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Christian Conrad

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.

Working papers

  1. Conrad, Christian & Lahiri, Kajal, 2024. "Heterogeneous Expectations among Professional Forecasters," Working Papers 0754, University of Heidelberg, Department of Economics.

    Cited by:

    1. Ilhan Kilic & Faruk Balli, 2024. "Measuring economic country-specific uncertainty in Türkiye," Empirical Economics, Springer, vol. 67(4), pages 1649-1689, October.

  2. Christian Conrad & Zeno Enders & Alexander Glas, 2020. "The Role of Information and Experience for Households' Inflation Expectations," CESifo Working Paper Series 8528, CESifo.

    Cited by:

    1. Lena Dräger & Michael J. Lamla, 2024. "Consumers' macroeconomic expectations," Journal of Economic Surveys, Wiley Blackwell, vol. 38(2), pages 427-451, April.
    2. Ehrmann, Michael & Wabitsch, Alena, 2022. "Central bank communication with non-experts – A road to nowhere?," Journal of Monetary Economics, Elsevier, vol. 127(C), pages 69-85.
    3. Jonas Dovern & Alexander Glas & Geoff Kenny, 2024. "Testing for differences in survey‐based density expectations: A compositional data approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(6), pages 1104-1122, September.
    4. Lena Dräger, 2023. "Central Bank Communication with the General Public," CESifo Working Paper Series 10713, CESifo.
    5. Bjerkander, Lena & Glas, Alexander, 2024. "Talking in a language that everyone can understand? Clarity of speeches by the ECB Executive Board," Journal of International Money and Finance, Elsevier, vol. 149(C).
    6. Cato, Misina & Schmidt, Tobias, 2023. "Households' expectations and regional COVID-19 dynamics," Discussion Papers 02/2023, Deutsche Bundesbank.
    7. Basse, Tobias & Wegener, Christoph, 2022. "Inflation expectations: Australian consumer survey data versus the bond market," Journal of Economic Behavior & Organization, Elsevier, vol. 203(C), pages 416-430.
    8. Di Pace, Federico & Mangiante, Giacomo & Masolo, Riccardo M., 2025. "Do firm expectations respond to monetary policy announcements?," Journal of Monetary Economics, Elsevier, vol. 149(C).
    9. Julien Pinter & Evzen Kocenda, 2021. "Media Treatment of Monetary Policy Surprises and Their Impact on Firms' and Consumers' Expectations," Working Papers IES 2021/30, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Sep 2021.
    10. Couture, Cody & Owen, Ann L., 2022. "Police-Involved Killings and the Black-White Gap in Economic Expectations," MPRA Paper 115663, University Library of Munich, Germany.
    11. Becker, Christoph & Dürsch, Peter & Eife, Thomas A. & Glas, Alexander, 2023. "Households' probabilistic inflation expectations in high-inflation regimes," FAU Discussion Papers in Economics 01/2023, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    12. Donato Masciandaro & Oana Peia & Davide Romelli, 2022. "Central Bank Communication and Social Media: From Silence to Twitter," BAFFI CAREFIN Working Papers 22187, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    13. Sheen, Jeffrey & Wang, Ben Zhe, 2023. "Do monetary condition news at the zero lower bound influence households’ expectations and readiness to spend?," European Economic Review, Elsevier, vol. 152(C).
    14. Zeno Enders & Franziska Hünnekes & Gernot Müller, 2022. "Firm Expectations and Economic Activity," Journal of the European Economic Association, European Economic Association, vol. 20(6), pages 2396-2439.
    15. Dovern, Jonas, 2024. "Eliciting expectation uncertainty from private households," International Journal of Forecasting, Elsevier, vol. 40(1), pages 113-123.
    16. Peter Kwame Kuutol & Josue Mbonigaba & Rufaro Garidzirai, 2024. "Financial Literacy and Financial Well-Being in Rural Households in Ghana: The Role of Financial Information Consumption," Sustainability, MDPI, vol. 16(19), pages 1-24, September.
    17. Michael J. Lamla & Dmitri V. Vinogradov, 2021. "Is the Word of a Gentleman as Good as His Tweet? Policy communications of the Bank of England," Working Paper Series in Economics 403, University of Lüneburg, Institute of Economics.
    18. Stanisławska, Ewa & Paloviita, Maritta, 2024. "Heterogeneous responsiveness of consumers’ medium-term inflation expectations," Economics Letters, Elsevier, vol. 237(C).
    19. Katharina Allinger & Fabio Rumler, 2023. "Inflation Expectations in CESEE: The Role of Sentiment and Experiences (Katharina Allinger, Fabio Rumler)," Working Papers 247, Oesterreichische Nationalbank (Austrian Central Bank).
    20. Schmidt, Tobias, 2025. "Narrating inflation: How German economic journalists explain post-covid price rises," DoCMA Working Papers 14, TU Dortmund University, Dortmund Center for Data-based Media Analysis (DoCMA).
    21. Herzog, Bodo, 2023. "How credible is average and symmetric inflation targeting in an episode of high inflation?," Economic Analysis and Policy, Elsevier, vol. 80(C), pages 1750-1761.
    22. Müller, Lena Sophia & Glas, Alexander, 2021. "Talking in a language that everyone can understand? Transparency of speeches by the ECB Executive Board," VfS Annual Conference 2021 (Virtual Conference): Climate Economics 242364, Verein für Socialpolitik / German Economic Association.
    23. Агамбаева Саида // Agambayeva Saida & Конурбаева Наталья // Konurbayeva Natalya, 2022. "Финансовая грамотность и инфляционные ожидания домашних хозяйств // Financial literacy and inflation expectations of households," Working Papers #2022-7, National Bank of Kazakhstan.
    24. Kyriazis, Nikolaos & Papadamou, Stephanos & Tzeremes, Panayiotis & Corbet, Shaen, 2024. "Examining spillovers and connectedness among commodities, inflation, and uncertainty: A quantile-VAR framework," Energy Economics, Elsevier, vol. 133(C).
    25. Isabel Gameiro & Rita Duarte & Ildeberta Abreu, 2024. "Reaching out to the general public: a challenging journey for central banks," Economic Bulletin and Financial Stability Report Articles and Banco de Portugal Economic Studies, Banco de Portugal, Economics and Research Department.
    26. Kieren, Pascal & König-Kersting, Christian & Schmidt, Robert J. & Trautmann, Stefan T. & Theurich, Franziska, 2024. "First-order and higher-order inflation expectations: Evidence about households and firms," Discussion Papers 18/2024, Deutsche Bundesbank.
    27. Go Fujii & Shogo Nakano & Kosuke Takatomi, 2025. "Households' Medium- to Long-Term Inflation Expectations Formation: The Role of Past Experience and Inflation Regimes," Bank of Japan Working Paper Series 25-E-6, Bank of Japan.
    28. Knut Are Aastveit & Hilde C. Bjørnland & Jamie L. Cross & Helene Olsen, 2024. "Unveiling inflation: Oil Shocks, Supply Chain Pressures, and Expectations," Working Papers No 05/2024, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    29. Conrad, Christian & Enders, Zeno, 2024. "Die Grenzen der EZB-Prognosen," Working Papers 0747, University of Heidelberg, Department of Economics.
    30. Helder Ferreira de Mendonça & Cristiane Nascimento de Lima, 2023. "Does central bank credibility from professional forecasters and consumers affect the interest rate and its expectations?," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 51(4), pages 895-918, October.
    31. Lehmann-Hasemeyer, Sibylle & Neumayer, Andreas & Streb, Jochen, 2023. "Heterogeneous inflation and deflation experiences and savings decisions during German industrialization," Journal of Banking & Finance, Elsevier, vol. 154(C).
    32. Bottone, Marco & Tagliabracci, Alex & Zevi, Giordano, 2021. "What do Italian households know about the ECB’s target?," Economics Letters, Elsevier, vol. 207(C).
    33. Assenmacher, Katrin & Glöckler, Gabriel & Holton, Sarah & Trautmann, Peter & Ioannou, Demosthenes & Mee, Simon & Alonso, Conception & Argiri, Eleni & Arigoni, Filippo & Bakk-Simon, Klára & Bergbauer, , 2021. "Clear, consistent and engaging: ECB monetary policy communication in a changing world," Occasional Paper Series 274, European Central Bank.
    34. Perico Ortiz, Daniel, 2023. "Inflation news coverage, expectations and risk premium," FAU Discussion Papers in Economics 05/2023, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    35. Daria Minina & Gabriele Galati & Richhild Moessner & Maarten van Rooij, 2024. "The effect of information on consumer inflation expectations," Working Papers 810, DNB.

  3. Conrad, Christian & Schienle, Melanie, 2019. "Testing for an omitted multiplicative long-term component in GARCH models," Working Paper Series in Economics 121, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.

    Cited by:

    1. Yun-Shi Dai & Peng-Fei Dai & Wei-Xing Zhou, 2024. "The impact of geopolitical risk on the international agricultural market: Empirical analysis based on the GJR-GARCH-MIDAS model," Papers 2404.01641, arXiv.org.
    2. Cristina Amado & Annastiina Silvennoinen & Timo Ter¨asvirta, 2018. "Models with Multiplicative Decomposition of Conditional Variances and Correlations," NIPE Working Papers 07/2018, NIPE - Universidade do Minho.
    3. Wu, Xinyu & Xie, Haibin, 2021. "A realized EGARCH-MIDAS model with higher moments," Finance Research Letters, Elsevier, vol. 38(C).
    4. Jian Liu & Ziting Zhang & Lizhao Yan & Fenghua Wen, 2021. "Forecasting the volatility of EUA futures with economic policy uncertainty using the GARCH-MIDAS model," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-19, December.
    5. Amendola, Alessandra & Candila, Vincenzo & Gallo, Giampiero M., 2021. "Choosing the frequency of volatility components within the Double Asymmetric GARCH–MIDAS–X model," Econometrics and Statistics, Elsevier, vol. 20(C), pages 12-28.
    6. Christian Conrad & Robert F. Engle, 2025. "Modelling Volatility Cycles: The MF2‐GARCH Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 40(4), pages 438-454, June.
    7. Conrad, Christian & Hartmann, Matthias, 2019. "On the determinants of long-run inflation uncertainty: Evidence from a panel of 17 developed economies," European Journal of Political Economy, Elsevier, vol. 56(C), pages 233-250.
    8. Afees A. Salisu & Wenting Liao & Rangan Gupta & Oguzhan Cepni, 2023. "Economic Conditions and Predictability of US Stock Returns Volatility: Local Factor versus National Factor in a GARCH-MIDAS Model," Working Papers 202323, University of Pretoria, Department of Economics.
    9. Vincenzo Candila & Giampiero M. Gallo & Lea Petrella, 2020. "Mixed--frequency quantile regressions to forecast Value--at--Risk and Expected Shortfall," Papers 2011.00552, arXiv.org, revised Mar 2023.
    10. Conrad, Christian & Glas, Alexander, 2018. "‘Déjà vol’ revisited: Survey forecasts of macroeconomic variables predict volatility in the cross-section of industry portfolios," Working Papers 0655, University of Heidelberg, Department of Economics.
    11. Christian Francq & Baye Matar Kandji & Jean-Michel Zakoian, 2022. "Inference on Multiplicative Component GARCH without any Small-Order Moment," Working Papers 2022-09, Center for Research in Economics and Statistics.

  4. Conrad, Christian & Stuermer, Karin, 2017. "On the economic determinants of optimal stock-bond portfolios: international evidence," Working Papers 0636, University of Heidelberg, Department of Economics.

    Cited by:

    1. Nguyen, Hoang & Virbickaitė, Audronė, 2023. "Modeling stock-oil co-dependence with Dynamic Stochastic MIDAS Copula models," Energy Economics, Elsevier, vol. 124(C).
    2. Ermolov, Andrey, 2022. "Time-varying risk of nominal bonds: How important are macroeconomic shocks?," Journal of Financial Economics, Elsevier, vol. 145(1), pages 1-28.
    3. Skintzi, Vasiliki, 2017. "Determinants of stock-bond market comovement in the Eurozone under model uncertainty," MPRA Paper 78278, University Library of Munich, Germany.
    4. S. Yfanti & M. Karanasos & J. Wu & P. Vourvachis, 2025. "Short- and long-run cross-border European sustainability interdependences," Annals of Operations Research, Springer, vol. 347(1), pages 579-610, April.

  5. Conrad, Christian & Loch, Karin, 2016. "Macroeconomic expectations and the time-varying stock-bond correlation: international evidence," VfS Annual Conference 2016 (Augsburg): Demographic Change 145530, Verein für Socialpolitik / German Economic Association.

    Cited by:

    1. Nguyen, Hoang & Virbickaitė, Audronė, 2023. "Modeling stock-oil co-dependence with Dynamic Stochastic MIDAS Copula models," Energy Economics, Elsevier, vol. 124(C).
    2. Skintzi, Vasiliki, 2017. "Determinants of stock-bond market comovement in the Eurozone under model uncertainty," MPRA Paper 78278, University Library of Munich, Germany.
    3. Allard, Anne-Florence & Iania, Leonardo & Smedts, Kristien, 2020. "Stock-bond return correlations: Moving away from “one-frequency-fits-all” by extending the DCC-MIDAS approach," International Review of Financial Analysis, Elsevier, vol. 71(C).

  6. Conrad, Christian & Mammen , Enno, 2015. "Asymptotics for parametric GARCH-in-Mean Models," Working Papers 0579, University of Heidelberg, Department of Economics.

    Cited by:

    1. Alessandra Canepa, & Karanasos, Menelaos & Paraskevopoulos, Athanasios & Chini, Emilio Zanetti, 2022. "Forecasting Ination: A GARCH-in-Mean-Level Model with Time Varying Predictability," Department of Economics and Statistics Cognetti de Martiis. Working Papers 202212, University of Turin.
    2. Fengler, Matthias & Melnikov, Alexander, 2017. "GARCH option pricing models with Meixner innovations," Economics Working Paper Series 1702, University of St. Gallen, School of Economics and Political Science.
    3. Troug, Haytem Ahmed & Murray, Matt, 2015. "Crisis Determination and Financial Contagion: An Analysis of the Hong Kong and Tokyo Stock Markets using an MSBVAR Approach," MPRA Paper 68706, University Library of Munich, Germany.
    4. Canepa, Alessandra, 2024. "Inflation dynamics and persistence: The importance of the uncertainty channel," The North American Journal of Economics and Finance, Elsevier, vol. 72(C).
    5. Hafner, Christian & Kyriakopoulou, Dimitra, 2020. "Exponential-Type GARCH Models With Linear-in-Variance Risk Premium," LIDAM Reprints ISBA 2020029, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    6. Canepa, Alessandra, 2022. "Ination Dynamics and Time-Varying Persistence: The Importance of the Uncertainty Channel," Department of Economics and Statistics Cognetti de Martiis. Working Papers 202211, University of Turin.
    7. Asai, Manabu, 2023. "Feasible Panel GARCH Models: Variance-Targeting Estimation and Empirical Application," Econometrics and Statistics, Elsevier, vol. 25(C), pages 23-38.
    8. Ruili Sun & Tiefeng Ma & Shuangzhe Liu & Milind Sathye, 2019. "Improved Covariance Matrix Estimation for Portfolio Risk Measurement: A Review," JRFM, MDPI, vol. 12(1), pages 1-34, March.
    9. Dias, Gustavo Fruet, 2017. "The time-varying GARCH-in-mean model," Economics Letters, Elsevier, vol. 157(C), pages 129-132.
    10. Alessandra Canepa, & Menelaos G. Karanasos & Alexandros G. Paraskevopoulos,, 2019. "Second Order Time Dependent Inflation Persistence in the United States: a GARCH-in-Mean Model with Time Varying Coefficients," Department of Economics and Statistics Cognetti de Martiis. Working Papers 201911, University of Turin.
    11. Perera, Indeewara & Silvapulle, Mervyn J., 2023. "Bootstrap specification tests for dynamic conditional distribution models," Journal of Econometrics, Elsevier, vol. 235(2), pages 949-971.
    12. Troug, Haytem Ahmed & Murray, Matt, 2015. "Quantitative Easing in Japan and the UK An Econometric Evaluation of the Impacts of Unconventional Monetary Policy on the Returns of Aggregate Output and Price Levels," MPRA Paper 68707, University Library of Munich, Germany.

  7. Conrad, Christian & Loch, Karin, 2015. "The Variance Risk Premium and Fundamental Uncertainty," Working Papers 0583, University of Heidelberg, Department of Economics.

    Cited by:

    1. Zhenxiong Li & Marwan Izzeldin & Xingzhi Yao, 2020. "Return predictability of variance differences: A fractionally cointegrated approach," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(7), pages 1072-1089, July.
    2. Zhu, Sha & Liu, Qiuhong & Wang, Yan & Wei, Yu & Wei, Guiwu, 2019. "Which fear index matters for predicting US stock market volatilities: Text-counts or option based measurement?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    3. Peter Reinhard Hansen & Zhuo Huang & Chen Tong & Tianyi Wang, 2024. "Realized GARCH, CBOE VIX, and the Volatility Risk Premium," Journal of Financial Econometrics, Oxford University Press, vol. 22(1), pages 187-223.
    4. Reckling, Dennis, 2016. "Variance risk premia in CO2 markets: A political perspective," Energy Policy, Elsevier, vol. 94(C), pages 345-354.
    5. Tim Bollerslev & Andrew J. Patton & Rogier Quaedvlieg, 2015. "Exploiting the Errors: A Simple Approach for Improved Volatility Forecasting," CREATES Research Papers 2015-14, Department of Economics and Business Economics, Aarhus University.
    6. Ruobing Liu & Jianhui Yang & Chuan-Yang Ruan, 2019. "The Impact of Macroeconomic News on Chinese Futures," IJFS, MDPI, vol. 7(4), pages 1-14, October.
    7. Slim, Skander & Dahmene, Meriam & Boughrara, Adel, 2020. "How informative are variance risk premium and implied volatility for Value-at-Risk prediction? International evidence," The Quarterly Review of Economics and Finance, Elsevier, vol. 76(C), pages 22-37.
    8. Ma, Feng & Wang, Jiqian & Wahab, M.I.M. & Ma, Yuanhui, 2023. "Stock market volatility predictability in a data-rich world: A new insight," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1804-1819.
    9. Conrad, Christian & Schienle, Melanie, 2019. "Testing for an omitted multiplicative long-term component in GARCH models," Working Paper Series in Economics 121, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
    10. Pan, Zhiyuan & Wang, Yudong & Wu, Chongfeng & Yin, Libo, 2017. "Oil price volatility and macroeconomic fundamentals: A regime switching GARCH-MIDAS model," Journal of Empirical Finance, Elsevier, vol. 43(C), pages 130-142.
    11. Ma, Feng & Guo, Yangli & Chevallier, Julien & Huang, Dengshi, 2022. "Macroeconomic attention, economic policy uncertainty, and stock volatility predictability," International Review of Financial Analysis, Elsevier, vol. 84(C).
    12. Xiafei Li & Yu Wei & Xiaodan Chen & Feng Ma & Chao Liang & Wang Chen, 2022. "Which uncertainty is powerful to forecast crude oil market volatility? New evidence," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4279-4297, October.
    13. Tong Fang & Deyu Miao & Zhi Su & Libo Yin, 2023. "Uncertainty‐driven oil volatility risk premium and international stock market volatility forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 872-904, July.
    14. Conrad, Christian & Loch, Karin, 2016. "Macroeconomic expectations and the time-varying stock-bond correlation: international evidence," VfS Annual Conference 2016 (Augsburg): Demographic Change 145530, Verein für Socialpolitik / German Economic Association.
    15. Conrad, Christian & Schienle, Melanie, 2015. "Misspecification Testing in GARCH-MIDAS Models," Working Papers 0597, University of Heidelberg, Department of Economics.

  8. Conrad, Christian & Schienle, Melanie, 2015. "Misspecification Testing in GARCH-MIDAS Models," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112919, Verein für Socialpolitik / German Economic Association.

