. "The case against active pension funds: Evidence from the Turkish Private Pension System," Emerging Markets Review, Elsevier, vol. 23(C), pages 46-67.
    26. Anup K. Basu & Michael E. Drew, 2009. "The Case for Gender-Sensitive Superannuation Plan Design," Discussion Papers in Finance finance:200904, Griffith University, Department of Accounting, Finance and Economics.
    27. Maximilian Vermorken & Marc Gendebien & Alphons Vermorken & Thomas Schröder, 2013. "Skilled monkey or unlucky manager?," Journal of Asset Management, Palgrave Macmillan, vol. 14(5), pages 267-277, October.
    28. Christoph Gort & Mei Wang, 2010. "Overconfidence and Active Management," Chapters, in: Brian Bruce (ed.), Handbook of Behavioral Finance, chapter 12, Edward Elgar Publishing.
    29. Dahlquist, Magnus & Odegaard, Bernt Arne, 2018. "A Review of Norges Bank's Active Management of the Government Pension Fund Global," UiS Working Papers in Economics and Finance 2018/1, University of Stavanger.
    30. Annaert, Jan & De Ceuster, Marc J. K. & Van Hyfte, Wim, 2005. "The value of asset allocation advice: Evidence from The Economist's quarterly portfolio poll," Journal of Banking & Finance, Elsevier, vol. 29(3), pages 661-680, March.
    31. Mercedes Alda & Luis Ferruz, 2012. "The Role of Fees in Pension Fund Performance. Evidence from Spain," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 62(6), pages 518-535, December.
    32. Isabel Abinzano & Luis Muga & Rafael Santamaria, 2016. "The Role of Investor Type in the Fee Structures of Pension Plans," Journal of Financial Services Research, Springer;Western Finance Association, vol. 50(3), pages 387-417, December.
    33. Dreassi, Alberto & Miani, Stefano & Paltrinieri, Andrea, 2017. "Sovereign pension and social security reserve funds: A portfolio analysis," Global Finance Journal, Elsevier, vol. 34(C), pages 43-53.
    34. Valpy Fitzgerald, 2006. "International Risk Tolerance, Capital Market Failure and Capital Flows to Emerging Markets," WIDER Working Paper Series RP2006-35, World Institute for Development Economic Research (UNU-WIDER).
    35. Alda, Mercedes & Andreu, Laura & Sarto, José Luis, 2017. "Learning about individual managers’ performance in UK pension funds: The importance of specialization," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 654-667.
    36. Jansen, Kristy, 2021. "Essays on institutional investors, portfolio choice, and asset prices," Other publications TiSEM fd998408-d282-4e0f-b542-4, Tilburg University, School of Economics and Management.
    37. Blake, David, 2003. "UK pension fund management after Myners: the hunt for correlation begins," LSE Research Online Documents on Economics 24833, London School of Economics and Political Science, LSE Library.
    38. David R. Gallagher & Elvis Jarnecic, 2002. "The Performance of Active Australian Bond Funds," Australian Journal of Management, Australian School of Business, vol. 27(2), pages 163-185, December.
    39. Manuel Ammann & Andreas Zingg, 2008. "Investment Performance of Swiss Pension Funds and Investment Foundations," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 144(II), pages 153-195, June.
    40. Yafeh, Yishay & Kandel, Eugene & Hamdani, Assaf & Mugerman, Yevgeny, 2015. "Incentive Fees and Competition in Pension Funds: Evidence from a Regulatory Experiment in Israel," CEPR Discussion Papers 10911, C.E.P.R. Discussion Papers.
    41. Stephen Satchell & Wei Xia, 2005. "Estimation of the Risk Attitude of the Representative UK Pension Fund Investor," Birkbeck Working Papers in Economics and Finance 0509, Birkbeck, Department of Economics, Mathematics & Statistics.
    42. Hamdani, Assaf & Kandel, Eugene & Mugerman, Yevgeny & Yafeh, Yishay, 2017. "Incentive Fees and Competition in Pension Funds: Evidence from a Regulatory Experiment," Journal of Law, Finance, and Accounting, now publishers, vol. 2(1), pages 49-86, June.
    43. Dirk Broeders & Kristy Jansen, 2021. "Pension Funds and Drivers of Heterogeneous Investment Strategies," Working Papers 712, DNB.
    44. José Alvarez & Laura Andreu & Cristina Ortiz & José Sarto, 2014. "A nonparametric approach to market timing: evidence from Spanish mutual funds," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 38(1), pages 119-132, January.
    45. Lang, Gunnar & Shen, Yu & Xu, Xian, 2014. "Chinese pension fund investment efficiency: Evidence from CNCSSF stock holdings," ZEW Discussion Papers 14-007, ZEW - Leibniz Centre for European Economic Research.
    46. Anastasia Petraki & Anna Zalewska, 2017. "Jumping over a low hurdle: personal pension fund performance," Review of Quantitative Finance and Accounting, Springer, vol. 48(1), pages 153-190, January.