    Cited by:

    1. Conrad, Christian & Kleen, Onno, 2016. "On the statistical properties of multiplicative GARCH models," Working Papers 0613, University of Heidelberg, Department of Economics.

  9. Conrad, Christian & Schienle, Melanie, 2015. "Misspecification Testing in GARCH-MIDAS Models," Working Papers 0597, University of Heidelberg, Department of Economics.

    Cited by:

    1. Conrad, Christian & Kleen, Onno, 2016. "On the statistical properties of multiplicative GARCH models," Working Papers 0613, University of Heidelberg, Department of Economics.

  10. Conrad, Christian & Hartmann, Matthias, 2014. "Cross-sectional evidence on the relation between monetary policy, macroeconomic conditions and low-frequency inflation uncertainty," Working Papers 0574, University of Heidelberg, Department of Economics.

    Cited by:

    1. Zied Ftiti & Abdelkader Aguir & Mounir Smida, 2017. "Time-inconsistency and expansionary business cycle theories: What does matter for the central bank independence–inflation relationship?," Post-Print hal-01746100, HAL.
    2. Glas, Alexander & Hartmann, Matthias, 2016. "Inflation uncertainty, disagreement and monetary policy: Evidence from the ECB Survey of Professional Forecasters," VfS Annual Conference 2016 (Augsburg): Demographic Change 145888, Verein für Socialpolitik / German Economic Association.

  11. Conrad, Christian & Weber, Enzo, 2013. "Measuring Persistence in Volatility Spillovers," Working Papers 0543, University of Heidelberg, Department of Economics.

    Cited by:

    1. Karanasos, Menelaos & Paraskevopoulos, Alexandros G. & Menla Ali, Faek & Karoglou, Michail & Yfanti, Stavroula, 2014. "Modelling stock volatilities during financial crises: A time varying coefficient approach," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 113-128.
    2. Pedersen, Rasmus Søndergaard, 2017. "Inference and testing on the boundary in extended constant conditional correlation GARCH models," Journal of Econometrics, Elsevier, vol. 196(1), pages 23-36.
    3. Francq, Christian & Sucarrat, Genaro, 2015. "Equation-by-Equation Estimation of a Multivariate Log-GARCH-X Model of Financial Returns," MPRA Paper 67140, University Library of Munich, Germany.
    4. Eraslan, Sercan & Ali, Faek Menla, 2017. "Financial crises and the dynamic linkages between stock and bond returns," Discussion Papers 17/2017, Deutsche Bundesbank.
    5. Karanasos, Menelaos & Menla Ali, Faek & Margaronis, Zannis & Nath, Rajat, 2018. "Modelling time varying volatility spillovers and conditional correlations across commodity metal futures," International Review of Financial Analysis, Elsevier, vol. 57(C), pages 246-256.
    6. Xiaochun Liu, 2018. "Structural Volatility Impulse Response Function and Asymptotic Inference," Journal of Financial Econometrics, Oxford University Press, vol. 16(2), pages 316-339.

  12. Conrad, Christian & Zumbach, Klaus Ulrich, 2012. "The Effect of Political Communication on European Financial Markets during the Sovereign Debt Crisis," Working Papers 0536, University of Heidelberg, Department of Economics.

    Cited by:

    1. Julia Wolfinger & Lars P. Feld & Ekkehard A. Köhler & Tobias Thomas, 2018. "57 Channels (And Nothin On) - Does TV-News on the Eurozone Affect Government Bond Yield Spreads?," CESifo Working Paper Series 7437, CESifo.
    2. Hirsch, Patrick & Köhler, Ekkehard A. & Feld, Lars P. & Thomas, Tobias, 2020. ""Whatever it takes!": How tonality of TV-news affects government bond yield spreads during crises," Freiburg Discussion Papers on Constitutional Economics 20/9, Walter Eucken Institut e.V..
    3. Li, Kun, 2018. "Reaction to news in the Chinese stock market: A study on Xiong’an New Area Strategy," Journal of Behavioral and Experimental Finance, Elsevier, vol. 19(C), pages 36-38.
    4. Adrián Fernandez-Perez & Marta Gómez-Puig & Simón Sosvilla-Rivero, 2025. "Examining the transmission of credit and liquidity risks: A network analysis for EMU sovereign debt markets," IREA Working Papers 202504, University of Barcelona, Research Institute of Applied Economics.
    5. Patrick Hirsch & Lars P. Feld & Ekkehard A. Köhler & Tobias Thomas, 2024. "“Whatever It Takes!” How Tonality of TV-News Affected Government Bond Yield Spreads during the European Debt Crisis," CESifo Working Paper Series 10980, CESifo.
    6. Clancy, Daragh & Gabriele, Carmine & Žigraiová, Diana, 2022. "Sovereign bond market spillovers from crisis-time developments in Greece," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 78(C).
    7. Conrad, Christian & Stuermer, Karin, 2017. "On the economic determinants of optimal stock-bond portfolios: international evidence," Working Papers 0636, University of Heidelberg, Department of Economics.
    8. Philipp Mohl & Gilles Mourre & Sven Langedijk & Martijn Hoogeland, 2021. "Does Media Visibility Make EU Fiscal Rules More Effective?," European Economy - Discussion Papers 155, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.

  13. Conrad, Christian & Eife, Thomas A., 2012. "Explaining Inflation-Gap Persistence by a Time-Varying Taylor Rule," Working Papers 0521, University of Heidelberg, Department of Economics.

    Cited by:

    1. Bogdan CAPRARU & Norel Ionut MOISE & Andrei RADULESCU, 2015. "The Monetary Policy Of The National Bank Of Romania In The Inflation Targeting Era. A Taylor Rule Approach," Review of Economic and Business Studies, Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, issue 16, pages 91-102, December.
    2. Yosra Baaziz, 2015. "Estimating Interest Rate Setting Behavior in Brazil: A LSTR Model Approach," Economies, MDPI, vol. 3(2), pages 1-17, April.
    3. Yanli LI, Hongfeng PENG & Hongfeng PENG, 2013. "Inflation Persistence in Nine Latin American Countries: Panel SURKSS Test with a Fourier Function," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 132-143, October.
    4. Clarida, Richard & Galí, Jordi & Gertler, Mark, 1999. "The Science of Monetary Policy: A New Keynesian Perspective," CEPR Discussion Papers 2139, C.E.P.R. Discussion Papers.
    5. Hartmann, Matthias & Conrad, Christian, 2014. "Cross sectional evidence on the relation between monetary policy, macroeconomic conditions and low-frequency inflation uncertainty," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100477, Verein für Socialpolitik / German Economic Association.
    6. Guizhou Wang & Kjell Hausken, 2023. "Modeling which Factors Impact Interest Rates," Journal of Central Banking Theory and Practice, Central bank of Montenegro, vol. 12(2), pages 211-237.
    7. Christina Anderl & Guglielmo Maria Caporale, 2023. "Time-Varying Parameters in Monetary Policy Rules: A GMM Approach," CESifo Working Paper Series 10451, CESifo.
    8. Geronikolaou, George & Spyromitros, Eleftherios & Tsintzos, Panagiotis, 2016. "Inflation persistence: The path of labor market structural reforms," Economic Modelling, Elsevier, vol. 58(C), pages 317-322.
    9. Conrad, Christian & Hartmann, Matthias, 2019. "On the determinants of long-run inflation uncertainty: Evidence from a panel of 17 developed economies," European Journal of Political Economy, Elsevier, vol. 56(C), pages 233-250.
    10. Shih‐Tang Hwu & Chang‐Jin Kim, 2019. "Estimating Trend Inflation Based on Unobserved Components Model: Is It Correlated with the Inflation Gap?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 51(8), pages 2305-2319, December.
    11. Glas, Alexander & Hartmann, Matthias, 2016. "Inflation uncertainty, disagreement and monetary policy: Evidence from the ECB Survey of Professional Forecasters," VfS Annual Conference 2016 (Augsburg): Demographic Change 145888, Verein für Socialpolitik / German Economic Association.
    12. Edward N. Gamber & Jeffrey P. Liebner & Julie K. Smith, 2013. "Inflation Persistence: Revisited," Working Papers 2013-002, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    13. Baaziz, Yosra & Labidi, Moez & Lahiani, Amine, 2013. "Does the South African Reserve Bank follow a nonlinear interest rate reaction function?," Economic Modelling, Elsevier, vol. 35(C), pages 272-282.
    14. Donayre, Luiggi & Panovska, Irina, 2018. "U.S. wage growth and nonlinearities: The roles of inflation and unemployment," Economic Modelling, Elsevier, vol. 68(C), pages 273-292.
    15. Yosra Baaziz & Moez Labidi, 2016. "Nonlinear Monetary Policy Rules: An Essay in the Comparative Study on Egyptian and Tunisian Central Banks," Economies, MDPI, vol. 4(2), pages 1-18, April.

  14. Conrad, Christian & Loch, Karin & Rittler, Daniel, 2012. "On the Macroeconomic Determinants of the Long-Term Oil-Stock Correlation," Working Papers 0525, University of Heidelberg, Department of Economics.

    Cited by:

    1. Hossein Asgharian & Charlotte Christiansen & Ai Jun Hou, 2016. "Macro-Finance Determinants of the Long-Run Stock–Bond Correlation: The DCC-MIDAS Specification," Journal of Financial Econometrics, Oxford University Press, vol. 14(3), pages 617-642.
    2. Conrad, Christian & Loch, Karin, 2012. "Anticipating Long-Term Stock Market Volatility," Working Papers 0535, University of Heidelberg, Department of Economics.
    3. Julien, Chevallier & Sévi, Benoît, 2013. "A Fear Index to Predict Oil Futures Returns," Energy: Resources and Markets 156489, Fondazione Eni Enrico Mattei (FEEM).
    4. Turhan, M. Ibrahim & Sensoy, Ahmet & Ozturk, Kevser & Hacihasanoglu, Erk, 2014. "A view to the long-run dynamic relationship between crude oil and the major asset classes," International Review of Economics & Finance, Elsevier, vol. 33(C), pages 286-299.
    5. Emiliano Magrini & Ayca Donmez, 2013. "Agricultural Commodity Price Volatility and Its Macroeconomic Determinants: A GARCH-MIDAS Approach," JRC Research Reports JRC84138, Joint Research Centre.
    6. Mo, Di & Gupta, Rakesh & Li, Bin & Singh, Tarlok, 2018. "The macroeconomic determinants of commodity futures volatility: Evidence from Chinese and Indian markets," Economic Modelling, Elsevier, vol. 70(C), pages 543-560.

  15. Conrad, Christian & Loch, Karin, 2012. "Anticipating Long-Term Stock Market Volatility," Working Papers 0535, University of Heidelberg, Department of Economics.

    Cited by:

    1. Mawuli Segnon & Rangan Gupta & Bernd Wilfling, 2022. "Forecasting Stock Market Volatility with Regime-Switching GARCH-MIDAS: The Role of Geopolitical Risks," Working Papers 202203, University of Pretoria, Department of Economics.
    2. Chao Liang & Yin Liao & Feng Ma & Bo Zhu, 2022. "United States Oil Fund volatility prediction: the roles of leverage effect and jumps," Empirical Economics, Springer, vol. 62(5), pages 2239-2262, May.
    3. Dai, Zhifeng & Chang, Xiaoming, 2021. "Forecasting stock market volatility: Can the risk aversion measure exert an important role?," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    4. Hossein Asgharian & Charlotte Christiansen & Ai Jun Hou, 2016. "Macro-Finance Determinants of the Long-Run Stock–Bond Correlation: The DCC-MIDAS Specification," Journal of Financial Econometrics, Oxford University Press, vol. 14(3), pages 617-642.
    5. Rangan Gupta & Jacobus Nel & Christian Pierdzioch, 2021. "Investor Confidence and Forecastability of US Stock Market Realized Volatility : Evidence from Machine Learning," Working Papers 202118, University of Pretoria, Department of Economics.
    6. Liu, Wei & Garrett, Ian, 2023. "Regime-dependent effects of macroeconomic uncertainty on realized volatility in the U.S. stock market," Economic Modelling, Elsevier, vol. 128(C).
    7. Yun-Shi Dai & Peng-Fei Dai & Wei-Xing Zhou, 2024. "The impact of geopolitical risk on the international agricultural market: Empirical analysis based on the GJR-GARCH-MIDAS model," Papers 2404.01641, arXiv.org.
    8. Nonejad, Nima, 2022. "An interesting finding about the ability of geopolitical risk to forecast aggregate equity return volatility out-of-sample," Finance Research Letters, Elsevier, vol. 47(PB).
    9. Christian Conrad & Julius Theodor Schoelkopf & Nikoleta Tushteva, 2023. "Long-Term Volatility Shapes the Stock Market’s Sensitivity to News," Working Paper series 23-16, Rimini Centre for Economic Analysis.
    10. Nonejad, Nima, 2017. "Forecasting aggregate stock market volatility using financial and macroeconomic predictors: Which models forecast best, when and why?," Journal of Empirical Finance, Elsevier, vol. 42(C), pages 131-154.
    11. Monica Billio & Anna Petronevich, 2017. "Dynamical Interaction Between Financial and Business Cycles," Working Papers 2017:24, Department of Economics, University of Venice "Ca' Foscari".
    12. Alessandra Amendola & Marinella Boccia & Vincenzo Candila & Giampiero M. Gallo, 2020. "Energy and non–energy Commodities: Spillover Effects on African Stock Markets," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 9(4), pages 1-7.
    13. Fang, Libing & Yu, Honghai & Xiao, Wen, 2018. "Forecasting gold futures market volatility using macroeconomic variables in the United States," Economic Modelling, Elsevier, vol. 72(C), pages 249-259.
    14. Guo, Jin & Wen, Xiaoqian, 2024. "Option listing and underlying commodity futures volatility in China," Economic Modelling, Elsevier, vol. 141(C).
    15. Duc Khuong Nguyen & Thomas Walther, 2020. "Modeling and forecasting commodity market volatility with long‐term economic and financial variables," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 126-142, March.
    16. Chun, Dohyun & Cho, Hoon & Ryu, Doojin, 2023. "Discovering the drivers of stock market volatility in a data-rich world," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
    17. Cristina Amado & Annastiina Silvennoinen & Timo Ter¨asvirta, 2018. "Models with Multiplicative Decomposition of Conditional Variances and Correlations," NIPE Working Papers 07/2018, NIPE - Universidade do Minho.
    18. Vasilios Plakandaras & Rangan Gupta & Mehmet Balcilar & Qiang Ji, 2021. "Evolving United States Stock Market Volatility: The Role of Conventional and Unconventional Monetary Policies," Working Papers 202113, University of Pretoria, Department of Economics.
    19. Fang, Tong & Su, Zhi & Yin, Libo, 2020. "Economic fundamentals or investor perceptions? The role of uncertainty in predicting long-term cryptocurrency volatility," International Review of Financial Analysis, Elsevier, vol. 71(C).
    20. Tong, Chen & Huang, Zhuo & Wang, Tianyi & Zhang, Cong, 2023. "The effects of economic uncertainty on financial volatility: A comprehensive investigation," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 369-389.
    21. Amendola, Alessandra & Candila, Vincenzo & Gallo, Giampiero M., 2019. "On the asymmetric impact of macro–variables on volatility," Economic Modelling, Elsevier, vol. 76(C), pages 135-152.
    22. Virk, Nader & Javed, Farrukh & Awartani, Basel, 2021. "A reality check on the GARCH-MIDAS volatility models," Working Papers 2021:2, Örebro University, School of Business.
    23. Alexandridis, Antonios K. & Panopoulou, Ekaterini & Souropanis, Ioannis, 2024. "Forecasting exchange rate volatility: An amalgamation approach," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 97(C).
    24. Wu, Xinyu & Xie, Haibin, 2021. "A realized EGARCH-MIDAS model with higher moments," Finance Research Letters, Elsevier, vol. 38(C).
    25. Metiu, Norbert & Prieto, Esteban, 2025. "Time-varying stock return correlation, news shocks, and business cycles," European Economic Review, Elsevier, vol. 172(C).
    26. Bjoern Schulte-Tillman & Mawuli Segnon & Bernd Wilfling, 2022. "Financial-market volatility prediction with multiplicative Markov-switching MIDAS components," CQE Working Papers 9922, Center for Quantitative Economics (CQE), University of Muenster.
    27. Vincenzo Candila, 2021. "Multivariate Analysis of Cryptocurrencies," Econometrics, MDPI, vol. 9(3), pages 1-17, July.
    28. Berg, Kimberly A. & Vu, Nam T., 2019. "International spillovers of U.S. financial volatility," Journal of International Money and Finance, Elsevier, vol. 97(C), pages 19-34.
    29. Yin, Libo & Feng, Jiabao & Liu, Li & Wang, Yudong, 2019. "It's not that important: The negligible effect of oil market uncertainty," International Review of Economics & Finance, Elsevier, vol. 60(C), pages 62-84.
    30. Wang, Yuejing & Ye, Wuyi & Jiang, Ying & Liu, Xiaoquan, 2024. "Volatility prediction for the energy sector with economic determinants: Evidence from a hybrid model," International Review of Financial Analysis, Elsevier, vol. 92(C).
    31. Naimoli, Antonio, 2023. "The information content of sentiment indices in forecasting Value at Risk and Expected Shortfall: a Complete Realized Exponential GARCH-X approach," International Economics, Elsevier, vol. 176(C).
    32. Li, Tao & Ma, Feng & Zhang, Xuehua & Zhang, Yaojie, 2020. "Economic policy uncertainty and the Chinese stock market volatility: Novel evidence," Economic Modelling, Elsevier, vol. 87(C), pages 24-33.
    33. Chen, Qiang & Gong, Yuting, 2019. "The economic sources of China's CSI 300 spot and futures volatilities before and after the 2015 stock market crisis," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 102-121.
    34. Huang, Yu-Fan & Startz, Richard, 2020. "Improved recession dating using stock market volatility," International Journal of Forecasting, Elsevier, vol. 36(2), pages 507-514.
    35. Christian Conrad & Anessa Custovic & Eric Ghysels, 2018. "Long- and Short-Term Cryptocurrency Volatility Components: A GARCH-MIDAS Analysis," JRFM, MDPI, vol. 11(2), pages 1-12, May.
    36. Jian Liu & Ziting Zhang & Lizhao Yan & Fenghua Wen, 2021. "Forecasting the volatility of EUA futures with economic policy uncertainty using the GARCH-MIDAS model," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-19, December.
    37. Salisu, Afees A. & Cuñado, Juncal & Gupta, Rangan, 2022. "Geopolitical risks and historical exchange rate volatility of the BRICS," International Review of Economics & Finance, Elsevier, vol. 77(C), pages 179-190.
    38. Salisu, Afees A. & Demirer, Riza & Gupta, Rangan, 2024. "Technological shocks and stock market volatility over a century," Journal of Empirical Finance, Elsevier, vol. 79(C).
    39. Afees A. Salisu & Rangan Gupta & Elie Bouri & Qiang Ji, 2022. "Mixed‐frequency forecasting of crude oil volatility based on the information content of global economic conditions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(1), pages 134-157, January.
    40. Nonejad, Nima, 2023. "Conditional out-of-sample predictability of aggregate equity returns and aggregate equity return volatility using economic variables," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 91-122.
    41. Jiang, Cuixia & Li, Yuqian & Xu, Qifa & Liu, Yezheng, 2021. "Measuring risk spillovers from multiple developed stock markets to China: A vine-copula-GARCH-MIDAS model," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 386-398.
    42. Belcaid, Karim & El Ghini, Ahmed, 2019. "U.S., European, Chinese economic policy uncertainty and Moroccan stock market volatility," The Journal of Economic Asymmetries, Elsevier, vol. 20(C).
    43. Amendola, A. & Candila, V. & Cipollini, F. & Gallo, G.M., 2024. "Doubly multiplicative error models with long- and short-run components," Socio-Economic Planning Sciences, Elsevier, vol. 91(C).
    44. Su, Zhi & Fang, Tong & Yin, Libo, 2017. "The role of news-based implied volatility among US financial markets," Economics Letters, Elsevier, vol. 157(C), pages 24-27.
    45. Gong, Xu & Xu, Jun, 2022. "Geopolitical risk and dynamic connectedness between commodity markets," Energy Economics, Elsevier, vol. 110(C).
    46. Tong Fang & Tae-Hwy Lee & Zhi Su, 2020. "Predicting the Long-term Stock Market Volatility: A GARCH-MIDAS Model with Variable Selection," Working Papers 202009, University of California at Riverside, Department of Economics.
    47. Riza Demirer & Rangan Gupta & He Li & Yu You, 2021. "Financial Vulnerability and Volatility in Emerging Stock Markets: Evidence from GARCH-MIDAS Models," Working Papers 202112, University of Pretoria, Department of Economics.
    48. Christian Conrad & Robert F. Engle, 2025. "Modelling Volatility Cycles: The MF2‐GARCH Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 40(4), pages 438-454, June.
    49. Conrad, Christian & Hartmann, Matthias, 2019. "On the determinants of long-run inflation uncertainty: Evidence from a panel of 17 developed economies," European Journal of Political Economy, Elsevier, vol. 56(C), pages 233-250.
    50. Nonejad, Nima, 2020. "A comprehensive empirical analysis of the predictive impact of the price of crude oil on aggregate equity return volatility," Journal of Commodity Markets, Elsevier, vol. 20(C).
    51. Wu, Xinyu & Xie, Haibin & Zhang, Huanming, 2022. "Time-varying risk aversion and renminbi exchange rate volatility: Evidence from CARR-MIDAS model," The North American Journal of Economics and Finance, Elsevier, vol. 61(C).
    52. Guglielmo Maria Caporale & Menelaos Karanasos & Stavroula Yfanti, 2019. "Macro-Financial Linkages in the High-Frequency Domain: The Effects of Uncertainty on Realized Volatility," CESifo Working Paper Series 8000, CESifo.
    53. Shen, Lihua & Lu, Xinjie & Luu Duc Huynh, Toan & Liang, Chao, 2023. "Air quality index and the Chinese stock market volatility: Evidence from both market and sector indices," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 224-239.
    54. 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).
    55. Zhao, Pan & Pan, Jian & Yue, Qin & Zhang, Jinbo, 2021. "Pricing of financial derivatives based on the Tsallis statistical theory," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
    56. Conrad, Christian & Loch, Karin & Rittler, Daniel, 2012. "On the Macroeconomic Determinants of the Long-Term Oil-Stock Correlation," Working Papers 0525, University of Heidelberg, Department of Economics.
    57. Dai, Zhifeng & Zhou, Huiting & Wen, Fenghua & He, Shaoyi, 2020. "Efficient predictability of stock return volatility: The role of stock market implied volatility," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    58. Afees A. Salisu & Rangan Gupta & Elie Bouri, 2022. "Testing the Forecasting Power of Global Economic Conditions for the Volatility of International REITs using a GARCH-MIDAS Approach," Working Papers 202211, University of Pretoria, Department of Economics.
    59. Hongyu An & Boping Tian, 2025. "Unleashing the Potential of Mixed Frequency Data: Measuring Risk with Dynamic Tail Index Regression Model," Computational Economics, Springer;Society for Computational Economics, vol. 65(3), pages 1567-1615, March.
    60. Afees A. Salisu & Wenting Liao & Rangan Gupta & Oguzhan Cepni, 2023. "Economic Conditions and Predictability of US Stock Returns Volatility: Local Factor versus National Factor in a GARCH-MIDAS Model," Working Papers 202323, University of Pretoria, Department of Economics.
    61. Vincenzo Candila & Giampiero M. Gallo & Lea Petrella, 2020. "Mixed--frequency quantile regressions to forecast Value--at--Risk and Expected Shortfall," Papers 2011.00552, arXiv.org, revised Mar 2023.
    62. Bertelsen, Kristoffer Pons & Borup, Daniel & Jakobsen, Johan Stax, 2021. "Stock market volatility and public information flow: A non-linear perspective," Economics Letters, Elsevier, vol. 204(C).
    63. Afees A. Salisu & Rangan Gupta & Riza Demirer, 2021. "Global Financial Cycle and the Predictability of Oil Market Volatility: Evidence from a GARCH-MIDAS Model," Working Papers 202121, University of Pretoria, Department of Economics.
    64. Yu, Honghai & Fang, Libing & Sun, Wencong, 2018. "Forecasting performance of global economic policy uncertainty for volatility of Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 931-940.
    65. Lu, Fei & Ma, Feng & Guo, Qiang, 2023. "Less is more? New evidence from stock market volatility predictability," International Review of Financial Analysis, Elsevier, vol. 89(C).
    66. Zhou, Zhongbao & Fu, Zhangyan & Jiang, Yong & Zeng, Ximei & Lin, Ling, 2020. "Can economic policy uncertainty predict exchange rate volatility? New evidence from the GARCH-MIDAS model," Finance Research Letters, Elsevier, vol. 34(C).
    67. Naimoli, Antonio, 2022. "The information content of sentiment indices for forecasting Value at Risk and Expected Shortfall in equity markets," MPRA Paper 112588, University Library of Munich, Germany.
    68. Liu, Han & Yang, Peng & He, Yongda & Oxley, Les & Guo, Pengwei, 2024. "Exploring the influence of the geopolitical risks on the natural resource price volatility and correlation: Evidence from DCC-MIDAS-X model," Energy Economics, Elsevier, vol. 129(C).
    69. Fang, Libing & Qian, Yichuo & Chen, Ying & Yu, Honghai, 2018. "How does stock market volatility react to NVIX? Evidence from developed countries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 490-499.
    70. Ruipeng Liu & Mawuli Segnon & Rangan Gupta & Elie Bouri, 2021. "Conventional and Unconventional Monetary Policy Rate Uncertainty and Stock Market Volatility: A Forecasting Perspective," Working Papers 202178, University of Pretoria, Department of Economics.
    71. M. Karanasos & S. Yfanti & J. Hunter, 2022. "Emerging stock market volatility and economic fundamentals: the importance of US uncertainty spillovers, financial and health crises," Annals of Operations Research, Springer, vol. 313(2), pages 1077-1116, June.
    72. Su, Zhi & Fang, Tong & Yin, Libo, 2019. "Understanding stock market volatility: What is the role of U.S. uncertainty?," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 582-590.
    73. Conrad, Christian & Glas, Alexander, 2018. "‘Déjà vol’ revisited: Survey forecasts of macroeconomic variables predict volatility in the cross-section of industry portfolios," Working Papers 0655, University of Heidelberg, Department of Economics.
    74. Han Liu & Peng Yang & Haiyan Song & Doris Chenguang Wu, 2024. "Global and domestic economic policy uncertainties and tourism stock market: Evidence from China," Tourism Economics, , vol. 30(3), pages 567-591, May.
    75. Afees A. Salisu & Riza Demirer & Rangan Gupta, 2023. "Technological Shocks and Stock Market Volatility Over a Century: A GARCH-MIDAS Approach," Working Papers 202308, University of Pretoria, Department of Economics.
    76. Conrad, Christian & Schienle, Melanie, 2019. "Testing for an omitted multiplicative long-term component in GARCH models," Working Paper Series in Economics 121, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
    77. Pan, Zhiyuan & Wang, Yudong & Wu, Chongfeng & Yin, Libo, 2017. "Oil price volatility and macroeconomic fundamentals: A regime switching GARCH-MIDAS model," Journal of Empirical Finance, Elsevier, vol. 43(C), pages 130-142.
    78. Asgharian, Hossein & Christiansen, Charlotte & Hou, Ai Jun & Wang, Weining, 2021. "Long- and short-run components of factor betas: Implications for stock pricing," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    79. Liu, Zhenhua & Wang, Yushu & Yuan, Xinting & Ding, Zhihua & Ji, Qiang, 2025. "Geopolitical risk and vulnerability of energy markets," Energy Economics, Elsevier, vol. 141(C).
    80. Damien Kunjal & Faeezah Peerbhai & Paul-Francois Muzindutsi, 2022. "Political, economic, and financial country risks and the volatility of the South African Exchange Traded Fund market: A GARCH-MIDAS approach," Risk Management, Palgrave Macmillan, vol. 24(3), pages 236-258, September.
    81. Dai, Zhifeng & Zhu, Huan & Dong, Xiaodi, 2020. "Forecasting Chinese industry return volatilities with RMB/USD exchange rate," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
    82. Souropanis, Ioannis & Vivian, Andrew, 2023. "Forecasting realized volatility with wavelet decomposition," Journal of Empirical Finance, Elsevier, vol. 74(C).
    83. Hayden Brown, 2024. "Justifying the Volatility of S&P 500 Daily Returns," Papers 2403.01088, arXiv.org, revised Nov 2024.
    84. Christian Francq & Baye Matar Kandji & Jean-Michel Zakoian, 2022. "Inference on Multiplicative Component GARCH without any Small-Order Moment," Working Papers 2022-09, Center for Research in Economics and Statistics.
    85. Alain Hecq & Marie Ternes & Ines Wilms, 2023. "Hierarchical Regularizers for Reverse Unrestricted Mixed Data Sampling Regressions," Papers 2301.10592, arXiv.org, revised Nov 2024.
    86. Mawuli Segnon & Bjorn Schulte-Tillmann & Riza Demirer & Rangan Gupta, 2025. "Deglobalization and Foreign Exchange Volatility: The Role of Supply Chain Pressures," Working Papers 202506, University of Pretoria, Department of Economics.
    87. Conrad, Christian & Stuermer, Karin, 2017. "On the economic determinants of optimal stock-bond portfolios: international evidence," Working Papers 0636, University of Heidelberg, Department of Economics.
    88. Bruno Deschamps & Tianlun Fei & Ying Jiang & Xiaoquan Liu, 2022. "Procyclical volatility in Chinese stock markets," Review of Quantitative Finance and Accounting, Springer, vol. 58(3), pages 1117-1144, April.
    89. Zhang Wu & Terence Tai-Leung Chong, 2021. "Does the macroeconomy matter to market volatility? Evidence from US industries," Empirical Economics, Springer, vol. 61(6), pages 2931-2962, December.
    90. Liu, Yang & Han, Liyan & Yin, Libo, 2019. "News implied volatility and long-term foreign exchange market volatility," International Review of Financial Analysis, Elsevier, vol. 61(C), pages 126-142.
    91. Xu, Qifa & Chen, Lu & Jiang, Cuixia & Yuan, Jing, 2018. "Measuring systemic risk of the banking industry in China: A DCC-MIDAS-t approach," Pacific-Basin Finance Journal, Elsevier, vol. 51(C), pages 13-31.
    92. Ghysels, Eric & Qian, Hang, 2019. "Estimating MIDAS regressions via OLS with polynomial parameter profiling," Econometrics and Statistics, Elsevier, vol. 9(C), pages 1-16.
    93. S. Yfanti & M. Karanasos & J. Wu & P. Vourvachis, 2025. "Short- and long-run cross-border European sustainability interdependences," Annals of Operations Research, Springer, vol. 347(1), pages 579-610, April.
    94. Nonejad, Nima, 2022. "Understanding the conditional out-of-sample predictive impact of the price of crude oil on aggregate equity return volatility," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).

  16. Conrad, Christian & Karanasos, Menelaos, 2010. "Modeling the link between US inflation and output: the importance of the uncertainty channel," Working Papers 0507, University of Heidelberg, Department of Economics.

    Cited by:

    1. O. Evans, 2019. "Money, Inflation and Output in Nigeria and South Africa: Could Friedman and Schwartz Be Right?," Journal of African Business, Taylor & Francis Journals, vol. 20(3), pages 392-406, July.
    2. Kushal Banik Chowdhury & Nityananda Sarkar, 2019. "Regime Dependent Effect Of Output Growth On Output Growth Uncertainty: Evidence From Oecd Countries," Bulletin of Economic Research, Wiley Blackwell, vol. 71(3), pages 257-282, July.
    3. Conrad, Christian & Hartmann, Matthias, 2019. "On the determinants of long-run inflation uncertainty: Evidence from a panel of 17 developed economies," European Journal of Political Economy, Elsevier, vol. 56(C), pages 233-250.
    4. Karanasos, M. & Koutroumpis, P. & Karavias, Y. & Kartsaklas, A. & Arakelian, V., 2016. "Inflation convergence in the EMU," Journal of Empirical Finance, Elsevier, vol. 39(PB), pages 241-253.
    5. Mihaela SIMIONESCU, 2016. "The Identification Of Inflation Rate Determinants In The Usa Using The Stochastic Search Variable Selection," CES Working Papers, Centre for European Studies, Alexandru Ioan Cuza University, vol. 8(1), pages 171-181, March.
    6. Kushal Banik Chowdhury, 2024. "Relationships between inflation, output growth, and uncertainty in the era of inflation stabilization: a multicountry study," Empirical Economics, Springer, vol. 66(2), pages 623-650, February.
    7. Aaron D. Smallwood, 2022. "Inference in Misspecified GARCH‐M Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(2), pages 334-355, April.
    8. Kushal Banik Chowdhury & Srikanta Kundu & Nityananda Sarkar, 2018. "Regime‐dependent effects of uncertainty on inflation and output growth: evidence from the United Kingdom and the United States," Scottish Journal of Political Economy, Scottish Economic Society, vol. 65(4), pages 390-413, September.
    9. Kushal Banik Chowdhury & Kaustav Kanti Sarkar & Srikanta Kundu, 2021. "Nonlinear relationships between inflation, output growth and uncertainty in India: New evidence from a bivariate threshold model," Bulletin of Economic Research, Wiley Blackwell, vol. 73(3), pages 469-493, July.
    10. Karanasos, Menelaos & Menla Ali, Faek & Margaronis, Zannis & Nath, Rajat, 2018. "Modelling time varying volatility spillovers and conditional correlations across commodity metal futures," International Review of Financial Analysis, Elsevier, vol. 57(C), pages 246-256.
    11. Fuest, Angela & Schmidt, Torsten, 2020. "Inflation expectation uncertainty in a New Keynesian framework," Ruhr Economic Papers 867, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    12. Eyayu Tesfaye Mulugeta, 2025. "Output Growth Volatility, Remittances, and Financial Development in the Common Market for Eastern and Southern Africa Region: A System Generalized Method of Moments Approach," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 16(1), pages 2844-2860, March.

  17. Conrad, Christian & Rittler, Daniel & Rotfuß, Waldemar, 2010. "Modeling and Explaining the Dynamics of European Union Allowance Prices at High-Frequency," Working Papers 0497, University of Heidelberg, Department of Economics.

    Cited by:

    1. Zhu, Bangzhu & Ma, Shujiao & Chevallier, Julien & Wei, Yiming, 2014. "Modelling the dynamics of European carbon futures price: A Zipf analysis," Economic Modelling, Elsevier, vol. 38(C), pages 372-380.
    2. Mengrui Zhu & Hua Xu & Xingyu Gao & Minggang Wang & André L. M. Vilela & Lixin Tian, 2022. "Identification of Breakpoints in Carbon Market Based on Probability Density Recurrence Network," Energies, MDPI, vol. 15(15), pages 1-18, July.
    3. Fang, Sheng & Lu, Xinsheng & Li, Jianfeng & Qu, Ling, 2018. "Multifractal detrended cross-correlation analysis of carbon emission allowance and stock returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 551-566.
    4. Yoichi Otsubo & Bruce Mizrach, 2012. "The Market Microstructure of the European Climate Exchange," LSF Research Working Paper Series 12-7, Luxembourg School of Finance, University of Luxembourg.
    5. Paolo Mazza & Mikael Petitjean, 2015. "How integrated is the European carbon derivatives market?," Post-Print hal-01526028, HAL.
    6. Fan, Ying & Jia, Jun-Jun & Wang, Xin & Xu, Jin-Hua, 2017. "What policy adjustments in the EU ETS truly affected the carbon prices?," Energy Policy, Elsevier, vol. 103(C), pages 145-164.
    7. Bai, Yiyi & Okullo, Samuel J., 2023. "Drivers and pass-through of the EU ETS price: Evidence from the power sector," Energy Economics, Elsevier, vol. 123(C).
    8. Lau, Chi Keung & Soliman, Alaa M. & Albasu, Joseph & Gozgor, Giray, 2023. "Dependence structures among geopolitical risks, energy prices, and carbon emissions prices," Resources Policy, Elsevier, vol. 83(C).
    9. Löschel, Andreas & Brockmann, Karl Ludwig & Heindl, Peter & Lutz, Benjamin & Schumacher, Jan, 2011. "KfW/ZEW CO2 Barometer 2011: Hoher Anpassungsbedarf im EU-Emissionshandel ab 2013 – deutliche Defizite bei der Vorbereitung in den Unternehmen," KfW/ZEW-CO2-Barometer, ZEW - Leibniz Centre for European Economic Research, number 109795.
    10. Frédéric Branger, Philippe Quirion, Julien Chevallier, 2017. "Carbon Leakage and Competitiveness of Cement and Steel Industries Under the EU ETS: Much Ado About Nothing," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    11. Palao, Fernando & Pardo, Ángel, 2014. "What makes carbon traders cluster their orders?," Energy Economics, Elsevier, vol. 43(C), pages 158-165.
    12. Stefan Trück & Rafal Weron, 2015. "Convenience yields and risk premiums in the EU-ETS - Evidence from the Kyoto commitment period," HSC Research Reports HSC/15/03, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    13. Gavard, Claire & Kirat, Djamel, 2018. "Flexibility in the market for international carbon credits and price dynamics difference with European allowances," Energy Economics, Elsevier, vol. 76(C), pages 504-518.
    14. Ajay K. Dhamija & Surendra S. Yadav & PK Jain, 2017. "Forecasting volatility of carbon under EU ETS: a multi-phase study," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 19(2), pages 299-335, April.
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  18. Rotfuß, Waldemar & Conrad, Christian & Rittler, Daniel, 2009. "The European Commission and EUA prices: a high-frequency analysis of the EC's decisions on second NAPs," ZEW Discussion Papers 09-045, ZEW - Leibniz Centre for European Economic Research.

    Cited by:

    1. Conrad, Christian & Rittler, Daniel & Rotfuß, Waldemar, 2010. "Modeling and Explaining the Dynamics of European Union Allowance Prices at High-Frequency," Working Papers 0497, University of Heidelberg, Department of Economics.
    2. Vicente Medina Martínez & Ángel Pardo Tornero & Roberto Pascual, 2012. "The timeline of trading fricions in the European Carbon Market," Working Papers. Serie AD 2012-05, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    3. Chawla, M. & Pollitt, M.G., 2012. "Energy-efficiency and environmental policies & income supplements in the UK: Their evolution and distributional impact in relation to domestic energy bills," Cambridge Working Papers in Economics 1256, Faculty of Economics, University of Cambridge.
    4. Mallika Chawla & Michael G. Pollitt, 2013. "Energy-efficiency and Environmental Policies & Income Supplements in the UK: Evolution and Distributional Impacts on Domestic Energy Bills," Economics of Energy & Environmental Policy, International Association for Energy Economics, vol. 0(Number 1).

  19. Christian Conrad & Menelaos Karanasos, 2008. "Negative Volatility Spillovers in the Unrestricted ECCC-GARCH Model," KOF Working papers 08-189, KOF Swiss Economic Institute, ETH Zurich.