    47. Huang, X. & Mahieu, R.J., 2012. "Performance persistence of Dutch pension plans," Other publications TiSEM 3dba651c-bb31-443f-963c-4, Tilburg University, School of Economics and Management.
    48. Gallagher, David R. & Jarnecic, Elvis, 2004. "International equity funds, performance, and investor flows: Australian evidence," Journal of Multinational Financial Management, Elsevier, vol. 14(1), pages 81-95, February.
    49. J. Annaert & J.K. De Ceuster & W. Van Hyfte, 2002. "The Value of Asset Allocation Advice - Evidence of The Economist’s Quarterly Portfolio Poll," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 02/160, Ghent University, Faculty of Economics and Business Administration.
    50. Blake, David & Cairns, Andrew & Dowd, Kevin, 2008. "Turning pension plans into pension planes: What investment strategy designers of defined contribution pension plans can learn from commercial aircraft designers," MPRA Paper 33749, University Library of Munich, Germany.
    51. Dirk W.G.A. Broeders & Damiaan H.J. Chen & Peter A. Minderhoud & C.J. Willem Schudel, 2021. "Pension Funds' Herding," International Journal of Central Banking, International Journal of Central Banking, vol. 17(1), pages 285-330, March.
    52. Joseph Gerakos & Juhani T. Linnainmaa & Adair Morse, 2016. "Asset Managers: Institutional Performance and Smart Betas," NBER Working Papers 22982, National Bureau of Economic Research, Inc.
    53. Dariusz Stanko, 2003. "Performance Evaluation of Public Pension Funds: The Reformed Pension System in Poland," Finance 0306002, University Library of Munich, Germany.
    54. Blake, David, 2003. "Financial system requirements for successful pension reform," LSE Research Online Documents on Economics 24862, London School of Economics and Political Science, LSE Library.
    55. Manuel Ammann & Sebastian Fischer & Florian Weigert, 2018. "Risk Factor Exposure Variation and Mutual Fund Performance," Working Papers on Finance 1817, University of St. Gallen, School of Finance, revised Nov 2018.
    56. John Board & Charles Sutcliffe, 2005. "Joined-Up Pensions Policy in the UK: An Asset-Libility Model for Simultaneously Determining the Asset Allocation and Contribution Rate," ICMA Centre Discussion Papers in Finance icma-dp2005-11, Henley Business School, University of Reading.
    57. Marshall, Andrew & Tang, Leilei, 2011. "Assessing the impact of heteroskedasticity for evaluating hedge fund performance," International Review of Financial Analysis, Elsevier, vol. 20(1), pages 12-19, January.
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    59. Manuel Ammann & Christian Ehmann, 2017. "Is Governance Related to Investment Performance and Asset Allocation? Empirical Evidence from Swiss Pension Funds," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 153(3), pages 293-339, July.
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    1. J E Boylan & F R Johnston, 2003. "Optimality and robustness of combinations of moving averages," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(1), pages 109-115, January.
    2. Theodosiou, Marina, 2011. "Forecasting monthly and quarterly time series using STL decomposition," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1178-1195, October.
    3. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    4. Gardner, Everette Jr., 2006. "Exponential smoothing: The state of the art--Part II," International Journal of Forecasting, Elsevier, vol. 22(4), pages 637-666.
    5. Jan G. De Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Monash Econometrics and Business Statistics Working Papers 12/05, Monash University, Department of Econometrics and Business Statistics.
    6. Costello, Greg & Fraser, Patricia & Groenewold, Nicolaas, 2011. "House prices, non-fundamental components and interstate spillovers: The Australian experience," Journal of Banking & Finance, Elsevier, vol. 35(3), pages 653-669, March.
    7. Trond Borgersen & Dag Einar Sommervoll & Tom Wennemo, 2006. "Endogenous Housing Market Cycles," Discussion Papers 458, Statistics Norway, Research Department.
    8. Sommervoll, Dag Einar & Borgersen, Trond-Arne & Wennemo, Tom, 2010. "Endogenous housing market cycles," Journal of Banking & Finance, Elsevier, vol. 34(3), pages 557-567, March.
    9. Dag Einar Sommervoll, 2007. "Counterintuitive response to tax incentives? Mortgage interest deductions and the demand for debt," Discussion Papers 492, Statistics Norway, Research Department.
    10. Katharina Hampel & Marcus Kunz & Norbert Schanne & Ruediger Wapler & Antje Weyh, 2006. "Regional Unemployment Forecasting Using Structural Component Models With Spatial Autocorrelation," ERSA conference papers ersa06p196, European Regional Science Association.