    Cited by:

    1. Karanasos, Menelaos & Xu, Yongdeng & Yfanti, Stavroula, 2017. "Constrained QML Estimation for Multivariate Asymmetric MEM with Spillovers: The Practicality of Matrix Inequalities," Cardiff Economics Working Papers E2017/14, Cardiff University, Cardiff Business School, Economics Section.
    2. Bago, Jean-Louis & Akakpo, Koffi & Rherrad, Imad & Ouédraogo, Ernest, 2020. "Volatility Spillover and International Contagion of Housing Bubbles," MPRA Paper 100098, University Library of Munich, Germany.
    3. Guglielmo Maria Caporale & John Hunter & Faek Menla Ali, 2013. "On the Linkages between Stock Prices and Exchange Rates: Evidence from the Banking Crisis of 2007-2010," CESifo Working Paper Series 4189, CESifo.
    4. Rittler, Daniel, 2012. "Price discovery and volatility spillovers in the European Union emissions trading scheme: A high-frequency analysis," Journal of Banking & Finance, Elsevier, vol. 36(3), pages 774-785.
    5. M. Angeles Carnero Fernández & M. Hakan Eratalay, 2012. "Estimating VAR-MGARCH models in multiple steps," Working Papers. Serie AD 2012-10, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    6. Tomasz Wozniak, 2012. "Testing Causality Between Two Vectors in Multivariate GARCH Models," Department of Economics - Working Papers Series 1139, The University of Melbourne.
    7. Noureddine Benlagha, 2014. "Volatility Linkage of Nominal and Index-linked Bond Returns: A Multivariate BEKK-GARCH Approach," Review of Economics & Finance, Better Advances Press, Canada, vol. 4, pages 49-60, November.
    8. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    9. Conrad, Christian & Weber, Enzo, 2013. "Measuring Persistence in Volatility Spillovers," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79850, Verein für Socialpolitik / German Economic Association.
    10. M. Karanasos & S. Yfanti & A. Christopoulos, 2021. "The long memory HEAVY process: modeling and forecasting financial volatility," Annals of Operations Research, Springer, vol. 306(1), pages 111-130, November.
    11. Karanasos, Menelaos & Paraskevopoulos,Alexandros & Canepa, Alessandra, 2020. "Unified Theory for the Large Family of Time Varying Models with Arma Representations: One Solution Fits All," Department of Economics and Statistics Cognetti de Martiis. Working Papers 202008, University of Turin.
    12. Karanasos, Menelaos & Paraskevopoulos, Alexandros G. & Menla Ali, Faek & Karoglou, Michail & Yfanti, Stavroula, 2014. "Modelling stock volatilities during financial crises: A time varying coefficient approach," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 113-128.
    13. Nektarios Aslanidis & Isabel Casas, 2010. "Modelling asset correlations during the recent FInancial crisis: A semiparametric approach," CREATES Research Papers 2010-71, Department of Economics and Business Economics, Aarhus University.
    14. Karanasos, Menelaos & Paraskevopoulos, Alexandros & Magdalinos, Anastasios & Canepa, Alessandra, 2024. "A Unified Theory for Arma Models with Varying Coefficients: One Solution Fits All," Department of Economics and Statistics Cognetti de Martiis. Working Papers 202413, University of Turin.
    15. Menelaos Karanasos & Alexandros Paraskevopoulos & Faek Menla Ali & Michail Karoglou & Stavroula Yfanti, 2014. "Modelling Returns and Volatilities During Financial Crises: a Time Varying Coefficient Approach," Papers 1403.7179, arXiv.org.
    16. Christian Francq & Jean-Michel Zakoïan, 2016. "Estimating multivariate volatility models equation by equation," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(3), pages 613-635, June.
    17. Xu, Yongdeng, 2024. "Extended multivariate EGARCH model: A model for zero†return and negative spillovers," Cardiff Economics Working Papers E2024/24, Cardiff University, Cardiff Business School, Economics Section.
    18. Pedersen, Rasmus Søndergaard, 2017. "Inference and testing on the boundary in extended constant conditional correlation GARCH models," Journal of Econometrics, Elsevier, vol. 196(1), pages 23-36.
    19. Hetland, Simon & Pedersen, Rasmus Søndergaard & Rahbek, Anders, 2023. "Dynamic conditional eigenvalue GARCH," Journal of Econometrics, Elsevier, vol. 237(2).
    20. Conrad, Christian, 2010. "Non-negativity conditions for the hyperbolic GARCH model," Journal of Econometrics, Elsevier, vol. 157(2), pages 441-457, August.
    21. Guglielmo Maria Caporale & Menelaos Karanasos & Stavroula Yfanti, 2019. "Macro-Financial Linkages in the High-Frequency Domain: The Effects of Uncertainty on Realized Volatility," CESifo Working Paper Series 8000, CESifo.
    22. Conrad, Christian & Karanasos, Menelaos & Zeng, Ning, 2010. "The link between macroeconomic performance and variability in the UK," Economics Letters, Elsevier, vol. 106(3), pages 154-157, March.
    23. Palani-Rajan Kadapakkam & Timothy Krause & Yiuman Tse, 2015. "Exchange traded funds, size-based portfolios, and market efficiency," Review of Quantitative Finance and Accounting, Springer, vol. 45(1), pages 89-110, July.
    24. Conrad, Christian & Karanasos, Menelaos & Zeng, Ning, 2011. "Multivariate fractionally integrated APARCH modeling of stock market volatility: A multi-country study," Journal of Empirical Finance, Elsevier, vol. 18(1), pages 147-159, January.
    25. Eraslan, Sercan & Ali, Faek Menla, 2017. "Financial crises and the dynamic linkages between stock and bond returns," Discussion Papers 17/2017, Deutsche Bundesbank.
    26. Dahiru A. Balaa & Taro Takimotob, 2017. "Stock markets volatility spillovers during financial crises: A DCC-MGARCH with skewed-t density approach," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 17(1), pages 25-48, March.
    27. Yannick Hoga, 2023. "The Estimation Risk in Extreme Systemic Risk Forecasts," Papers 2304.10349, arXiv.org.
    28. Tomasz Wozniak, 2012. "Granger-causal analysis of VARMA-GARCH models," Economics Working Papers ECO2012/19, European University Institute.
    29. Guglielmo Maria Caporale & Menelaos Karanasos & Stavroula Yfanti, 2024. "Macro‐financial linkages in the high‐frequency domain: Economic fundamentals and the Covid‐induced uncertainty channel in US and UK financial markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(2), pages 1581-1608, April.
    30. Kushal Banik Chowdhury, 2024. "Relationships between inflation, output growth, and uncertainty in the era of inflation stabilization: a multicountry study," Empirical Economics, Springer, vol. 66(2), pages 623-650, February.
    31. Aaron D. Smallwood, 2022. "Inference in Misspecified GARCH‐M Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(2), pages 334-355, April.
    32. Palani-Rajan Kadapakkam & Timothy Krause & Yiuman Tse, 2013. "Exchange Traded Funds, Size-Based Portfolios, And Market Efficiency," Working Papers 0214fin, College of Business, University of Texas at San Antonio.
    33. Kushal Banik Chowdhury & Srikanta Kundu & Nityananda Sarkar, 2018. "Regime‐dependent effects of uncertainty on inflation and output growth: evidence from the United Kingdom and the United States," Scottish Journal of Political Economy, Scottish Economic Society, vol. 65(4), pages 390-413, September.
    34. M. Karanasos & S. Yfanti & J. Hunter, 2022. "Emerging stock market volatility and economic fundamentals: the importance of US uncertainty spillovers, financial and health crises," Annals of Operations Research, Springer, vol. 313(2), pages 1077-1116, June.
    35. Menelaos Karanasos & Ning Zeng, 2013. "Conditional heteroskedasticity in macroeconomics data: UK inflation, output growth and their uncertainties," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 12, pages 266-288, Edward Elgar Publishing.
    36. Yfanti, Stavroula & Karanasos, Menelaos & Zopounidis, Constantin & Christopoulos, Apostolos, 2023. "Corporate credit risk counter-cyclical interdependence: A systematic analysis of cross-border and cross-sector correlation dynamics," European Journal of Operational Research, Elsevier, vol. 304(2), pages 813-831.
    37. Stavroula Yfanti & Georgios Chortareas & Menelaos Karanasos & Emmanouil Noikokyris, 2022. "A three‐dimensional asymmetric power HEAVY model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 2737-2761, July.
    38. Timo Dimitriadis & Yannick Hoga, 2022. "Dynamic CoVaR Modeling and Estimation," Papers 2206.14275, arXiv.org, revised Jan 2025.
    39. Karanasos, Menelaos & Menla Ali, Faek & Margaronis, Zannis & Nath, Rajat, 2018. "Modelling time varying volatility spillovers and conditional correlations across commodity metal futures," International Review of Financial Analysis, Elsevier, vol. 57(C), pages 246-256.
    40. Yongdeng Xu, 2025. "Extended Multivariate EGARCH Model: A Model for Zero‐Return and Negative Spillovers," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(4), pages 1266-1279, July.

  20. Christian Conrad & Michael J. Lamla, 2007. "The High-Frequency Response of the EUR-US Dollar Exchange Rate to ECB Monetary Policy Announcements," KOF Working papers 07-174, KOF Swiss Economic Institute, ETH Zurich.

    Cited by:

    1. Michael J. Lamla & Christian Conrad, 2007. "An den Lippen der EZB – Der KOF Monetary Policy Communicator," KOF Analysen, KOF Swiss Economic Institute, ETH Zurich, vol. 1(4), pages 33-45, March.
    2. Chang, C-L. & McAleer, M.J. & Tansuchat, R., 2012. "Modelling Long Memory Volatility in Agricultural Commodity Futures Returns," Econometric Institute Research Papers EI 2012-15, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3. Thiago Cacicedo Cidad & Gabriel Caldas Montes, 2016. "Does Central Bank’S Perception Regarding The State Of The Economy Affect Entrepreneurs’ Expectations? Are Entrepreneurs’ Expectations Important For Investment? Empirical Evidence From Brazil," Anais do XLIII Encontro Nacional de Economia [Proceedings of the 43rd Brazilian Economics Meeting] 035, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    4. Neuenkirch, Matthias, 2013. "Monetary policy transmission in vector autoregressions: A new approach using central bank communication," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4278-4285.
    5. Jakob Haan, 2008. "The effect of ECB communication on interest rates: An assessment," The Review of International Organizations, Springer, vol. 3(4), pages 375-398, December.
    6. Gabriel Caldas Montes & Rodolfo Tomás da Fonseca Nicolay, 2015. "Central bank’s perception on inflation and inflation expectations of experts," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 42(6), pages 1142-1158, November.
    7. Jan-Egbert Sturm & Jakob de Haan & Jakob de Haan, 2009. "Does Central Bank Communication really Lead to better Forecasts of Policy Decisions? New Evidence Based on a Taylor Rule Model for the ECB," CESifo Working Paper Series 2760, CESifo.
    8. Mr. Martin Cihak & Ms. Katerina Smídková & Mr. Aleš Bulíř, 2008. "Writing Clearly: ECB’s Monetary Policy Communication," IMF Working Papers 2008/252, International Monetary Fund.
    9. Rodolfo Tomás Da Fonseca Nicolay & Gabriel Caldas Montes, 2014. "Comunicação Do Banco Central,Expectativas De Inflação E Profecia Auto-Realizável: Evidências Para Obrasil," Anais do XL Encontro Nacional de Economia [Proceedings of the 40th Brazilian Economics Meeting] 046, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    10. Mr. Helge Berger & Mr. Thomas Harjes & Mr. Emil Stavrev, 2008. "The ECB’s Monetary Analysis Revisited," IMF Working Papers 2008/171, International Monetary Fund.
    11. Berger, Helge & Harjes, Thomas & Stavrev, Emil, 2008. "The ECB's monetary analysis revisited," Discussion Papers 2008/14, Free University Berlin, School of Business & Economics.

  21. Christian Conrad, 2007. "Non-negativity Conditions for the Hyperbolic GARCH Model," KOF Working papers 07-162, KOF Swiss Economic Institute, ETH Zurich.

    Cited by:

    1. Antonio Rubia & Trino-Manuel Ñíguez, 2006. "Forecasting the conditional covariance matrix of a portfolio under long-run temporal dependence," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(6), pages 439-458.
    2. Dark Jonathan Graeme, 2010. "Estimation of Time Varying Skewness and Kurtosis with an Application to Value at Risk," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(2), pages 1-50, March.
    3. Li, Muyi & Li, Wai Keung & Li, Guodong, 2015. "A new hyperbolic GARCH model," Journal of Econometrics, Elsevier, vol. 189(2), pages 428-436.
    4. Karanasos, Menelaos & Xu, Yongdeng & Yfanti, Stavroula, 2017. "Constrained QML Estimation for Multivariate Asymmetric MEM with Spillovers: The Practicality of Matrix Inequalities," Cardiff Economics Working Papers E2017/14, Cardiff University, Cardiff Business School, Economics Section.
    5. Heni Boubaker & Giorgio Canarella & Rangan Gupta & Stephen M. Miller, 2020. "Hybrid ARFIMA Wavelet Artificial Neural Network Model for DJIA Index Forecasting," Working papers 2020-10, University of Connecticut, Department of Economics.
    6. Pan, Qunxing & Li, Peng & Du, Xiuli, 2023. "An improved FIGARCH model with the fractional differencing operator (1-νL)d," Finance Research Letters, Elsevier, vol. 55(PB).
    7. Mohamed Chikhi & Anne Peguin-Feissolle & Michel Terraza, 2012. "SEMIFARMA-HYGARCH Modeling of Dow Jones Return Persistence," Working Papers halshs-00793203, HAL.
    8. Mawuli Segnon & Stelios Bekiros, 2020. "Forecasting volatility in bitcoin market," Annals of Finance, Springer, vol. 16(3), pages 435-462, September.
    9. Vygintas Gontis, 2023. "Discrete $q$-exponential limit order cancellation time distribution," Papers 2306.00093, arXiv.org, revised Oct 2023.
    10. Bjoern Schulte-Tillman & Mawuli Segnon & Bernd Wilfling, 2022. "Financial-market volatility prediction with multiplicative Markov-switching MIDAS components," CQE Working Papers 9922, Center for Quantitative Economics (CQE), University of Muenster.
    11. Conrad, Christian & Loch, Karin & Rittler, Daniel, 2014. "On the macroeconomic determinants of long-term volatilities and correlations in U.S. stock and crude oil markets," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 26-40.
    12. M. Karanasos & S. Yfanti & A. Christopoulos, 2021. "The long memory HEAVY process: modeling and forecasting financial volatility," Annals of Operations Research, Springer, vol. 306(1), pages 111-130, November.
    13. Lux, Thomas & Segnon, Mawuli & Gupta, Rangan, 2015. "Modeling and forecasting crude oil price volatility: Evidence from historical and recent data," FinMaP-Working Papers 31, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    14. Conrad, Christian & Loch, Karin, 2012. "Anticipating Long-Term Stock Market Volatility," Working Papers 0535, University of Heidelberg, Department of Economics.
    15. Al-Shboul, Mohammad & Alsharari, Nizar, 2019. "The dynamic behavior of evolving efficiency: Evidence from the UAE stock markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 73(C), pages 119-135.
    16. Mawuli Segnon & Manuel Stapper, 2019. "Long Memory Conditional Heteroscedasticity in Count Data," CQE Working Papers 8219, Center for Quantitative Economics (CQE), University of Muenster.
    17. Conrad, Christian & Rittler, Daniel & Rotfuß, Waldemar, 2010. "Modeling and Explaining the Dynamics of European Union Allowance Prices at High-Frequency," Working Papers 0497, University of Heidelberg, Department of Economics.
    18. Karanasos, Menelaos & Yfanti, Stavroula & Karoglou, Michail, 2016. "Multivariate FIAPARCH modelling of financial markets with dynamic correlations in times of crisis," International Review of Financial Analysis, Elsevier, vol. 45(C), pages 332-349.
    19. Guglielmo Maria Caporale & Menelaos Karanasos & Stavroula Yfanti & Aris Kartsaklas, 2019. "Investors' Trading Behaviour and Stock Market Volatility during Crisis Periods: A Dual Long-Memory Model for the Korean Stock Exchange," CESifo Working Paper Series 7984, CESifo.
    20. Gontis, V. & Kononovicius, A., 2017. "Burst and inter-burst duration statistics as empirical test of long-range memory in the financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 266-272.
    21. Dima, Bogdan & Dima, Ştefana Maria, 2017. "Mutual information and persistence in the stochastic volatility of market returns: An emergent market example," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 36-59.
    22. Lang, Korbinian & Auer, Benjamin R., 2020. "The economic and financial properties of crude oil: A review," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    23. Amélie Charles & Olivier Darné, 2012. "Volatility Persistence in Crude Oil Markets," Working Papers hal-00719387, HAL.
    24. Conrad, Christian & Karanasos, Menelaos & Zeng, Ning, 2011. "Multivariate fractionally integrated APARCH modeling of stock market volatility: A multi-country study," Journal of Empirical Finance, Elsevier, vol. 18(1), pages 147-159, January.
    25. Zouheir Mighri & Faysal Mansouri, 2014. "Modeling international stock market contagion using multivariate fractionally integrated APARCH approach," Cogent Economics & Finance, Taylor & Francis Journals, vol. 2(1), pages 1-25, December.
    26. Conrad, Christian & Loch, Karin & Rittler, Daniel, 2012. "On the Macroeconomic Determinants of the Long-Term Oil-Stock Correlation," Working Papers 0525, University of Heidelberg, Department of Economics.
    27. Yanlin Shi & Yang Yang, 2018. "Modeling High Frequency Data with Long Memory and Structural Change: A-HYEGARCH Model," Risks, MDPI, vol. 6(2), pages 1-28, March.
    28. Christian Conrad & Menelaos Karanasos, 2008. "Negative Volatility Spillovers in the Unrestricted ECCC-GARCH Model," KOF Working papers 08-189, KOF Swiss Economic Institute, ETH Zurich.
    29. V. Gontis & A. Kononovicius, 2017. "Burst and inter-burst duration statistics as empirical test of long-range memory in the financial markets," Papers 1701.01255, arXiv.org.
    30. Rasheed O. Alao & Abdulkareem Alhassan & Saheed Alao & Ifedolapo O. Olanipekun & Godwin O. Olasehinde-Williams & Ojonugwa Usman, 2023. "Symmetric and asymmetric GARCH estimations of the impact of oil price uncertainty on output growth: evidence from the G7," Letters in Spatial and Resource Sciences, Springer, vol. 16(1), pages 1-14, December.
    31. Lee, Oesook, 2018. "Stationarity and functional central limit theorem for ARCH(∞) models," Economics Letters, Elsevier, vol. 162(C), pages 107-111.
    32. Zouheir Mighri, 2018. "On the Dynamic Linkages Among International Emerging Currencies," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 16(2), pages 427-473, June.
    33. Nazarian, Rafik & Naderi, Esmaeil & Gandali Alikhani, Nadiya & Amiri, Ashkan, 2013. "Long Memory Analysis: An Empirical Investigation," MPRA Paper 45605, University Library of Munich, Germany.
    34. Morales-Pelagio, Ricardo Cristhian & López-Herrera, Francisco & Cabrera-Llanos, Agustín Ignacio, 2013. "Eficiencia de las principales acciones de la bolsa mexicana de valores: 2001-2012," eseconomía, Escuela Superior de Economía, Instituto Politécnico Nacional, vol. 0(37), pages 55-75, primer tr.
    35. Muyi Li & Wai Keung Li & Guodong Li, 2013. "On Mixture Memory Garch Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(6), pages 606-624, November.
    36. Vygintas Gontis, 2021. "Order flow in the financial markets from the perspective of the Fractional L\'evy stable motion," Papers 2105.02057, arXiv.org, revised Nov 2021.
    37. Klein, Tony & Walther, Thomas, 2016. "Oil price volatility forecast with mixture memory GARCH," Energy Economics, Elsevier, vol. 58(C), pages 46-58.
    38. Mawuli Segnon & Stelios Bekiros, 2019. "Forecasting Volatility in Cryptocurrency Markets," CQE Working Papers 7919, Center for Quantitative Economics (CQE), University of Muenster.

Articles

  1. Conrad, Christian & Enders, Zeno & Glas, Alexander, 2022. "The role of information and experience for households’ inflation expectations," European Economic Review, Elsevier, vol. 143(C).
    See citations under working paper version above.
  2. Christian Conrad & Onno Kleen, 2020. "Two are better than one: Volatility forecasting using multiplicative component GARCH‐MIDAS models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(1), pages 19-45, January.

    Cited by:

    1. Mawuli Segnon & Rangan Gupta & Bernd Wilfling, 2022. "Forecasting Stock Market Volatility with Regime-Switching GARCH-MIDAS: The Role of Geopolitical Risks," Working Papers 202203, University of Pretoria, Department of Economics.
    2. Yun-Shi Dai & Peng-Fei Dai & Wei-Xing Zhou, 2024. "The impact of geopolitical risk on the international agricultural market: Empirical analysis based on the GJR-GARCH-MIDAS model," Papers 2404.01641, arXiv.org.
    3. Nguyen, Hoang & Virbickaitė, Audronė, 2023. "Modeling stock-oil co-dependence with Dynamic Stochastic MIDAS Copula models," Energy Economics, Elsevier, vol. 124(C).
    4. Nguyen, Hoang & Javed, Farrukh, 2023. "Dynamic relationship between Stock and Bond returns: A GAS MIDAS copula approach," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 272-292.
    5. Christian Conrad & Julius Theodor Schoelkopf & Nikoleta Tushteva, 2023. "Long-Term Volatility Shapes the Stock Market’s Sensitivity to News," Working Paper series 23-16, Rimini Centre for Economic Analysis.
    6. Liang, Chao & Xia, Zhenglan & Lai, Xiaodong & Wang, Lu, 2022. "Natural gas volatility prediction: Fresh evidence from extreme weather and extended GARCH-MIDAS-ES model," Energy Economics, Elsevier, vol. 116(C).
    7. Cagliesi, Gabriella & Guidi, Francesco, 2021. "A three-tiered nested analytical approach to financial integration: The case of emerging and frontier equity markets," International Review of Financial Analysis, Elsevier, vol. 74(C).
    8. Huabin Bian & Renhai Hua & Qingfu Liu & Ping Zhang, 2022. "Petroleum market volatility tracker in China," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(11), pages 2022-2040, November.
    9. Yao, Zhigang & Liu, Yao, 2023. "Crude oil volatility forecasting: New evidence from world uncertainty index," Finance Research Letters, Elsevier, vol. 58(PA).
    10. Zhang, Xincheng & Wu, Shaojiang, 2024. "Natural resources and sustainable development: Evidence from the dynamic correlation between crude oil and gold market," International Review of Economics & Finance, Elsevier, vol. 96(PB).
    11. O-Chia Chuang & Chenxu Yang, 2022. "Identifying the Determinants of Crude Oil Market Volatility by the Multivariate GARCH-MIDAS Model," Energies, MDPI, vol. 15(8), pages 1-14, April.
    12. Wu, Xinyu & Zhao, An & Cheng, Tengfei, 2023. "A Real-Time GARCH-MIDAS model," Finance Research Letters, Elsevier, vol. 56(C).
    13. Virk, Nader & Javed, Farrukh & Awartani, Basel, 2021. "A reality check on the GARCH-MIDAS volatility models," Working Papers 2021:2, Örebro University, School of Business.
    14. L. Scaffidi Domianello & G.M. Gallo & E. Otranto, 2022. "Smooth and Abrupt Dynamics in Financial Volatility: the MS-MEM-MIDAS," Working Paper CRENoS 202205, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    15. Bjoern Schulte-Tillman & Mawuli Segnon & Bernd Wilfling, 2022. "Financial-market volatility prediction with multiplicative Markov-switching MIDAS components," CQE Working Papers 9922, Center for Quantitative Economics (CQE), University of Muenster.
    16. Julien Chevallier & Bilel Sanhaji, 2023. "Jump-Robust Realized-GARCH-MIDAS-X Estimators for Bitcoin and Ethereum Volatility Indices," Post-Print halshs-04344131, HAL.
    17. Arthur J. Lin & Hai-Yen Chang, 2020. "Volatility Transmission from Equity, Bulk Shipping, and Commodity Markets to Oil ETF and Energy Fund—A GARCH-MIDAS Model," Mathematics, MDPI, vol. 8(9), pages 1-21, September.
    18. Bahram Adrangi & Arjun Chatrath & Kambiz Raffiee, 2025. "Latin American Equities, Volatility Regimes, and the US Economic Policy Uncertainty," Bulletin of Applied Economics, Risk Market Journals, vol. 12(2), pages 15-44.
    19. Min Liu & Chien‐Chiang Lee & Wei‐Chong Choo, 2021. "An empirical study on the role of trading volume and data frequency in volatility forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 792-816, August.
    20. Amendola, Alessandra & Candila, Vincenzo & Gallo, Giampiero M., 2021. "Choosing the frequency of volatility components within the Double Asymmetric GARCH–MIDAS–X model," Econometrics and Statistics, Elsevier, vol. 20(C), pages 12-28.
    21. Amendola, A. & Candila, V. & Cipollini, F. & Gallo, G.M., 2024. "Doubly multiplicative error models with long- and short-run components," Socio-Economic Planning Sciences, Elsevier, vol. 91(C).
    22. Yanping Liu & Bo Yan, 2024. "Spillover effects of carbon, energy, and stock markets considering economic policy uncertainty," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 48(3), pages 563-591, September.
    23. Lu, Xinjie & Ma, Feng & Xu, Jin & Zhang, Zehui, 2022. "Oil futures volatility predictability: New evidence based on machine learning models11All the authors contribute to the paper equally," International Review of Financial Analysis, Elsevier, vol. 83(C).
    24. Hengzhen Lu & Qiujin Gao & Ling Xiao & Gurjeet Dhesi, 2024. "Forecasting EUA futures volatility with geopolitical risk: evidence from GARCH-MIDAS models," Review of Managerial Science, Springer, vol. 18(7), pages 1917-1943, July.
    25. Christian Conrad & Robert F. Engle, 2025. "Modelling Volatility Cycles: The MF2‐GARCH Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 40(4), pages 438-454, June.
    26. Lv, Wendai & Qi, Jipeng & Feng, Jing, 2023. "Economic policy uncertainty and environmental governance company volatility: Evidence from China," Research in International Business and Finance, Elsevier, vol. 64(C).
    27. Liu, Min & Lee, Chien-Chiang, 2021. "Capturing the dynamics of the China crude oil futures: Markov switching, co-movement, and volatility forecasting," Energy Economics, Elsevier, vol. 103(C).
    28. Chaturvedi, Priya & Kumar, Kuldeep, 2022. "Econometric modelling of exchange rate volatility using mixed-frequency data," MPRA Paper 115222, University Library of Munich, Germany.
    29. Wu, Xinyu & Xie, Haibin & Zhang, Huanming, 2022. "Time-varying risk aversion and renminbi exchange rate volatility: Evidence from CARR-MIDAS model," The North American Journal of Economics and Finance, Elsevier, vol. 61(C).
    30. Virbickaite, Audrone & Nguyen, Hoang & Tran, Minh-Ngoc, 2023. "Bayesian Predictive Distributions of Oil Returns Using Mixed Data Sampling Volatility Models," Working Papers 2023:7, Örebro University, School of Business.
    31. Bahram Adrangi & Arjun Chatrath & Saman Hatamerad & Kambiz Raffiee, 2025. "Equity Markets Volatility, Regime Dependence and Economic Uncertainty: The Case of Pacific Basin," Bulletin of Applied Economics, Risk Market Journals, vol. 12(1), pages 75-105.
    32. Hongyu An & Boping Tian, 2025. "Unleashing the Potential of Mixed Frequency Data: Measuring Risk with Dynamic Tail Index Regression Model," Computational Economics, Springer;Society for Computational Economics, vol. 65(3), pages 1567-1615, March.
    33. Afees A. Salisu & Wenting Liao & Rangan Gupta & Oguzhan Cepni, 2023. "Economic Conditions and Predictability of US Stock Returns Volatility: Local Factor versus National Factor in a GARCH-MIDAS Model," Working Papers 202323, University of Pretoria, Department of Economics.
    34. Vincenzo Candila & Giampiero M. Gallo & Lea Petrella, 2020. "Mixed--frequency quantile regressions to forecast Value--at--Risk and Expected Shortfall," Papers 2011.00552, arXiv.org, revised Mar 2023.
    35. Nguyen, Hien Thi & Nguyen, Hoang & Tran, Minh-Ngoc, 2024. "Deep learning enhanced volatility modeling with covariates," Finance Research Letters, Elsevier, vol. 69(PB).
    36. Bertelsen, Kristoffer Pons & Borup, Daniel & Jakobsen, Johan Stax, 2021. "Stock market volatility and public information flow: A non-linear perspective," Economics Letters, Elsevier, vol. 204(C).
    37. Zian Wang & Xinshu Li, 2024. "On the macroeconomic fundamentals of long-term volatilities and dynamic correlations in COMEX copper futures," Papers 2409.08355, arXiv.org.
    38. Stewart, Shamar L. & Isengildina Massa, Olga, 2024. "Food & Oil Price Volatility Dynamics: Insights from a TVP-SVAR-DCC-MIDAS Model," 2024 Annual Meeting, July 28-30, New Orleans, LA 343936, Agricultural and Applied Economics Association.
    39. Huawei Niu & Tianyu Liu, 2024. "Forecasting the volatility of European Union allowance futures with macroeconomic variables using the GJR-GARCH-MIDAS model," Empirical Economics, Springer, vol. 67(1), pages 75-96, July.
    40. Liu, Jing & Chen, Zhonglu, 2023. "How do stock prices respond to the leading economic indicators? Analysis of large and small shocks," Finance Research Letters, Elsevier, vol. 51(C).
    41. Cipollini, Fabrizio & Gallo, Giampiero M., 2025. "Multiplicative Error Models: 20 years on," Econometrics and Statistics, Elsevier, vol. 33(C), pages 209-229.
    42. Liu, Han & Yang, Peng & He, Yongda & Oxley, Les & Guo, Pengwei, 2024. "Exploring the influence of the geopolitical risks on the natural resource price volatility and correlation: Evidence from DCC-MIDAS-X model," Energy Economics, Elsevier, vol. 129(C).
    43. Han Liu & Peng Yang & Haiyan Song & Doris Chenguang Wu, 2024. "Global and domestic economic policy uncertainties and tourism stock market: Evidence from China," Tourism Economics, , vol. 30(3), pages 567-591, May.
    44. Dong, Feng & Li, Zhicheng & Huang, Zihuang & Liu, Yu, 2024. "Extreme weather, policy uncertainty, and risk spillovers between energy, financial, and carbon markets," Energy Economics, Elsevier, vol. 137(C).
    45. Zhang, Jiaming & Xiang, Yitian & Zou, Yang & Guo, Songlin, 2024. "Volatility forecasting of Chinese energy market: Which uncertainty have better performance?," International Review of Financial Analysis, Elsevier, vol. 91(C).
    46. Han, Yingwei & Li, Jie, 2023. "The impact of global economic policy uncertainty on portfolio optimization: A Black–Litterman approach," International Review of Financial Analysis, Elsevier, vol. 86(C).
    47. Ma, Feng & Wang, Jiqian & Wahab, M.I.M. & Ma, Yuanhui, 2023. "Stock market volatility predictability in a data-rich world: A new insight," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1804-1819.
    48. Ghani, Maria & Guo, Qiang & Ma, Feng & Li, Tao, 2022. "Forecasting Pakistan stock market volatility: Evidence from economic variables and the uncertainty index," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 1180-1189.
    49. José Antonio Núñez-Mora & Roberto Joaquín Santillán-Salgado & Mario Iván Contreras-Valdez, 2022. "COVID Asymmetric Impact on the Risk Premium of Developed and Emerging Countries’ Stock Markets," Mathematics, MDPI, vol. 10(9), pages 1-36, April.
    50. Gao, Wang & Zhang, Linlin & Zhang, Haizhen & Zhang, Hongwei, 2024. "The role of trade policy uncertainty on contemporaneous and lagged connectedness between critical raw materials and high-tech markets: Evidence from China," Resources Policy, Elsevier, vol. 98(C).
    51. Damien Kunjal & Faeezah Peerbhai & Paul-Francois Muzindutsi, 2022. "Political, economic, and financial country risks and the volatility of the South African Exchange Traded Fund market: A GARCH-MIDAS approach," Risk Management, Palgrave Macmillan, vol. 24(3), pages 236-258, September.
    52. Zhao, Jing, 2022. "Exploring the influence of the main factors on the crude oil price volatility: An analysis based on GARCH-MIDAS model with Lasso approach," Resources Policy, Elsevier, vol. 79(C).
    53. Díaz, Juan D. & Hansen, Erwin & Cabrera, Gabriel, 2024. "Machine-learning stock market volatility: Predictability, drivers, and economic value," International Review of Financial Analysis, Elsevier, vol. 94(C).
    54. Alain Hecq & Marie Ternes & Ines Wilms, 2023. "Hierarchical Regularizers for Reverse Unrestricted Mixed Data Sampling Regressions," Papers 2301.10592, arXiv.org, revised Nov 2024.
    55. Mawuli Segnon & Bjorn Schulte-Tillmann & Riza Demirer & Rangan Gupta, 2025. "Deglobalization and Foreign Exchange Volatility: The Role of Supply Chain Pressures," Working Papers 202506, University of Pretoria, Department of Economics.
    56. Zian Wang & Xinyi Lu, 2024. "COMEX Copper Futures Volatility Forecasting: Econometric Models and Deep Learning," Papers 2409.08356, arXiv.org.
    57. Zhang Wu & Terence Tai-Leung Chong, 2021. "Does the macroeconomy matter to market volatility? Evidence from US industries," Empirical Economics, Springer, vol. 61(6), pages 2931-2962, December.
    58. Bahram Adrangi & Arjun Chatrath & Kambiz Raffiee, 2023. "S&P 500 volatility, volatility regimes, and economic uncertainty," Bulletin of Economic Research, Wiley Blackwell, vol. 75(4), pages 1362-1387, October.
    59. Maria Ghani & Usman Ghani, 2024. "Economic Policy Uncertainty and Emerging Stock Market Volatility," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 31(1), pages 165-181, March.
    60. Yao, Can-Zhong & Li, Min-Jian, 2023. "GARCH-MIDAS-GAS-copula model for CoVaR and risk spillover in stock markets," The North American Journal of Economics and Finance, Elsevier, vol. 66(C).
    61. Lukman A. Lasisi & Franklin N. Ngwu & Mohammed K. Taliat & Abeeb O. Olaniran & Kelechi C. Nnamdi, 2025. "Modelling commodity market volatility with climate policy uncertainty: a GARCH-MIDAS approach," SN Business & Economics, Springer, vol. 5(3), pages 1-21, March.
    62. Mo, Guoli & Zhang, Weiguo & Tan, Chunzhi & Liu, Xing, 2022. "Predicting the portfolio risk of high-dimensional international stock indices with dynamic spatial dependence," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    63. Arthur Jin Lin, 2023. "Volatility Contagion from Bulk Shipping and Petrochemical Industries to Oil Futures Market during the Economic Uncertainty," Mathematics, MDPI, vol. 11(17), pages 1-19, August.

  3. Christian Conrad & Melanie Schienle, 2020. "Testing for an Omitted Multiplicative Long-Term Component in GARCH Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 229-242, April.
    See citations under working paper version above.
  4. Conrad, Christian & Hartmann, Matthias, 2019. "On the determinants of long-run inflation uncertainty: Evidence from a panel of 17 developed economies," European Journal of Political Economy, Elsevier, vol. 56(C), pages 233-250.

    Cited by:

    1. Neil Lawton & Liam A. Gallagher, 2020. "The negative side of inflation targeting: revisiting inflation uncertainty in the EMU," Applied Economics, Taylor & Francis Journals, vol. 52(29), pages 3186-3203, June.
    2. Cahan, Dodge & Doerr, Luisa & Potrafke, Niklas, 2019. "Government ideology and monetary policy in OECD countries," Munich Reprints in Economics 78247, University of Munich, Department of Economics.
    3. Conrad, Christian & Lahiri, Kajal, 2024. "Heterogeneous Expectations among Professional Forecasters," Working Papers 0754, University of Heidelberg, Department of Economics.
    4. Conrad, Christian & Enders, Zeno & Glas, Alexander, 2021. "The role of information and experience for households' inflation expectations," Discussion Papers 07/2021, Deutsche Bundesbank.
    5. McDowell, Daniel & Steinberg, David A., 2024. "Black representation and the popular legitimacy of the Federal Reserve," European Journal of Political Economy, Elsevier, vol. 85(C).

  5. Christian Conrad & Anessa Custovic & Eric Ghysels, 2018. "Long- and Short-Term Cryptocurrency Volatility Components: A GARCH-MIDAS Analysis," JRFM, MDPI, vol. 11(2), pages 1-12, May.

    Cited by:

    1. Fang, Libing & Bouri, Elie & Gupta, Rangan & Roubaud, David, 2019. "Does global economic uncertainty matter for the volatility and hedging effectiveness of Bitcoin?," International Review of Financial Analysis, Elsevier, vol. 61(C), pages 29-36.
    2. Haffar, Adlane & Le Fur, Éric, 2022. "Time-varying dependence of Bitcoin," The Quarterly Review of Economics and Finance, Elsevier, vol. 86(C), pages 211-220.
    3. Cathy Yi-Hsuan Chen & Christian M. Hafner, 2019. "Sentiment-Induced Bubbles in the Cryptocurrency Market," JRFM, MDPI, vol. 12(2), pages 1-12, April.
    4. Matkovskyy, Roman, 2019. "Centralized and decentralized bitcoin markets: Euro vs USD vs GBP," The Quarterly Review of Economics and Finance, Elsevier, vol. 71(C), pages 270-279.
    5. Eric Ghysels & Giang Nguyen, 2019. "Price Discovery of a Speculative Asset: Evidence from a Bitcoin Exchange," JRFM, MDPI, vol. 12(4), pages 1-26, October.
    6. Bouteska, Ahmed & Abedin, Mohammad Zoynul & Hajek, Petr & Yuan, Kunpeng, 2024. "Cryptocurrency price forecasting – A comparative analysis of ensemble learning and deep learning methods," International Review of Financial Analysis, Elsevier, vol. 92(C).
    7. Tzeng, Kae-Yih & Su, Yi-Kai, 2024. "Can U.S. macroeconomic indicators forecast cryptocurrency volatility?," The North American Journal of Economics and Finance, Elsevier, vol. 74(C).
    8. Aiusha Sangadiev & Rodrigo Rivera-Castro & Kirill Stepanov & Andrey Poddubny & Kirill Bubenchikov & Nikita Bekezin & Polina Pilyugina & Evgeny Burnaev, 2020. "DeepFolio: Convolutional Neural Networks for Portfolios with Limit Order Book Data," Papers 2008.12152, arXiv.org.
    9. Khalid Khan & Jiluo Sun & Sinem Derindere Koseoglu & Ashfaq U. Rehman, 2021. "Revisiting Bitcoin Price Behavior Under Global Economic Uncertainty," SAGE Open, , vol. 11(3), pages 21582440211, August.
    10. Ben Khelifa, Soumaya & Guesmi, Khaled & Urom, Christian, 2021. "Exploring the relationship between cryptocurrencies and hedge funds during COVID-19 crisis," International Review of Financial Analysis, Elsevier, vol. 76(C).
    11. Bourghelle, David & Jawadi, Fredj & Rozin, Philippe, 2022. "Do collective emotions drive bitcoin volatility? A triple regime-switching vector approach," Journal of Economic Behavior & Organization, Elsevier, vol. 196(C), pages 294-306.
    12. López-Cabarcos, M. Ángeles & Pérez-Pico, Ada M. & Piñeiro-Chousa, Juan & Šević, Aleksandar, 2021. "Bitcoin volatility, stock market and investor sentiment. Are they connected?," Finance Research Letters, Elsevier, vol. 38(C).
    13. Pierre J. Venter & Eben Maré, 2020. "GARCH Generated Volatility Indices of Bitcoin and CRIX," JRFM, MDPI, vol. 13(6), pages 1-15, June.
    14. Walid Chkili, 2021. "Modeling Bitcoin price volatility: long memory vs Markov switching," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 11(3), pages 433-448, September.
    15. BenMabrouk, Houda & Sassi, Syrine & Soltane, Feriel & Abid, Ilyes, 2024. "Connectedness and portfolio hedging between NFTs segments, American stocks and cryptocurrencies Nexus," International Review of Financial Analysis, Elsevier, vol. 91(C).
    16. Balcilar, Mehmet & Ozdemir, Huseyin & Agan, Busra, 2022. "Effects of COVID-19 on cryptocurrency and emerging market connectedness: Empirical evidence from quantile, frequency, and lasso networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    17. Yue, Yao & Li, Xuerong & Zhang, Dingxuan & Wang, Shouyang, 2021. "How cryptocurrency affects economy? A network analysis using bibliometric methods," International Review of Financial Analysis, Elsevier, vol. 77(C).
    18. Fan Fang & Carmine Ventre & Michail Basios & Leslie Kanthan & David Martinez-Rego & Fan Wu & Lingbo Li, 2022. "Cryptocurrency trading: a comprehensive survey," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-59, December.
    19. Fang, Tong & Su, Zhi & Yin, Libo, 2020. "Economic fundamentals or investor perceptions? The role of uncertainty in predicting long-term cryptocurrency volatility," International Review of Financial Analysis, Elsevier, vol. 71(C).
    20. Fan Fang & Carmine Ventre & Michail Basios & Leslie Kanthan & Lingbo Li & David Martinez-Regoband & Fan Wu, 2020. "Cryptocurrency Trading: A Comprehensive Survey," Papers 2003.11352, arXiv.org, revised Jan 2022.
    21. Zoltan Ban & Jan Lansky & Stanislava Mildeova & Petr Tesar, 2019. "A Probe Survey of Bitcoin Transactions Through Analysis of Advertising in an On-Line Discussion Forum," Acta Informatica Pragensia, Prague University of Economics and Business, vol. 2019(2), pages 112-131.
    22. Farman Ullah Khan & Faridoon Khan & Parvez Ahmed Shaikh, 2023. "Forecasting returns volatility of cryptocurrency by applying various deep learning algorithms," Future Business Journal, Springer, vol. 9(1), pages 1-11, December.
    23. Chowdhury, Md Shahedur R. & Damianov, Damian S., 2024. "Uncertainty and bubbles in cryptocurrencies: Evidence from newly developed uncertainty indices," International Review of Financial Analysis, Elsevier, vol. 91(C).
    24. Mensi, Walid & Rehman, Mobeen Ur & Vo, Xuan Vinh & Kang, Sang Hoon, 2024. "Spillovers and multiscale relationships among cryptocurrencies: A portfolio implication using high frequency data," Economic Analysis and Policy, Elsevier, vol. 82(C), pages 449-479.
    25. Lu, Xunfa & Wang, Huiyou & Mo, Jianlei, 2025. "Modelling the volatility dynamics of China's regional carbon markets: The heterogeneous effects of the fossil and clean energy electricity generation," Renewable Energy, Elsevier, vol. 240(C).
    26. Vincenzo Candila, 2021. "Multivariate Analysis of Cryptocurrencies," Econometrics, MDPI, vol. 9(3), pages 1-17, July.
    27. Klein, Tony & Hien, Pham Thu & Walther, Thomas, 2018. "Bitcoin Is Not the New Gold: A Comparison of Volatility, Correlation, and Portfolio Performance," QBS Working Paper Series 2018/01, Queen's University Belfast, Queen's Business School.
    28. Sabah, Nasim, 2020. "Cryptocurrency accepting venues, investor attention, and volatility," Finance Research Letters, Elsevier, vol. 36(C).
    29. Lee, Kangsan & Jeong, Daeyoung, 2023. "Too much is too bad: The effect of media coverage on the price volatility of cryptocurrencies," Journal of International Money and Finance, Elsevier, vol. 133(C).
    30. Lahmiri, Salim & Bekiros, Stelios, 2019. "Decomposing the persistence structure of Islamic and green crypto-currencies with nonlinear stepwise filtering," Chaos, Solitons & Fractals, Elsevier, vol. 127(C), pages 334-341.
    31. Liu, Yang & Han, Liyan & Xu, Yang, 2021. "The impact of geopolitical uncertainty on energy volatility," International Review of Financial Analysis, Elsevier, vol. 75(C).
    32. Asad Ul Islam & William Bwando, 2024. "Are the Crypto Markets Shock Resilient to COVID-19? A Comparative Investigation of Trading Prices and Volumes," International Econometric Review (IER), Econometric Research Association, vol. 16(2), pages 148-171, December.
    33. Haffar, Adlane & Le Fur, Eric, 2021. "Structural vector error correction modelling of Bitcoin price," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 170-178.
    34. Lyócsa, Štefan & Molnár, Peter & Plíhal, Tomáš & Širaňová, Mária, 2020. "Impact of macroeconomic news, regulation and hacking exchange markets on the volatility of bitcoin," Journal of Economic Dynamics and Control, Elsevier, vol. 119(C).
    35. Wu, Chang-Che & Ho, Shu-Ling & Wu, Chih-Chiang, 2022. "The determinants of Bitcoin returns and volatility: Perspectives on global and national economic policy uncertainty," Finance Research Letters, Elsevier, vol. 45(C).
    36. Jin, Daxiang & Yu, Jize, 2023. "Predicting cryptocurrency market volatility: Novel evidence from climate policy uncertainty," Finance Research Letters, Elsevier, vol. 58(PC).
    37. Berend Jelmer Dirk Gort & Xiao-Yang Liu & Xinghang Sun & Jiechao Gao & Shuaiyu Chen & Christina Dan Wang, 2022. "Deep Reinforcement Learning for Cryptocurrency Trading: Practical Approach to Address Backtest Overfitting," Papers 2209.05559, arXiv.org, revised Jan 2023.
    38. Khaki, Audil & Prasad, Mason & Al-Mohamad, Somar & Bakry, Walid & Vo, Xuan Vinh, 2023. "Re-evaluating portfolio diversification and design using cryptocurrencies: Are decentralized cryptocurrencies enough?," Research in International Business and Finance, Elsevier, vol. 64(C).
    39. Bahram Adrangi & Arjun Chatrath & Kambiz Raffiee, 2025. "Latin American Equities, Volatility Regimes, and the US Economic Policy Uncertainty," Bulletin of Applied Economics, Risk Market Journals, vol. 12(2), pages 15-44.
    40. Thomas Walther & Tony Klein, 2018. "Exogenous Drivers of Cryptocurrency Volatility - A Mixed Data Sampling Approach To Forecasting," Working Papers on Finance 1815, University of St. Gallen, School of Finance.
    41. Walther, Thomas & Klein, Tony & Bouri, Elie, 2019. "Exogenous drivers of Bitcoin and Cryptocurrency volatility – A mixed data sampling approach to forecasting," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 63(C).
    42. Elie Bouri & Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2021. "Forecasting Realized Volatility of Bitcoin: The Role of the Trade War," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 29-53, January.
    43. Sofiane Aboura, 2022. "A note on the Bitcoin and Fed Funds rate," Empirical Economics, Springer, vol. 63(5), pages 2577-2603, November.
    44. Theodore Pelagidis & Eleftheria Kostika, 2022. "Investigating the role of central banks in the interconnection between financial markets and cryptoassets," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 49(3), pages 481-507, September.
    45. Nikolaos A. Kyriazis, 2021. "A Survey on Volatility Fluctuations in the Decentralized Cryptocurrency Financial Assets," JRFM, MDPI, vol. 14(7), pages 1-46, June.
    46. Wang, Yijun & Andreeva, Galina & Martin-Barragan, Belen, 2023. "Machine learning approaches to forecasting cryptocurrency volatility: Considering internal and external determinants," International Review of Financial Analysis, Elsevier, vol. 90(C).
    47. Christian M. Hafner, 2020. "Alternative Assets and Cryptocurrencies," JRFM, MDPI, vol. 13(1), pages 1-3, January.
    48. Ferreira, Paulo & Kristoufek, Ladislav & Pereira, Eder Johnson de Area Leão, 2020. "DCCA and DMCA correlations of cryptocurrency markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    49. Chaturvedi, Priya & Kumar, Kuldeep, 2022. "Econometric modelling of exchange rate volatility using mixed-frequency data," MPRA Paper 115222, University Library of Munich, Germany.
    50. Bouri, Elie & Lau, Chi Keung Marco & Saeed, Tareq & Wang, Shixuan & Zhao, Yuqian, 2021. "On the intraday return curves of Bitcoin: Predictability and trading opportunities," International Review of Financial Analysis, Elsevier, vol. 76(C).
    51. Onur Özdemir, 2022. "Cue the volatility spillover in the cryptocurrency markets during the COVID-19 pandemic: evidence from DCC-GARCH and wavelet analysis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-38, December.
    52. Silky Vigg Kushwah & Shab Hundal & Payal Goel, 2024. "Unveiling Interconnectedness and Volatility Transmission: A Novel GARCH Analysis of Leading Global Cryptocurrencies," International Journal of Economics and Financial Issues, Econjournals, vol. 14(3), pages 132-139, May.
    53. Yang Zhou & Chi Xie & Gang-Jin Wang & Jue Gong & You Zhu, 2025. "Forecasting cryptocurrency volatility: a novel framework based on the evolving multiscale graph neural network," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-52, December.
    54. Walid Bakry & Audil Rashid & Somar Al-Mohamad & Nasser El-Kanj, 2021. "Bitcoin and Portfolio Diversification: A Portfolio Optimization Approach," JRFM, MDPI, vol. 14(7), pages 1-24, June.
    55. Virbickaite, Audrone & Nguyen, Hoang & Tran, Minh-Ngoc, 2023. "Bayesian Predictive Distributions of Oil Returns Using Mixed Data Sampling Volatility Models," Working Papers 2023:7, Örebro University, School of Business.
    56. Bahram Adrangi & Arjun Chatrath & Saman Hatamerad & Kambiz Raffiee, 2025. "Equity Markets Volatility, Regime Dependence and Economic Uncertainty: The Case of Pacific Basin," Bulletin of Applied Economics, Risk Market Journals, vol. 12(1), pages 75-105.
    57. Emon Kalyan Chowdhury & Mohammad Nayeem Abdullah, 2024. "Gauging Demand for Cryptocurrency over the Economic Policy Uncertainty and Stock Market Volatility," Computational Economics, Springer;Society for Computational Economics, vol. 64(1), pages 37-55, July.
    58. Hu, Junjie & Kuo, Weiyu & Härdle, Wolfgang Karl, 2019. "Risk of Bitcoin Market: Volatility, Jumps, and Forecasts," IRTG 1792 Discussion Papers 2019-024, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    59. Grobys, Klaus & Junttila, Juha, 2021. "Speculation and lottery-like demand in cryptocurrency markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 71(C).
    60. Badescu, Alexandru & Quaye, Enoch & Tunaru, Radu, 2022. "On non-negative equity guarantee calculations with macroeconomic variables related to house prices," Insurance: Mathematics and Economics, Elsevier, vol. 103(C), pages 119-138.
    61. Andrada-Félix, Julián & Fernandez-Perez, Adrian & Sosvilla-Rivero, Simón, 2020. "Distant or close cousins: Connectedness between cryptocurrencies and traditional currencies volatilities," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 67(C).
    62. Luo, Tao & Sun, Huaping & Zhang, Lixia & Bai, Jiancheng, 2024. "Do the dynamics of macroeconomic attention drive the yen/dollar exchange market volatility?," International Review of Economics & Finance, Elsevier, vol. 89(PB), pages 597-611.
    63. Ha, Le Thanh & Bouteska, Ahmed & Mefteh-Wali, Salma & The Anh, Pham, 2023. "Fluctuations in gold prices in Vietnam during the COVID-19 pandemic: Insights from a time-varying parameter autoregression model," Resources Policy, Elsevier, vol. 86(PB).
    64. Yin, Libo & Nie, Jing & Han, Liyan, 2021. "Understanding cryptocurrency volatility: The role of oil market shocks," International Review of Economics & Finance, Elsevier, vol. 72(C), pages 233-253.
    65. Afees A. Salisu & Rangan Gupta & Oguzhan Cepni & Petre Caraiani, 2023. "Oil Shocks and State-Level Stock Market Volatility of the United States: A GARCH-MIDAS Approach," Working Papers 202327, University of Pretoria, Department of Economics.
    66. Liu, Min, 2022. "The driving forces of green bond market volatility and the response of the market to the COVID-19 pandemic," Economic Analysis and Policy, Elsevier, vol. 75(C), pages 288-309.
    67. Trucíos, Carlos, 2019. "Forecasting Bitcoin risk measures: A robust approach," International Journal of Forecasting, Elsevier, vol. 35(3), pages 836-847.
    68. Gaies, Brahim & Chaâbane, Najeh & Bouzouita, Nesrine, 2024. "Navigating the storm: Time-frequency quantile dependence and non-linear causality between crypto-currency market volatility and financial instability," The Quarterly Review of Economics and Finance, Elsevier, vol. 93(C), pages 43-70.
    69. Georgios A. Panos & Tatja Karkkainen & Adele Atkinson, 2020. "Financial Literacy and Attitudes to Cryptocurrencies," Working Papers 2020_26, Business School - Economics, University of Glasgow.
    70. Fabian Woebbeking, 2021. "Cryptocurrency volatility markets," Digital Finance, Springer, vol. 3(3), pages 273-298, December.
    71. Mamoona Zahid & Farhat Iqbal & Dimitrios Koutmos, 2022. "Forecasting Bitcoin Volatility Using Hybrid GARCH Models with Machine Learning," Risks, MDPI, vol. 10(12), pages 1-18, December.
    72. Zied Ftiti & Wael Louhichi & Hachmi Ben Ameur, 2023. "Cryptocurrency volatility forecasting: What can we learn from the first wave of the COVID-19 outbreak?," Annals of Operations Research, Springer, vol. 330(1), pages 665-690, November.
    73. Zhang, Li & Wang, Lu & Peng, Lijuan & Luo, Keyu, 2023. "Measuring the response of clean energy stock price volatility to extreme shocks," Renewable Energy, Elsevier, vol. 206(C), pages 1289-1300.
    74. Adediran, Idris A. & Swaray, Raymond, 2023. "Carbon trading amidst global uncertainty: The role of policy and geopolitical uncertainty," Economic Modelling, Elsevier, vol. 123(C).
    75. Mahdi Ghaemi Asl & David Roubaud, 2024. "Asymmetric interactions among cutting-edge technologies and pioneering conventional and Islamic cryptocurrencies: fresh evidence from intra-day-based good and bad volatilities," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-49, December.
    76. Yi, Yongsheng & He, Mengxi & Zhang, Yaojie, 2022. "Out-of-sample prediction of Bitcoin realized volatility: Do other cryptocurrencies help?," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    77. Nidhal Mgadmi & Azza Béjaoui & Wajdi Moussa, 2023. "Disentangling the Nonlinearity Effect in Cryptocurrency Markets During the Covid-19 Pandemic: Evidence from a Regime-Switching Approach," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 30(3), pages 457-473, September.
    78. Aysu Ahmadova & Taghi Guliyev & Khatai Aliyev, 2024. "The Relationship between Bitcoin and Nasdaq, U.S. Dollar Index and Commodities," International Journal of Energy Economics and Policy, Econjournals, vol. 14(1), pages 281-289, January.
    79. Ben Nouir, Jihed & Ben Haj Hamida, Hayet, 2023. "How do economic policy uncertainty and geopolitical risk drive Bitcoin volatility?," Research in International Business and Finance, Elsevier, vol. 64(C).
    80. Zhang, Li & Liang, Chao & Huynh, Luu Duc Toan & Wang, Lu & Damette, Olivier, 2024. "Measuring the impact of climate risk on renewable energy stock volatility: A case study of G20 economies," Journal of Economic Behavior & Organization, Elsevier, vol. 223(C), pages 168-184.
    81. Damien Kunjal & Faeezah Peerbhai & Paul-Francois Muzindutsi, 2022. "Political, economic, and financial country risks and the volatility of the South African Exchange Traded Fund market: A GARCH-MIDAS approach," Risk Management, Palgrave Macmillan, vol. 24(3), pages 236-258, September.
    82. Paolo Giudici & Gloria Polinesi, 2021. "Crypto price discovery through correlation networks," Annals of Operations Research, Springer, vol. 299(1), pages 443-457, April.
    83. Baur, Dirk G. & Dimpfl, Thomas, 2018. "Asymmetric volatility in cryptocurrencies," Economics Letters, Elsevier, vol. 173(C), pages 148-151.
    84. Chen, Zhonglu & Zhang, Li & Weng, Chen, 2023. "Does climate policy uncertainty affect Chinese stock market volatility?," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 369-381.
    85. Christian Francq & Baye Matar Kandji & Jean-Michel Zakoian, 2022. "Inference on Multiplicative Component GARCH without any Small-Order Moment," Working Papers 2022-09, Center for Research in Economics and Statistics.
    86. Rubaiyat Ahsan Bhuiyan & Afzol Husain & Changyong Zhang, 2023. "Diversification evidence of bitcoin and gold from wavelet analysis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-36, December.
    87. Ji Ho Kwon, 2021. "On the factors of Bitcoin’s value at risk," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-31, December.
    88. Eska, Fabian E. & Shi, Yanghua & Theissen, Erik & Uhrig-Homburg, Marliese, 2024. "Do design features explain the volatility of cryptocurrencies?," Finance Research Letters, Elsevier, vol. 66(C).
    89. Francisco Javier García-Corral & José Antonio Cordero-García & Jaime de Pablo-Valenciano & Juan Uribe-Toril, 2022. "A bibliometric review of cryptocurrencies: how have they grown?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-31, December.
    90. Pierre J. Venter & Eben Maré, 2021. "Univariate and Multivariate GARCH Models Applied to Bitcoin Futures Option Pricing," JRFM, MDPI, vol. 14(6), pages 1-14, June.
    91. Wang, Lu & Wu, Jiangbin & Cao, Yang & Hong, Yanran, 2022. "Forecasting renewable energy stock volatility using short and long-term Markov switching GARCH-MIDAS models: Either, neither or both?," Energy Economics, Elsevier, vol. 111(C).
    92. Uzonwanne, Godfrey, 2021. "Volatility and return spillovers between stock markets and cryptocurrencies," The Quarterly Review of Economics and Finance, Elsevier, vol. 82(C), pages 30-36.
    93. Maria Ghani & Usman Ghani, 2024. "Economic Policy Uncertainty and Emerging Stock Market Volatility," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 31(1), pages 165-181, March.
    94. Branimir Cvitko Cicvarić, 2020. "Volatility of Cryptocurrencies," Notitia - journal for economic, business and social issues, Notitia Ltd., vol. 1(6), pages 13-23, December.
    95. Michael McAleer, 2020. "Ten Most Highly Cited Papers in Journal of Risk and Financial Management (JRFM), 2018–2020," JRFM, MDPI, vol. 13(12), pages 1-5, November.
    96. Wu, Xinyu & Yin, Xuebao & Umar, Zaghum & Iqbal, Najaf, 2023. "Volatility forecasting in the Bitcoin market: A new proposed measure based on the VS-ACARR approach," The North American Journal of Economics and Finance, Elsevier, vol. 67(C).
    97. Cem Cagri Donmez & Doruk Sen & Ahmet Fatih Dereli & M. Bilal Horasan & Cagri Yildiz & Nergis Feride Kaplan Donmez, 2021. "An Investigation of Fiat Characterization and Evolutionary Dynamics of the Cryptocurrency Market," SAGE Open, , vol. 11(1), pages 21582440219, February.