  55. Pesaran, M Hashem & Timmermann, Allan, 1995. "Predictability of Stock Returns: Robustness and Economic Significance," Journal of Finance, American Finance Association, vol. 50(4), pages 1201-1228, September.

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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.
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    7. Tarek Zaher, 2017. "The Value of Active Investment Strategies," NFI Working Papers 2017-WP-02, Indiana State University, Scott College of Business, Networks Financial Institute.
    8. Aretz, Kevin & Bartram, Söhnke M. & Pope, Peter F., 2011. "Asymmetric Loss Functions and the Rationality of Expected Stock Returns," MPRA Paper 47343, University Library of Munich, Germany.
    9. Rossi, Barbara & Odendahl, Florens & Sekhposyan, Tatevik, 2020. "Comparing Forecast Performance with State Dependence," CEPR Discussion Papers 15217, C.E.P.R. Discussion Papers.
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    44. Carolina Fugazza & Massimo Guidolin & Giovanna Nicodano, 2009. "Time and risk diversification in real estate investments: assessing the ex post economic value," Working Papers 2009-001, Federal Reserve Bank of St. Louis.
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    371. Patrick J. Coe & M. Hashem Pesaran & Shaun P. Vahey, 2005. "The Cost Effectiveness of the UK's Sovereign Debt Portfolio," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(4), pages 467-495, August.
    372. Ran, Jimmy & Voon, Jan P. & Li, Guangzhong, 2008. "Effects of foreign currency component in monetary aggregates on money neutrality," Economics Letters, Elsevier, vol. 99(3), pages 435-438, June.
    373. Rob Bauer & Rogér Otten & Alireza Tourani Rad, 2006. "New Zealand mutual funds: measuring performance and persistence in performance," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 46(3), pages 347-363, September.
    374. Dichtl, Hubert, 2020. "Forecasting excess returns of the gold market: Can we learn from stock market predictions?," Journal of Commodity Markets, Elsevier, vol. 19(C).
    375. Hui Zeng & Ben R Marshall & Nhut H Nguyen & Nuttawat Visaltanachoti, 2022. "Are individual stock returns predictable?," Australian Journal of Management, Australian School of Business, vol. 47(1), pages 135-162, February.
    376. McMillan, David G., 2019. "Stock return predictability: Using the cyclical component of the price ratio," Research in International Business and Finance, Elsevier, vol. 48(C), pages 228-242.
    377. Stefano Gubellini, 2014. "Conditioning information and cross-sectional anomalies," Review of Quantitative Finance and Accounting, Springer, vol. 43(3), pages 529-569, October.
    378. Majumder, Debasish, 2013. "Towards an efficient stock market: Empirical evidence from the Indian market," Journal of Policy Modeling, Elsevier, vol. 35(4), pages 572-587.
    379. Bange, Mary M. & Khang, Kenneth & Miller Jr., Thomas W., 2008. "Benchmarking the performance of recommended allocations to equities, bonds, and cash by international investment houses," Journal of Empirical Finance, Elsevier, vol. 15(3), pages 363-386, June.
    380. Doug Rolph & Pu Shen, 1999. "Do the spreads between the E/P ratio and interest rates contain information on future equity market movements?," Research Working Paper 99-03, Federal Reserve Bank of Kansas City.
    381. Döpke, Jörg & Müller, Karsten & Tegtmeier, Lars, 2018. "The economic value of business cycle forecasts for potential investors – Evidence from Germany," Research in International Business and Finance, Elsevier, vol. 46(C), pages 445-461.
    382. Brad S. Trinkle, 2005. "Forecasting annual excess stock returns via an adaptive network‐based fuzzy inference system," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 13(3), pages 165-177, July.
    383. Jia Miao & Jason Laws, 2016. "Profitability Of A Simple Pairs Trading Strategy: Recent Evidences From A Global Context," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 19(04), pages 1-18, June.
    384. Athambawa Jahfer & Abdul Hameed Mulafara, 2016. "Dividend policy and share price volatility: evidence from Colombo stock market," International Journal of Managerial and Financial Accounting, Inderscience Enterprises Ltd, vol. 8(2), pages 97-108.
    385. Dewandaru, Ginanjar & Rizvi, Syed Aun & Sarkar, Kabir & Bacha, Obiyathulla & Masih, Mansur, 2014. "How do Macroeconomic Changes Impact Islamic and Conventional Equity Prices? Evidence from Developed and Emerging Countries," MPRA Paper 59587, University Library of Munich, Germany.
    386. Balvers, Ronald J. & Wu, Yangru, 2006. "Momentum and mean reversion across national equity markets," Journal of Empirical Finance, Elsevier, vol. 13(1), pages 24-48, January.
    387. Pierdzioch, Christian & Schertler, Andrea, 2005. "Investing in European Stock Markets for High-Technology Firms," Kiel Working Papers 1265, Kiel Institute for the World Economy (IfW Kiel).
    388. Chevapatrakul, Thanaset, 2013. "Return sign forecasts based on conditional risk: Evidence from the UK stock market index," Journal of Banking & Finance, Elsevier, vol. 37(7), pages 2342-2353.
    389. Bhandari, Avishek, 2020. "Long memory and fractality among global equity markets: A multivariate wavelet approach," MPRA Paper 99653, University Library of Munich, Germany.
    390. Yvon Fauvel & Alain Paquet & Christian Zimmermann, 1999. "A Survey on Interest Rate Forecasting," Cahiers de recherche CREFE / CREFE Working Papers 87, CREFE, Université du Québec à Montréal.
    391. Paye, Bradley S. & Timmermann, Allan, 2006. "Instability of return prediction models," Journal of Empirical Finance, Elsevier, vol. 13(3), pages 274-315, June.
    392. Driffill John & Kenc Turalay & Sola Martin & Spagnolo Fabio, 2009. "The Effects of Different Parameterizations of Markov-Switching in a CIR Model of Bond Pricing," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 13(1), pages 1-24, March.
    393. Christos Avdoulas & Stelios Bekiros, 2018. "Nonlinear Forecasting of Euro Area Industrial Production Using Evolutionary Approaches," Computational Economics, Springer;Society for Computational Economics, vol. 52(2), pages 521-530, August.
    394. Nyberg, Henri, 2011. "Forecasting the direction of the US stock market with dynamic binary probit models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 561-578, April.
    395. Schnaubelt, Matthias & Seifert, Oleg, 2020. "Valuation ratios, surprises, uncertainty or sentiment: How does financial machine learning predict returns from earnings announcements?," FAU Discussion Papers in Economics 04/2020, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    396. Shangkun Deng & Kazuki Yoshiyama & Takashi Mitsubuchi & Akito Sakurai, 2015. "Hybrid Method of Multiple Kernel Learning and Genetic Algorithm for Forecasting Short-Term Foreign Exchange Rates," Computational Economics, Springer;Society for Computational Economics, vol. 45(1), pages 49-89, January.
    397. Giannetti, A., 2007. "The short term predictive ability of earnings-price ratios: The recent evidence (1994-2003)," The Quarterly Review of Economics and Finance, Elsevier, vol. 47(1), pages 26-39, March.
    398. Shamsuddin, Abul F. M. & Hillier, John R., 2004. "Fundamental determinants of the Australian price-earnings multiple," Pacific-Basin Finance Journal, Elsevier, vol. 12(5), pages 565-576, November.

  56. Timmermann, Allan, 1995. "Cointegration Tests of Present Value Models with a Time-Varying Discount Factor," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(1), pages 17-31, Jan.-Marc.

    Cited by:

    1. Yen-Hsiao Chen & Lianfeng Quan, 2013. "Rational speculative bubbles in the Asian stock markets: Tests on deterministic explosive bubbles and stochastic explosive root bubbles," Journal of Asset Management, Palgrave Macmillan, vol. 14(3), pages 195-208, June.
    2. Bohl, Martin T. & Siklos, Pierre L., 2004. "The present value model of U.S. stock prices redux: a new testing strategy and some evidence," The Quarterly Review of Economics and Finance, Elsevier, vol. 44(2), pages 208-223, May.
    3. Nélson Leitão Paes & Cássio Da Nóbrega Besarria & Marcelo Eduardo Alves Da Silva, 2018. "Bubbles In The Prices Of Housing? Evidence To Brazil?S Economy," Anais do XLIV Encontro Nacional de Economia [Proceedings of the 44th Brazilian Economics Meeting] 118, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    4. Engsted, Tom & Hviid, Simon J. & Pedersen, Thomas Q., 2016. "Explosive bubbles in house prices? Evidence from the OECD countries," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 40(C), pages 14-25.
    5. A. Durre & P. Giot, 2007. "An International Analysis of Earnings, Stock Prices and Bond Yields," Post-Print hal-00171145, HAL.
    6. Ky-Hyang Yuhn & Sang Bong Kim & Joo Ha Nam, 2015. "Bubbles and the Weibull distribution: was there an explosive bubble in US stock prices before the global economic crisis?," Applied Economics, Taylor & Francis Journals, vol. 47(3), pages 255-271, January.
    7. Gallagher, Liam A & Taylor, Mark P, 2001. "Risky Arbitrage, Limits of Arbitrage, and Nonlinear Adjustment in the Dividend-Price Ratio," Economic Inquiry, Western Economic Association International, vol. 39(4), pages 524-536, October.
    8. Edward Bernard Bastiaan de Rivera y Rivera & Diógenes Manoel Leiva Martin & Emerson Fernandes Marçal & Leonardo Fernando Cruz Basso, 2012. "Present value model between prices and dividends with constant and time-varying expected returns: enterprise-level Brazilian stock market evidence from non-stationary panels," Brazilian Business Review, Fucape Business School, vol. 9(4), pages 51-86, October.
    9. Wang, Peijie & Brand, Steven, 2015. "A new approach to estimating value–income ratios with income growth and time-varying yields," European Journal of Operational Research, Elsevier, vol. 242(1), pages 182-187.
    10. Ripamonti, Alexandre, 2013. "Rational Valuation Formula (RVF) and Time Variability in Asset Rates of Return," MPRA Paper 79460, University Library of Munich, Germany.
    11. Bohl, Martin T., 2003. "Periodically collapsing bubbles in the US stock market?," International Review of Economics & Finance, Elsevier, vol. 12(3), pages 385-397.
    12. Vyacheslav Mikhed & Petr Zemcik, 2007. "Do House Prices Reflect Fundamentals? Aggregate and Panel Data Evidence," CERGE-EI Working Papers wp337, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    13. GIOT, Pierre & PETITJEAN, Mikael, 2007. "The information content of the Bond-Equity Yield Ratio: Better than a random walk?," LIDAM Reprints CORE 1982, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    14. Ripamonti, Alexandre, 2020. "Financial institutions, asymmetric information and capital structure adjustments," The Quarterly Review of Economics and Finance, Elsevier, vol. 77(C), pages 75-83.
    15. Engsted, Tom, 2006. "Explosive bubbles in the cointegrated VAR model," Finance Research Letters, Elsevier, vol. 3(2), pages 154-162, June.
    16. Cunado, J. & Gil-Alana, L.A. & de Gracia, F. Perez, 2005. "A test for rational bubbles in the NASDAQ stock index: A fractionally integrated approach," Journal of Banking & Finance, Elsevier, vol. 29(10), pages 2633-2654, October.
    17. Christophe Boucher, 2003. "Stock Market Valuation : the Role of the Macroeconomic Risk Premium," Finance 0305011, University Library of Munich, Germany.
    18. Glen Donaldson & Mark Kamstra & Lisa Kramer, 2003. "Stare down the barrel and center the crosshairs: Targeting the ex ante equity premium," FRB Atlanta Working Paper 2003-4, Federal Reserve Bank of Atlanta.
    19. John Goddard & David Mcmillan & John Wilson, 2008. "Dividends, prices and the present value model: firm-level evidence," The European Journal of Finance, Taylor & Francis Journals, vol. 14(3), pages 195-210.
    20. Kanas, Angelos, 2005. "Nonlinearity in the stock price-dividend relation," Journal of International Money and Finance, Elsevier, vol. 24(4), pages 583-606, June.
    21. Fanelli, Luca, 2002. "A new approach for estimating and testing the linear quadratic adjustment cost model under rational expectations and I(1) variables," Journal of Economic Dynamics and Control, Elsevier, vol. 26(1), pages 117-139, January.
    22. Ye, Yonggang & Chang, Tsangyao & Hung, Ken & Lu, Yang-Cheng, 2011. "Revisiting rational bubbles in the G-7 stock markets using the Fourier unit root test and the nonparametric rank test for cointegration," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 82(2), pages 346-357.
    23. Ripamonti, Alexandre, 2016. "Corwin-Schultz bid-ask spread estimator in the Brazilian stock market," MPRA Paper 79459, University Library of Munich, Germany.
    24. Priestley, Richard, 2001. "Time-varying persistence in expected returns," Journal of Banking & Finance, Elsevier, vol. 25(7), pages 1271-1286, July.
    25. Tsangyao Chang & Wen-Chi Liu, 2008. "Rational Bubbles in the Korea Stock Market? Further Evidence based on Nonlinear and Nonparametric Cointegration Tests," Economics Bulletin, AccessEcon, vol. 3(34), pages 1-12.
    26. Onour, Ibrahim, 2009. "Rational bubbles and volatility persistence in India stock market," MPRA Paper 18545, University Library of Munich, Germany.
    27. Binswanger, Mathias, 2004. "Stock returns and real activity in the G-7 countries: did the relationship change during the 1980s?," The Quarterly Review of Economics and Finance, Elsevier, vol. 44(2), pages 237-252, May.
    28. Ullah, Irfan & Ahmed, Mumtaz, 2021. "Identifying Phases of Ebullience in EFTA Stock Markets," MPRA Paper 109633, University Library of Munich, Germany.
    29. Alexandre Ripamonti & Raphael Videira & Denis Ichimura, 2020. "Asymmetric information and daily stock prices in Brazil," Estudios Gerenciales, Universidad Icesi, vol. 36(157), pages 465-472, December.
    30. Pagan, Adrian, 1996. "The econometrics of financial markets," Journal of Empirical Finance, Elsevier, vol. 3(1), pages 15-102, May.
    31. Nasseh, Alireza & Strauss, Jack, 2000. "Stock prices and domestic and international macroeconomic activity: a cointegration approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 40(2), pages 229-245.
    32. Nasseh, Alireza & Strauss, Jack, 2004. "Stock prices and the dividend discount model: did their relation break down in the 1990s?," The Quarterly Review of Economics and Finance, Elsevier, vol. 44(2), pages 191-207, May.

  57. Timmermann, Allan, 1994. "Present value models with feedback : Solutions, stability, bubbles, and some empirical evidence," Journal of Economic Dynamics and Control, Elsevier, vol. 18(6), pages 1093-1119, November.

    Cited by:

    1. 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.
    2. William R. Parke & George A. Waters, 2011. "On the Evolutionary Stability of Rational Expectations," Working Paper Series 20111002, Illinois State University, Department of Economics.
    3. Fanelli, Luca, 2006. "Multi-equational linear quadratic adjustment cost models with rational expectations and cointegration," Journal of Economic Dynamics and Control, Elsevier, vol. 30(3), pages 445-456, March.
    4. Fanelli, Luca, 2007. "Present Value Relations, Granger Noncausality, And Var Stability," Econometric Theory, Cambridge University Press, vol. 23(6), pages 1254-1260, December.
    5. Michael Brandt, Qi Zeng and Lu Zhang, 2001. "Equilibrium Stock Return Dynamics Under Alternative Rules of Learning About Hidden States," Computing in Economics and Finance 2001 41, Society for Computational Economics.
    6. Krishnamoorthy Charith & Andrey Davydenko, 2021. "Informational Value of Dividend Initiations: Impact of Cash Dividends on Share Prices of Manufacturing Companies in Sri Lanka," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 13(3), pages 1-13, March.
    7. Andrey Davydenko & Krishnamoorthy Charith, 2021. "Informationswert von Dividendenausschüttungen: Einfluss von Bardividenden auf die Aktienkurse von produzierenden Unternehmen in Sri Lanka [Informational value of dividend initiations: Impact of cas," Post-Print hal-03359177, HAL.
    8. Jovanovic, Boyan, 2008. "Bubbles In Prices Of Exhaustible Resources," Working Papers 45830, American Association of Wine Economists.
    9. Sirnes, Espen, 1997. "Theories and Tests for Bubbles," MPRA Paper 53464, University Library of Munich, Germany, revised 1997.
    10. Fanelli, Luca, 2002. "A new approach for estimating and testing the linear quadratic adjustment cost model under rational expectations and I(1) variables," Journal of Economic Dynamics and Control, Elsevier, vol. 26(1), pages 117-139, January.
    11. Parke, William R. & Waters, George A., 2007. "An evolutionary game theory explanation of ARCH effects," Journal of Economic Dynamics and Control, Elsevier, vol. 31(7), pages 2234-2262, July.
    12. Dimitris Georgoutsos & George Kouretas, 2000. "A Multivariate I(2) Cointegration Analysis Of German Hyperinflation," Working Papers 0001, University of Crete, Department of Economics, revised 00 Jul 2001.
    13. Burda, Michael C., 2021. "Valuing cryptocurrencies: Three easy pieces," IRTG 1792 Discussion Papers 2021-011, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

  58. Pesaran, M. Hashem & Timmermann, Allan G., 1994. "A generalization of the non-parametric Henriksson-Merton test of market timing," Economics Letters, Elsevier, vol. 44(1-2), pages 1-7.
    See citations under working paper version above.
  59. Timmermann, Allan, 1994. "Why do dividend yields forecast stock returns?," Economics Letters, Elsevier, vol. 46(2), pages 149-158, October.

    Cited by:

  60. Timmermann, Allan, 1994. "Can Agents Learn to Form Rational Expectations? Some Results on Convergence and Stability of Learning in the UK Stock Market," Economic Journal, Royal Economic Society, vol. 104(425), pages 777-797, July.

    Cited by:

    1. George W. Evans, 2011. "Comment on "Natural Expectations, Macroeconomic Dynamics, and Asset Pricing"," NBER Chapters, in: NBER Macroeconomics Annual 2011, Volume 26, pages 61-71, National Bureau of Economic Research, Inc.
    2. Kapetanios, George & Mitchell, James & Shin, Yongcheol, 2014. "A nonlinear panel data model of cross-sectional dependence," Journal of Econometrics, Elsevier, vol. 179(2), pages 134-157.
    3. Barucci, Emilio & Landi, Leonardo, 1996. "Speculative dynamics with bounded rationality learning," European Journal of Operational Research, Elsevier, vol. 91(2), pages 284-300, June.
    4. George W. Evans, 2012. "Comment," NBER Macroeconomics Annual, University of Chicago Press, vol. 26(1), pages 61-71.
    5. Sampson, Michael, 2003. "New Eras and Stock Market Bubbles," Structural Change and Economic Dynamics, Elsevier, vol. 14(3), pages 297-315, September.
    6. Rotheli, Tobias F., 2001. "Acquisition of costly information: an experimental study," Journal of Economic Behavior & Organization, Elsevier, vol. 46(2), pages 193-208, October.
    7. Basdevant, Olivier, 2005. "Learning process and rational expectations: An analysis using a small macro-economic model for New Zealand," Economic Modelling, Elsevier, vol. 22(6), pages 1074-1089, December.
    8. Shively, Philip A., 2007. "Asymmetric temporary and permanent stock-price innovations," Journal of Empirical Finance, Elsevier, vol. 14(1), pages 120-130, January.
    9. Massimo Guidolin, 2013. "Markov switching models in asset pricing research," Chapters, in: Adrian R. Bell & Chris Brooks & Marcel Prokopczuk (ed.), Handbook of Research Methods and Applications in Empirical Finance, chapter 1, pages 3-44, Edward Elgar Publishing.
    10. Branch, William A. & Evans, George W., 2010. "Learning about Risk and Return: A Simple Model of Bubbles and Crashes," SIRE Discussion Papers 2010-33, Scottish Institute for Research in Economics (SIRE).

  61. Pesaran, M Hashem & Timmermann, Allan, 1992. "A Simple Nonparametric Test of Predictive Performance," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(4), pages 561-565, October.
    See citations under working paper version above.

Chapters

  1. 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.
    See citations under working paper version above.Sorry, no citations of chapters recorded.

Books

  1. G. Elliott & C. Granger & A. Timmermann (ed.), 2006. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 1, number 1.

    Cited by:

    1. Maurin, Laurent & Drechsel, Katja, 2008. "Flow of conjunctural information and forecast of euro area economic activity," Working Paper Series 925, European Central Bank.
    2. 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.
    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).
    4. Stylianos Asimakopoulos & Joan Paredes & Thomas Warmedinger, 2020. "Real‐Time Fiscal Forecasting Using Mixed‐Frequency Data," Scandinavian Journal of Economics, Wiley Blackwell, vol. 122(1), pages 369-390, January.
    5. 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.
    6. Kajal Lahiri & Huaming Peng & Xuguang Simon Sheng, 2021. "Measuring Uncertainty of a Combined Forecast and Some Tests for Forecaster Heterogeneity," Working Papers 2021-005, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    7. Tu, Yundong & Yi, Yanping, 2017. "Forecasting cointegrated nonstationary time series with time-varying variance," Journal of Econometrics, Elsevier, vol. 196(1), pages 83-98.
    8. Yin, Anwen, 2015. "Forecasting and model averaging with structural breaks," ISU General Staff Papers 201501010800005727, Iowa State University, Department of Economics.
    9. Robert Lehmann, 2016. "Economic Growth and Business Cycle Forecasting at the Regional Level," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 65.
    10. Pauwels, Laurent & Radchenko, Peter & Vasnev, Andrey, 2019. "Higher Moment Constraints for Predictive Density Combinations," Working Papers BAWP-2019-01, University of Sydney Business School, Discipline of Business Analytics.
    11. Wieland, Volker & Wolters, Maik, 2013. "Forecasting and Policy Making," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 239-325, Elsevier.
    12. Christiane Baumeister & Pierre Guérin, 2020. "A Comparison of Monthly Global Indicators for Forecasting Growth," CESifo Working Paper Series 8656, CESifo.
    13. 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.
    14. 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.
    15. Wilson, Kevin J., 2017. "An investigation of dependence in expert judgement studies with multiple experts," International Journal of Forecasting, Elsevier, vol. 33(1), pages 325-336.
    16. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2017. "The contribution of jumps to forecasting the density of returns," Post-Print halshs-01442618, HAL.
    17. Henzel, Steffen R. & Mayr, Johannes, 2013. "The mechanics of VAR forecast pooling—A DSGE model based Monte Carlo study," The North American Journal of Economics and Finance, Elsevier, vol. 24(C), pages 1-24.
    18. Winkelried, Diego, 2012. "Predicting quarterly aggregates with monthly indicators," Working Papers 2012-023, Banco Central de Reserva del Perú.
    19. Jiahan Li & Ilias Tsiakas, 2016. "Equity Premium Prediction: The Role of Economic and Statistical Constraints," Working Paper series 16-25, Rimini Centre for Economic Analysis.
    20. Jennifer Castle & David Hendry & Michael P. Clements, 2014. "Robust Approaches to Forecasting," Economics Series Working Papers 697, University of Oxford, Department of Economics.
    21. Schrimpf, Andreas, 2008. "International Stock Return Predictability Under Model Uncertainty," ZEW Discussion Papers 08-048, ZEW - Leibniz Centre for European Economic Research.
    22. WAN, Shui-Ki & WANG, Shin-Huei & WOO, Chi-Keung, 2012. "Total tourist arrival forecast: aggregation vs. disaggregation," LIDAM Discussion Papers CORE 2012039, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    23. In-Koo Cho & Kenneth Kasa, 2016. "Gresham’S Law Of Model Averaging," Discussion Papers dp16-06, Department of Economics, Simon Fraser University.
    24. Faria, Gonçalo & Verona, Fabio, 2023. "Forecast combination in the frequency domain," Bank of Finland Research Discussion Papers 1/2023, Bank of Finland.
    25. Dan Zhu & Qingwei Wang & John Goddard, 2022. "A new hedging hypothesis regarding prediction interval formation in stock price forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(4), pages 697-717, July.
    26. Luci Alessi & Eric Ghysels & Luca Onorante & Richard Peach & Simon M. Potter, 2014. "Central bank macroeconomic forecasting during the global financial crisis: the European Central Bank and Federal Reserve Bank of New York experiences," Staff Reports 680, Federal Reserve Bank of New York.
    27. Knut Are Aastveit & Anne Sofie Jore & Francesco Ravazzolo, 2014. "Forecasting recessions in real time," Working Paper 2014/02, Norges Bank.
    28. Hahn, Elke & Zekaite, Zivile & de Bondt, Gabe, 2018. "ALICE: A new inflation monitoring tool," Working Paper Series 2175, European Central Bank.
    29. Özer Karagedikli & Murat Özbilgin, 2019. "Mixed in New Zealand: Nowcasting Labour Markets with MIDAS," Reserve Bank of New Zealand Analytical Notes series AN2019/04, Reserve Bank of New Zealand.
    30. Hansen, Bruce E., 2010. "Averaging estimators for autoregressions with a near unit root," Journal of Econometrics, Elsevier, vol. 158(1), pages 142-155, September.
    31. Johannes Müller-Trede & Shoham Choshen-Hillel & Meir Barneron & Ilan Yaniv, 2017. "The Wisdom of Crowds in Matters of Taste," Discussion Paper Series dp709, The Federmann Center for the Study of Rationality, the Hebrew University, Jerusalem.
    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. Davide Pettenuzzo & Francesco Ravazzolo, 2014. "Optimal portfolio choice under decision-based model combinations," Working Paper 2014/15, Norges Bank.
    34. Francesco Ravazzolo & Shaun P. Vahey, 2010. "Forecast densities for economic aggregates from disaggregate ensembles," Working Paper 2010/02, Norges Bank.
    35. Fernandez-Perez, Adrian & Fuertes, Ana-Maria & Miffre, Joëlle, 2019. "A comprehensive appraisal of style-integration methods," Journal of Banking & Finance, Elsevier, vol. 105(C), pages 134-150.
    36. Tony Chernis & Niko Hauzenberger & Florian Huber & Gary Koop & James Mitchell, 2023. "Predictive Density Combination Using a Tree-Based Synthesis Function," Working Papers 23-30, Federal Reserve Bank of Cleveland.
    37. Karlsson, Sune, 2012. "Forecasting with Bayesian Vector Autoregressions," Working Papers 2012:12, Örebro University, School of Business.
    38. Cecilia Frale & Libero Monteforte, "undated". "FaMIDAS: A Mixed Frequency Factor Model with MIDAS structure," Working Papers 3, Department of the Treasury, Ministry of the Economy and of Finance.
    39. 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.
    40. Richard K. Crump & Miro Everaert & Domenico Giannone & Sean Hundtofte, 2018. "Changing Risk-Return Profiles," Staff Reports 850, Federal Reserve Bank of New York.
    41. Salinas, David & Flunkert, Valentin & Gasthaus, Jan & Januschowski, Tim, 2020. "DeepAR: Probabilistic forecasting with autoregressive recurrent networks," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1181-1191.
    42. Christiane Baumeister & Dimitris Korobilis & Thomas K. Lee, 2022. "Energy Markets and Global Economic Conditions," The Review of Economics and Statistics, MIT Press, vol. 104(4), pages 828-844, October.
    43. Yu-chin Chen & Kwok Ping Tsang & Wen Jen Tsay, 2010. "Home Bias in Currency Forecasts," Working Papers 272010, Hong Kong Institute for Monetary Research.
    44. Jan Prüser, 2019. "Adaptive learning from model space," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(1), pages 29-38, January.
    45. 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.
    46. Čapek, Jan & Crespo Cuaresma, Jesús & Hauzenberger, Niko & Reichel, Vlastimil, 2023. "Macroeconomic forecasting in the euro area using predictive combinations of DSGE models," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1820-1838.
    47. John Geweke & Gianni Amisano, 2008. "Optimal Prediction Pools," Working Paper series 22_08, Rimini Centre for Economic Analysis.
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