  6. Conrad, Christian & Zumbach, Klaus Ulrich, 2016. "The effect of political communication on European financial markets during the sovereign debt crisis," Journal of Empirical Finance, Elsevier, vol. 39(PB), pages 209-214.
    See citations under working paper version above.
  7. Conrad, Christian & Mammen, Enno, 2016. "Asymptotics for parametric GARCH-in-Mean models," Journal of Econometrics, Elsevier, vol. 194(2), pages 319-329.
    See citations under working paper version above.
  8. Christian Conrad & Menelaos Karanasos, 2015. "Modelling the Link Between US Inflation and Output: The Importance of the Uncertainty Channel," Scottish Journal of Political Economy, Scottish Economic Society, vol. 62(5), pages 431-453, November.
    See citations under working paper version above.
  9. Christian Conrad & Karin Loch, 2015. "Anticipating Long‐Term Stock Market Volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(7), pages 1090-1114, November.
    See citations under working paper version above.
  10. Conrad, Christian & Loch, Karin, 2015. "The variance risk premium and fundamental uncertainty," Economics Letters, Elsevier, vol. 132(C), pages 56-60.
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  11. Neil Kellard & Denise Osborn & Jerry Coakley & Christian Conrad & Menelaos Karanasos, 2015. "On the Transmission of Memory in Garch-in-Mean Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(5), pages 706-720, September.

    Cited by:

    1. Conrad, Christian & Mammen , Enno, 2015. "Asymptotics for parametric GARCH-in-Mean Models," Working Papers 0579, University of Heidelberg, Department of Economics.
    2. Canepa, Alessandra, 2024. "Inflation dynamics and persistence: The importance of the uncertainty channel," The North American Journal of Economics and Finance, Elsevier, vol. 72(C).
    3. Canepa, Alessandra, 2022. "Ination Dynamics and Time-Varying Persistence: The Importance of the Uncertainty Channel," Department of Economics and Statistics Cognetti de Martiis. Working Papers 202211, University of Turin.
    4. Kesavarajah Mayandy & Paul Middleditch, 2022. "Monetary policy and inflation–output variability in Sri Lanka: Lessons for developing economies," Review of Development Economics, Wiley Blackwell, vol. 26(1), pages 259-279, February.
    5. Karanasos, M. & Koutroumpis, P. & Karavias, Y. & Kartsaklas, A. & Arakelian, V., 2016. "Inflation convergence in the EMU," Journal of Empirical Finance, Elsevier, vol. 39(PB), pages 241-253.

  12. Conrad, Christian & Loch, Karin & Rittler, Daniel, 2014. "On the macroeconomic determinants of long-term volatilities and correlations in U.S. stock and crude oil markets," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 26-40.

    Cited by:

    1. Fang, Libing & Bouri, Elie & Gupta, Rangan & Roubaud, David, 2019. "Does global economic uncertainty matter for the volatility and hedging effectiveness of Bitcoin?," International Review of Financial Analysis, Elsevier, vol. 61(C), pages 29-36.
    2. Rodríguez-Nava, Abigail & Venegas-Martínez, Francisco & Coronado, Semei & Rojas, Omar, 2018. "Oil prices and stock markets returns: a comparison among Brazil, Chile, and Mexico," Sección de Estudios de Posgrado e Investigación de la Escuela Superios de Economía del Instituto Politécnico Nacional, in: Universidad de Guadalajara & Instituto Politécnico Nacional (ed.), Recent Topics in Time Series and Finance: Theory and Applications in Emerging Markets, volume 2, chapter 8, pages 199-210, Escuela Superior de Economía, Instituto Politécnico Nacional.
    3. Yun-Shi Dai & Peng-Fei Dai & Wei-Xing Zhou, 2024. "The impact of geopolitical risk on the international agricultural market: Empirical analysis based on the GJR-GARCH-MIDAS model," Papers 2404.01641, arXiv.org.
    4. Nguyen, Hoang & Virbickaitė, Audronė, 2023. "Modeling stock-oil co-dependence with Dynamic Stochastic MIDAS Copula models," Energy Economics, Elsevier, vol. 124(C).
    5. Nguyen, Hoang & Javed, Farrukh, 2023. "Dynamic relationship between Stock and Bond returns: A GAS MIDAS copula approach," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 272-292.
    6. Mei, Dexiang & Zeng, Qing & Cao, Xiang & Diao, Xiaohua, 2019. "Uncertainty and oil volatility: New evidence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 155-163.
    7. Fang, Libing & Yu, Honghai & Huang, Yingbo, 2018. "The role of investor sentiment in the long-term correlation between U.S. stock and bond markets," International Review of Economics & Finance, Elsevier, vol. 58(C), pages 127-139.
    8. Alessandra Amendola & Marinella Boccia & Vincenzo Candila & Giampiero M. Gallo, 2020. "Energy and non–energy Commodities: Spillover Effects on African Stock Markets," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 9(4), pages 1-7.
    9. Amendola, Alessandra & Candila, Vincenzo & Scognamillo, Antonio, 2015. "On the influence of the U.S. monetary policy on the crude oil price volatility," 2015 Fourth Congress, June 11-12, 2015, Ancona, Italy 207860, Italian Association of Agricultural and Applied Economics (AIEAA).
    10. Liu, Zhenhua & Zhang, Huiying & Ding, Zhihua & Lv, Tao & Wang, Xu & Wang, Deqing, 2022. "When are the effects of economic policy uncertainty on oil–stock correlations larger? Evidence from a regime-switching analysis," Economic Modelling, Elsevier, vol. 114(C).
    11. Huabin Bian & Renhai Hua & Qingfu Liu & Ping Zhang, 2022. "Petroleum market volatility tracker in China," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(11), pages 2022-2040, November.
    12. Zhang, Xincheng & Wu, Shaojiang, 2024. "Natural resources and sustainable development: Evidence from the dynamic correlation between crude oil and gold market," International Review of Economics & Finance, Elsevier, vol. 96(PB).
    13. Duc Khuong Nguyen & Thomas Walther, 2020. "Modeling and forecasting commodity market volatility with long‐term economic and financial variables," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 126-142, March.
    14. Fang, Libing & Yu, Honghai & Li, Lei, 2017. "The effect of economic policy uncertainty on the long-term correlation between U.S. stock and bond markets," Economic Modelling, Elsevier, vol. 66(C), pages 139-145.
    15. Chen, Chuanglian & Zhou, Lichao & Sun, Chuanwang & Lin, Yuting, 2024. "Does oil future increase the network systemic risk of financial institutions in China?," Applied Energy, Elsevier, vol. 364(C).
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    26. Walid Chkili & Shawkat Hammoudeh & Duc Khuong Nguyen, 2014. "Volatility forecasting and risk management for commodity markets in the presence of asymmetry and long memory," Working Papers 2014-389, Department of Research, Ipag Business School.
    27. Wajdi Moussa & Azza Bejaoui & Nidhal Mgadmi, 2021. "Asymmetric Effect and Dynamic Relationships Between Stock Prices and Exchange Rates Volatility," Annals of Data Science, Springer, vol. 8(4), pages 837-859, December.
    28. El Mehdi, Imen Khanchel & Mghaieth, Asma, 2017. "Volatility spillover and hedging strategies between Islamic and conventional stocks in the presence of asymmetry and long memory," Research in International Business and Finance, Elsevier, vol. 39(PA), pages 595-611.
    29. Dimitriou, Dimitrios & Kenourgios, Dimitris, 2013. "Financial crises and dynamic linkages among international currencies," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 26(C), pages 319-332.
    30. Zouheir Mighri & Faysal Mansouri, 2014. "Modeling international stock market contagion using multivariate fractionally integrated APARCH approach," Cogent Economics & Finance, Taylor & Francis Journals, vol. 2(1), pages 1-25, December.
    31. Moussa Wajdi, 2019. "The dynamic relationship between stock index and exchange rate: Evidence for Tunis," Journal of Finance and Investment Analysis, SCIENPRESS Ltd, vol. 8(1), pages 1-4.
    32. Carl Lönnbark, 2016. "Asymmetry with respect to the memory in stock market volatilities," Empirical Economics, Springer, vol. 50(4), pages 1409-1419, June.
    33. Wadud, Sania & Gronwald, Marc & Durand, Robert B. & Lee, Seungho, 2023. "Co-movement between commodity and equity markets revisited—An application of the Thick Pen method," International Review of Financial Analysis, Elsevier, vol. 87(C).
    34. Chkili, Walid & Aloui, Chaker & Nguyen, Duc Khuong, 2014. "Instabilities in the relationships and hedging strategies between crude oil and US stock markets: Do long memory and asymmetry matter?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 33(C), pages 354-366.
    35. Zouheir Mighri, 2018. "On the Dynamic Linkages Among International Emerging Currencies," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 16(2), pages 427-473, June.
    36. Markus Vogl, 2022. "Quantitative modelling frontiers: a literature review on the evolution in financial and risk modelling after the financial crisis (2008–2019)," SN Business & Economics, Springer, vol. 2(12), pages 1-69, December.
    37. Kenourgios, Dimitris & Dimitriou, Dimitrios, 2015. "Contagion of the Global Financial Crisis and the real economy: A regional analysis," Economic Modelling, Elsevier, vol. 44(C), pages 283-293.
    38. Liow, Kim Hiang & Song, Jeongseop, 2020. "Dynamic interdependence of ASEAN5 with G5 stock markets," Emerging Markets Review, Elsevier, vol. 45(C).
    39. Sang Hoon Kang & Ron McIver & Seong-Min Yoon, 2016. "Modeling Time-Varying Correlations in Volatility Between BRICS and Commodity Markets," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 52(7), pages 1698-1723, July.
    40. Riadh El Abed, 2017. "On the Co-movements among East Asian Foreign Exchange Markets: A Multivariate FIAPARCH-DCC approach," Economics Bulletin, AccessEcon, vol. 37(3), pages 2247-2259.
    41. A. M. M. Shahiduzzaman Quoreshi & Reaz Uddin & Viroj Jienwatcharamongkhol, 2019. "Equity Market Contagion in Return Volatility during Euro Zone and Global Financial Crises: Evidence from FIMACH Model," JRFM, MDPI, vol. 12(2), pages 1-18, June.
    42. Mensi, Walid & Hammoudeh, Shawkat & Nguyen, Duc Khuong & Kang, Sang Hoon, 2016. "Global financial crisis and spillover effects among the U.S. and BRICS stock markets," International Review of Economics & Finance, Elsevier, vol. 42(C), pages 257-276.
    43. Mensi, Walid & Hammoudeh, Shawkat & Kang, Sang Hoon, 2015. "Precious metals, cereal, oil and stock market linkages and portfolio risk management: Evidence from Saudi Arabia," Economic Modelling, Elsevier, vol. 51(C), pages 340-358.
    44. Chaker Aloui, 2015. "Volatility forecasting and risk management in some MENA stock markets: a nonlinear framework," Afro-Asian Journal of Finance and Accounting, Inderscience Enterprises Ltd, vol. 5(2), pages 160-192.
    45. Aloui, Chaker & Hkiri, Besma, 2014. "Co-movements of GCC emerging stock markets: New evidence from wavelet coherence analysis," Economic Modelling, Elsevier, vol. 36(C), pages 421-431.
    46. Kenourgios, Dimitris & Papadamou, Stephanos & Dimitriou, Dimitrios, 2015. "On quantitative easing and high frequency exchange rate dynamics," Research in International Business and Finance, Elsevier, vol. 34(C), pages 110-125.
    47. Muhammad Niaz Khan & Suzanne G. M. Fifield & Nongnuch Tantisantiwong & David M. Power, 2022. "Changes in co-movement and risk transmission between South Asian stock markets amidst the development of regional co-operation," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 36(1), pages 87-117, March.
    48. Wamg, Jianxin, 2011. "Forecasting Volatility in Asian Stock Markets: Contributions of Local, Regional, and Global Factors," Asian Development Review, Asian Development Bank, vol. 28(2), pages 32-57.

  16. Conrad, Christian & Karanasos, Menelaos & Zeng, Ning, 2010. "The link between macroeconomic performance and variability in the UK," Economics Letters, Elsevier, vol. 106(3), pages 154-157, March.

    Cited by:

    1. M. Tariq Majeed & Ayesha Noreen, 2018. "Financial Development and Output Volatility: A Cross-Sectional Panel Data Analysis," Lahore Journal of Economics, Department of Economics, The Lahore School of Economics, vol. 23(1), pages 97-141, Jan-June.
    2. Polito, Vito & Spencer, Peter, 2011. "UK Macroeconomic Volatility and the Welfare Costs of Inflation," Cardiff Economics Working Papers E2011/23, Cardiff University, Cardiff Business School, Economics Section.
    3. Alessandra Canepa, & Karanasos, Menelaos & Paraskevopoulos, Athanasios & Chini, Emilio Zanetti, 2022. "Forecasting Ination: A GARCH-in-Mean-Level Model with Time Varying Predictability," Department of Economics and Statistics Cognetti de Martiis. Working Papers 202212, University of Turin.
    4. Neil Kellard & Denise Osborn & Jerry Coakley & Christian Conrad & Menelaos Karanasos, 2015. "On the Transmission of Memory in Garch-in-Mean Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(5), pages 706-720, September.
    5. Canepa, Alessandra, 2024. "Inflation dynamics and persistence: The importance of the uncertainty channel," The North American Journal of Economics and Finance, Elsevier, vol. 72(C).
    6. Karanasos, Menelaos & Paraskevopoulos, Alexandros G. & Menla Ali, Faek & Karoglou, Michail & Yfanti, Stavroula, 2014. "Modelling stock volatilities during financial crises: A time varying coefficient approach," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 113-128.
    7. Kushal Banik Chowdhury & Nityananda Sarkar, 2019. "Regime Dependent Effect Of Output Growth On Output Growth Uncertainty: Evidence From Oecd Countries," Bulletin of Economic Research, Wiley Blackwell, vol. 71(3), pages 257-282, July.
    8. Menelaos Karanasos & Alexandros Paraskevopoulos & Faek Menla Ali & Michail Karoglou & Stavroula Yfanti, 2014. "Modelling Returns and Volatilities During Financial Crises: a Time Varying Coefficient Approach," Papers 1403.7179, arXiv.org.
    9. Canepa, Alessandra, 2022. "Ination Dynamics and Time-Varying Persistence: The Importance of the Uncertainty Channel," Department of Economics and Statistics Cognetti de Martiis. Working Papers 202211, University of Turin.
    10. Mehmet Balcilar & Zeynel Abidin Ozdemir, 2020. "A re-examination of growth and growth uncertainty relationship in a stochastic volatility in the mean model with time-varying parameters," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 47(3), pages 611-641, August.
    11. B. Balaji & S. Raja Sethu Durai & M. Ramachandran, 2018. "Spillover Effects of Real and Nominal Uncertainties in India," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 16(1), pages 143-162, December.
    12. Glas, Alexander & Hartmann, Matthias, 2016. "Inflation uncertainty, disagreement and monetary policy: Evidence from the ECB Survey of Professional Forecasters," VfS Annual Conference 2016 (Augsburg): Demographic Change 145888, Verein für Socialpolitik / German Economic Association.
    13. 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.
    14. Menelaos Karanasos & Ning Zeng, 2013. "Conditional heteroskedasticity in macroeconomics data: UK inflation, output growth and their uncertainties," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 12, pages 266-288, Edward Elgar Publishing.

  17. Conrad, Christian & Karanasos, Menelaos, 2010. "Negative Volatility Spillovers In The Unrestricted Eccc-Garch Model," Econometric Theory, Cambridge University Press, vol. 26(3), pages 838-862, June.
    See citations under working paper version above.
  18. Christian Conrad & Michael J. Lamla, 2010. "The High-Frequency Response of the EUR-USD Exchange Rate to ECB Communication," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 42(7), pages 1391-1417, October.

    Cited by:

    1. Shiwei Su & Ahmad Hassan Ahmad & Justine Wood, 2020. "How effective is central bank communication in emerging economies? An empirical analysis of the chinese money markets responses to the people’s bank of China’s policy communications," Review of Quantitative Finance and Accounting, Springer, vol. 54(4), pages 1195-1219, May.
    2. Beckmann, Joscha & Czudaj, Robert, 2017. "Exchange rate expectations and economic policy uncertainty," European Journal of Political Economy, Elsevier, vol. 47(C), pages 148-162.
    3. Hayo, Bernd & Neuenkirch, Matthias, 2015. "Central bank communication in the financial crisis: Evidence from a survey of financial market participants," Journal of International Money and Finance, Elsevier, vol. 59(C), pages 166-181.
    4. Beckmann, Joscha & Czudaj, Robert L. & Arora, Vipin, 2020. "The relationship between oil prices and exchange rates: Revisiting theory and evidence," Energy Economics, Elsevier, vol. 88(C).
    5. Serdengeçti, Süleyman & Sensoy, Ahmet & Nguyen, Duc Khuong, 2021. "Dynamics of return and liquidity (co) jumps in emerging foreign exchange markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 73(C).
    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. Ehrmann, Michael & Osbat, Chiara & Stráský, Jan & Uusküla, Lenno, 2013. "The euro exchange rate during the European sovereign debt crisis - dancing to its own tune?," Working Paper Series 1532, European Central Bank.
    8. Bjerkander, Lena & Glas, Alexander, 2024. "Talking in a language that everyone can understand? Clarity of speeches by the ECB Executive Board," Journal of International Money and Finance, Elsevier, vol. 149(C).
    9. Krieger, Kevin & Mauck, Nathan & Vasquez, Joseph, 2014. "Comparing U.S. and European Market Volatility Responses to Interest Rate Policy Announcements," MPRA Paper 52959, University Library of Munich, Germany.
    10. Aakriti Mathur & Rajeswari Sengupta, 2019. "Analysing monetary policy statements of the Reserve Bank of India," IHEID Working Papers 08-2019, Economics Section, The Graduate Institute of International Studies.
    11. Julian A. Parra-Polania & Andrés Sánchez-Jabba & Miguel Sarmiento, 2022. "Oral FX Interventions in Emerging Markets: the Colombian case," Borradores de Economia 1194, Banco de la Republica de Colombia.
    12. Brzeszczyński, Janusz & Kutan, Ali M., 2015. "Public information arrival and investor reaction during a period of institutional change: An episode of early years of a newly independent central bank," Journal of Comparative Economics, Elsevier, vol. 43(3), pages 727-753.
    13. Michael Ehrmann & Jonathan Talmi, 2016. "Starting from a Blank Page? Semantic Similarity in Central Bank Communication and Market Volatility," Staff Working Papers 16-37, Bank of Canada.
    14. Donato Masciandaro & Davide Romelli & Gaia Rubera, 2021. "Monetary policy and financial markets: evidence from Twitter traffic," BAFFI CAREFIN Working Papers 21160, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    15. Beckmann, Joscha & Czudaj, Robert, 2017. "Exchange rate expectations since the financial crisis: Performance evaluation and the role of monetary policy and safe haven," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168291, Verein für Socialpolitik / German Economic Association.
    16. Marc Anderes & Alexander Rathke & Sina Streicher & Jan-Egbert Sturm, 2021. "The role of ECB communication in guiding markets," Public Choice, Springer, vol. 186(3), pages 351-383, March.
    17. Donato Masciandaro & Oana Peia & Davide Romelli, 2022. "Central Bank Communication and Social Media: From Silence to Twitter," BAFFI CAREFIN Working Papers 22187, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    18. Conrad, Christian & Zumbach, Klaus Ulrich, 2016. "The effect of political communication on European financial markets during the sovereign debt crisis," Journal of Empirical Finance, Elsevier, vol. 39(PB), pages 209-214.
    19. Eichler, Stefan & Littke, Helge C. N., 2017. "Central bank transparency and the volatility of exchange rates," IWH Discussion Papers 22/2017, Halle Institute for Economic Research (IWH).
    20. Enders, Zeno & Hünnekes, Franziska & Müller, Gernot J., 2019. "Monetary Policy Announcements and Expectations: Evidence from German Firms," Working Papers 10, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
    21. Dooruj Rambaccussing & Craig Menzies & Andrzej Kwiatkowski, 2022. "Look who’s Talking: Individual Committee members’ impact on inflation expectations," Dundee Discussion Papers in Economics 305, Economic Studies, University of Dundee.
    22. Hugo Oriola & Matthieu Picault, 2023. "Opportunistic Political Central Bank Coverage: Does media coverage of ECB's Monetary Policy Impacts German Political Parties' Popularity?," EconomiX Working Papers 2023-30, University of Paris Nanterre, EconomiX.
    23. Lamla, Michael J & Vinogradov, Dmitri V, 2019. "Central Bank Announcements: Big News for Little People?," Essex Finance Centre Working Papers 25125, University of Essex, Essex Business School.
    24. Bartsch, Zachary, 2019. "Economic policy uncertainty and dollar-pound exchange rate return volatility," Journal of International Money and Finance, Elsevier, vol. 98(C), pages 1-1.
    25. Aleš Bulíř & Jaromír Hurník & Kateřina Šmídková, 2016. "What Do Central Banks Know about Inflation Factors?," Open Economies Review, Springer, vol. 27(4), pages 795-810, September.
    26. Smales, L.A. & Apergis, N., 2017. "Understanding the impact of monetary policy announcements: The importance of language and surprises," Journal of Banking & Finance, Elsevier, vol. 80(C), pages 33-50.
    27. Eichler, Stefan & Littke, Helge C.N., 2018. "Central bank transparency and the volatility of exchange rates," Journal of International Money and Finance, Elsevier, vol. 89(C), pages 23-49.
    28. Amrendra Pandey & Jagadish Shettigar & Amarnath Bose, 2021. "Evaluation of the Inflation Forecasting Process of the Reserve Bank of India: A Text Analysis Approach," SAGE Open, , vol. 11(3), pages 21582440211, July.
    29. Kumar, Satish, 2016. "Evidence of information transmission across currency futures markets using frequency domain tests," The North American Journal of Economics and Finance, Elsevier, vol. 37(C), pages 319-327.
    30. Linkon Mondal, 2014. "Volatility spillover between the RBI’s intervention and exchange rate," International Economics and Economic Policy, Springer, vol. 11(4), pages 549-560, December.
    31. Valerio Astuti & Alessio Ciarlone & Alberto Coco, 2022. "The role of central bank communication in inflation-targeting Eastern European emerging economies," Temi di discussione (Economic working papers) 1381, Bank of Italy, Economic Research and International Relations Area.
    32. Besma Hamdi & Sami Hammami, 2018. "The Crisis of Sovereign Debt in the Euro Zone: Effect on the Banking Sector," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 9(3), pages 822-832, September.
    33. Lars Winkelmann & Markus Bibinger & Tobias Linzert, 2016. "ECB Monetary Policy Surprises: Identification Through Cojumps in Interest Rates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(4), pages 613-629, June.
    34. Barbara Bedowska-Sojka, 2011. "The Impact of Macro News on Volatility of Stock Exchanges," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 11, pages 99-110.
    35. Lucian Liviu Albu & Radu Lupu & Adrian Cantemir Călin, 2016. "Impact Of FOMC Official Speeches on the Intraday Dynamics of CDS Markets," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 5-12, June.
    36. Hipòlit Torró, 2018. "The Response of European Energy Prices to ECB Monetary Policy," Working Papers 2018.09, Fondazione Eni Enrico Mattei.
    37. Linzert, Tobias & Winkelmann, Lars & Bibinger, Markus, 2014. "ECB monetary policy surprises: identification through cojumps in interest rates," Working Paper Series 1674, European Central Bank.
    38. Santos, Francisco Luna & Garcia, Márcio Gomes Pinto & Medeiros, Marcelo Cunha, 2016. "The High Frequency Impact of Macroeconomic Announcements in the Brazilian Futures Markets," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 36(2), November.
    39. Mr. Aleš Bulíř & Jaromír Hurník & Ms. Katerina Smídková, 2014. "Inflation Reports and Models: How Well Do Central Banks Really Write?," IMF Working Papers 2014/091, International Monetary Fund.
    40. Claudio Morana, 2016. "The US$/€ exchange rate: Structural modeling and forecasting during the recent financial crises," CeRP Working Papers 155, Center for Research on Pensions and Welfare Policies, Turin (Italy).
    41. Conrad, Christian & Karanasos, Menelaos & Zeng, Ning, 2011. "Multivariate fractionally integrated APARCH modeling of stock market volatility: A multi-country study," Journal of Empirical Finance, Elsevier, vol. 18(1), pages 147-159, January.
    42. Christopher J. Neely, 2011. "A survey of announcement effects on foreign exchange volatility and jumps," Review, Federal Reserve Bank of St. Louis, vol. 93(Sep), pages 361-385.
    43. Marcio Garcia & Marcelo Medeiros & Francisco Eduardo de Luna e Almeida Santos, 2014. "The impact of macroeconomic announcements in the Brazilian futures markets," Textos para discussão 623, Department of Economics PUC-Rio (Brazil).
    44. Mr. Martin Cihak & Ms. Katerina Smídková & Mr. Aleš Bulíř, 2008. "Writing Clearly: ECB’s Monetary Policy Communication," IMF Working Papers 2008/252, International Monetary Fund.
    45. Glas, Alexander & Hartmann, Matthias, 2016. "Inflation uncertainty, disagreement and monetary policy: Evidence from the ECB Survey of Professional Forecasters," VfS Annual Conference 2016 (Augsburg): Demographic Change 145888, Verein für Socialpolitik / German Economic Association.
    46. Dewachter, Hans & Erdemlioglu, Deniz & Gnabo, Jean-Yves & Lecourt, Christelle, 2014. "The intra-day impact of communication on euro-dollar volatility and jumps," Journal of International Money and Finance, Elsevier, vol. 43(C), pages 131-154.
    47. Cyril May & Greg Farrell & Jannie Rossouw, 2018. "Do Monetary Policy Announcements Affect Exchange Rate Returns and Volatility of Returns? Some Evidence from High‐Frequency Intra‐Day South African Data," South African Journal of Economics, Economic Society of South Africa, vol. 86(3), pages 308-338, September.
    48. Matthieu Picault & Thomas Renault, 2017. "Words are not all created equal: A new measure of ECB communication," Post-Print hal-03205121, HAL.
    49. Yin Germaschewski & Jaroslav Horvath & Jiansheng Zhong, 2022. "Oral interventions in the foreign exchange market: evidence from Australia," Empirical Economics, Springer, vol. 62(6), pages 2713-2737, June.
    50. Guo, Junjie & Guo, Yumei & Miao, Shan & Pang, Xin, 2021. "An investigation of semantic similarity in PBOC’s communication on RMB volatility," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 441-455.
    51. Bernd Hayo & Kai Henseler & Marc Steffen Rapp & Johannes Zahner, 2020. "Complexity of ECB Communication and Financial Market Trading," MAGKS Papers on Economics 201919, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    52. Weber, Christoph S., 2019. "The effect of central bank transparency on exchange rate volatility," Journal of International Money and Finance, Elsevier, vol. 95(C), pages 165-181.
    53. Conrad, Christian & Glas, Alexander, 2018. "‘Déjà vol’ revisited: Survey forecasts of macroeconomic variables predict volatility in the cross-section of industry portfolios," Working Papers 0655, University of Heidelberg, Department of Economics.
    54. Niţoi, Mihai & Pochea, Maria-Miruna & Radu, Ştefan-Constantin, 2023. "Unveiling the sentiment behind central bank narratives: A novel deep learning index," Journal of Behavioral and Experimental Finance, Elsevier, vol. 38(C).
    55. Keiichi Goshima & Yusuke Kumano, 2018. "Monetary Policy Announcement and Algorithmic News Trading in the Foreign Exchange Market," IMES Discussion Paper Series 18-E-13, Institute for Monetary and Economic Studies, Bank of Japan.
    56. Arghyrou, Michael G. & Pourpourides, Panayiotis, 2016. "Inflation announcements and asymmetric exchange rate responses," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 40(C), pages 80-84.
    57. Patrick Hirsch & Lars P. Feld & Ekkehard A. Köhler, 2023. "Breaking Monetary Policy News: The Role of Mass Media Coverage of ECB Announcements for Public Inflation Expectations," CESifo Working Paper Series 10285, CESifo.
    58. Conrad, Christian & Stuermer, Karin, 2017. "On the economic determinants of optimal stock-bond portfolios: international evidence," Working Papers 0636, University of Heidelberg, Department of Economics.
    59. Jorge Carvalho & Gualter Couto & Pedro Pimentel, 2022. "EUR/USD Exchange Rate Characterization: Study of Events," Economies, MDPI, vol. 10(12), pages 1-14, November.
    60. Peter Tillmann, 2020. "Financial Markets and Dissent in the ECB’s Governing Council," MAGKS Papers on Economics 202048, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    61. Conrad, Christian & Loch, Karin, 2016. "Macroeconomic expectations and the time-varying stock-bond correlation: international evidence," VfS Annual Conference 2016 (Augsburg): Demographic Change 145530, Verein für Socialpolitik / German Economic Association.
    62. Donato Masciandaro & Davide Romelli & Gaia Rubera, 2020. "Tweeting on Monetary Policy and Market Sentiments: The Central Bank Surprise Index," BAFFI CAREFIN Working Papers 20134, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    63. Liu, Yang & Han, Liyan & Yin, Libo, 2019. "News implied volatility and long-term foreign exchange market volatility," International Review of Financial Analysis, Elsevier, vol. 61(C), pages 126-142.
    64. Kenourgios, Dimitris & Papadamou, Stephanos & Dimitriou, Dimitrios, 2015. "On quantitative easing and high frequency exchange rate dynamics," Research in International Business and Finance, Elsevier, vol. 34(C), pages 110-125.
    65. Soriano, Pilar & Torró, Hipòlit, 2022. "The response of Brent crude oil to the European central bank monetary policy," Finance Research Letters, Elsevier, vol. 46(PA).

  19. Conrad, Christian, 2010. "Non-negativity conditions for the hyperbolic GARCH model," Journal of Econometrics, Elsevier, vol. 157(2), pages 441-457, August.
    See citations under working paper version above.
  20. Michael J. Lamla & Christian Conrad, 2007. "An den Lippen der EZB – Der KOF Monetary Policy Communicator," KOF Analysen, KOF Swiss Economic Institute, ETH Zurich, vol. 1(4), pages 33-45, March.

    Cited by:

    1. Lange, Kai-Robin & Reccius, Matthias & Schmidt, Tobias & Müller, Henrik & Roos, Michael W. M. & Jentsch, Carsten, 2022. "Towards extracting collective economic narratives from texts," Ruhr Economic Papers 963, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.

  21. Christian Conrad & Berthold R. Haag, 2006. "Inequality Constraints in the Fractionally Integrated GARCH Model," Journal of Financial Econometrics, Oxford University Press, vol. 4(3), pages 413-449.

    Cited by:

    1. Mawuli Segnon & Rangan Gupta & Keagile Lesame & Mark E. Wohar, 2019. "High-Frequency Volatility Forecasting of US Housing Markets," Working Papers 201977, University of Pretoria, Department of Economics.
    2. Claudio Morana, 2014. "Factor Vector Autoregressive Estimation of Heteroskedastic Persistent and Non Persistent Processes Subject to Structural Breaks," Working Papers 273, University of Milano-Bicocca, Department of Economics, revised May 2014.
    3. Li, Muyi & Li, Wai Keung & Li, Guodong, 2015. "A new hyperbolic GARCH model," Journal of Econometrics, Elsevier, vol. 189(2), pages 428-436.
    4. Kawakatsu Hiroyuki, 2021. "Simple Multivariate Conditional Covariance Dynamics Using Hyperbolically Weighted Moving Averages," Journal of Econometric Methods, De Gruyter, vol. 10(1), pages 33-52, January.
    5. Melike Bildirici & Özgür Ömer Ersin, 2014. "Nonlinearity, Volatility and Fractional Integration in Daily Oil Prices: Smooth Transition Autoregressive ST-FI(AP)GARCH Models," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 108-135, October.
    6. Shi, Yanlin & Ho, Kin-Yip, 2015. "Modeling high-frequency volatility with three-state FIGARCH models," Economic Modelling, Elsevier, vol. 51(C), pages 473-483.
    7. Chkili, Walid & Aloui, Chaker & Nguyen, Duc Khuong, 2012. "Asymmetric effects and long memory in dynamic volatility relationships between stock returns and exchange rates," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(4), pages 738-757.
    8. Bjoern Schulte-Tillmann & Mawuli Segnon & Timo Wiedemann, 2023. "A comparison of high-frequency realized variance measures: Duration- vs. return-based approaches," CQE Working Papers 10523, Center for Quantitative Economics (CQE), University of Muenster.
    9. Pan, Qunxing & Li, Peng & Du, Xiuli, 2023. "An improved FIGARCH model with the fractional differencing operator (1-νL)d," Finance Research Letters, Elsevier, vol. 55(PB).
    10. HAFNER, Christian & PREMINGER, Arie, 2016. "On Asymptotic Theory for ARCH(infinite) Models," LIDAM Discussion Papers CORE 2016030, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    11. Masato Ubukata & Toshiaki Watanabe, 2014. "Pricing Nikkei 225 Options Using Realized Volatility," The Japanese Economic Review, Japanese Economic Association, vol. 65(4), pages 431-467, December.
    12. Mawuli Segnon & Stelios Bekiros, 2020. "Forecasting volatility in bitcoin market," Annals of Finance, Springer, vol. 16(3), pages 435-462, September.
    13. Baillie, Richard T. & Morana, Claudio, 2009. "Modelling long memory and structural breaks in conditional variances: An adaptive FIGARCH approach," Journal of Economic Dynamics and Control, Elsevier, vol. 33(8), pages 1577-1592, August.
    14. Andre Lucas & Anne Opschoor, 2016. "Fractional Integration and Fat Tails for Realized Covariance Kernels and Returns," Tinbergen Institute Discussion Papers 16-069/IV, Tinbergen Institute, revised 07 Jul 2017.
    15. Koubaa, Yosra & Slim, Skander, 2019. "The relationship between trading activity and stock market volatility: Does the volume threshold matter?," Economic Modelling, Elsevier, vol. 82(C), pages 168-184.
    16. Baillie, Richard T. & Morana, Claudio, 2012. "Adaptive ARFIMA models with applications to inflation," Economic Modelling, Elsevier, vol. 29(6), pages 2451-2459.
    17. Bhaskar Bagchi & Biswajit Paul, 2023. "Effects of Crude Oil Price Shocks on Stock Markets and Currency Exchange Rates in the Context of Russia-Ukraine Conflict: Evidence from G7 Countries," JRFM, MDPI, vol. 16(2), pages 1-18, January.
    18. Groß-Klußmann, Axel & Hautsch, Nikolaus, 2011. "Predicting bid-ask spreads using long memory autoregressive conditional poisson models," SFB 649 Discussion Papers 2011-044, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    19. Yuanhua Feng & Thomas Gries & Sebastian Letmathe, 2023. "FIEGARCH, modulus asymmetric FILog-GARCH and trend-stationary dual long memory time series," Working Papers CIE 156, Paderborn University, CIE Center for International Economics.
    20. Kisswell Basira & Lawrence Dhliwayo & Knowledge Chinhamu & Retius Chifurira & Florence Matarise, 2024. "Estimation and Prediction of Commodity Returns Using Long Memory Volatility Models," Risks, MDPI, vol. 12(5), pages 1-20, April.
    21. Mawuli Segnon & Manuel Stapper, 2019. "Long Memory Conditional Heteroscedasticity in Count Data," CQE Working Papers 8219, Center for Quantitative Economics (CQE), University of Muenster.
    22. Christian Conrad & Michael J. Lamla, 2010. "The High‐Frequency Response of the EUR‐USD Exchange Rate to ECB Communication," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 42(7), pages 1391-1417, October.
    23. Conrad, Christian & Rittler, Daniel & Rotfuß, Waldemar, 2010. "Modeling and Explaining the Dynamics of European Union Allowance Prices at High-Frequency," Working Papers 0497, University of Heidelberg, Department of Economics.
    24. Dark, Jonathan, 2018. "Multivariate models with long memory dependence in conditional correlation and volatility," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 162-180.
    25. Karanasos, Menelaos & Yfanti, Stavroula & Karoglou, Michail, 2016. "Multivariate FIAPARCH modelling of financial markets with dynamic correlations in times of crisis," International Review of Financial Analysis, Elsevier, vol. 45(C), pages 332-349.
    26. Guglielmo Maria Caporale & Menelaos Karanasos & Stavroula Yfanti & Aris Kartsaklas, 2019. "Investors' Trading Behaviour and Stock Market Volatility during Crisis Periods: A Dual Long-Memory Model for the Korean Stock Exchange," CESifo Working Paper Series 7984, CESifo.
    27. Deniz Erdemlioglu & Sebastien Laurent & Christopher J. Neely, 2012. "Econometric modeling of exchange rate volatility and jumps," Working Papers 2012-008, Federal Reserve Bank of St. Louis.
    28. Morten Ørregaard Nielsen & Antoine L. Noël, 2021. "To infinity and beyond: Efficient computation of ARCH(∞) models," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(3), pages 338-354, May.
    29. Conrad, Christian, 2010. "Non-negativity conditions for the hyperbolic GARCH model," Journal of Econometrics, Elsevier, vol. 157(2), pages 441-457, August.
    30. Claudio Morana, 2013. "Factor Vector Autoregressive Estimation of Heteroskedastic Persistent and Non Persistent Processes Subject to Structural Breaks: New Insights on the US OIS SPreads Term Structure," Working Papers 233, University of Milano-Bicocca, Department of Economics, revised Feb 2013.
    31. Barbara Bedowska-Sojka, 2011. "The Impact of Macro News on Volatility of Stock Exchanges," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 11, pages 99-110.
    32. Sang Hoon Kang & SEONG-MIN YOON, 2008. "Asymmetry and Long Memory Features in Volatility: Evidence From Korean Stock Market," Korean Economic Review, Korean Economic Association, vol. 24, pages 383-412.
    33. Walid Chkili & Shawkat Hammoudeh & Duc Khuong Nguyen, 2014. "Volatility forecasting and risk management for commodity markets in the presence of asymmetry and long memory," Working Papers 2014-389, Department of Research, Ipag Business School.
    34. Amélie Charles & Olivier Darné, 2012. "Volatility Persistence in Crude Oil Markets," Working Papers hal-00719387, HAL.
    35. El Mehdi, Imen Khanchel & Mghaieth, Asma, 2017. "Volatility spillover and hedging strategies between Islamic and conventional stocks in the presence of asymmetry and long memory," Research in International Business and Finance, Elsevier, vol. 39(PA), pages 595-611.
    36. Conrad, Christian & Karanasos, Menelaos & Zeng, Ning, 2011. "Multivariate fractionally integrated APARCH modeling of stock market volatility: A multi-country study," Journal of Empirical Finance, Elsevier, vol. 18(1), pages 147-159, January.
    37. Zouheir Mighri & Faysal Mansouri, 2014. "Modeling international stock market contagion using multivariate fractionally integrated APARCH approach," Cogent Economics & Finance, Taylor & Francis Journals, vol. 2(1), pages 1-25, December.
    38. Adnen Ben Nasr & Ahdi N. Ajmi & Rangan Gupta, 2013. "Modeling the Volatility of the Dow Jones Islamic Market World Index Using a Fractionally Integrated Time Varying GARCH (FITVGARCH) Model," Working Papers 201357, University of Pretoria, Department of Economics.
    39. Yanlin Shi & Yang Yang, 2018. "Modeling High Frequency Data with Long Memory and Structural Change: A-HYEGARCH Model," Risks, MDPI, vol. 6(2), pages 1-28, March.
    40. Christian Conrad & Menelaos Karanasos, 2008. "Negative Volatility Spillovers in the Unrestricted ECCC-GARCH Model," KOF Working papers 08-189, KOF Swiss Economic Institute, ETH Zurich.
    41. Carl Lönnbark, 2016. "Asymmetry with respect to the memory in stock market volatilities," Empirical Economics, Springer, vol. 50(4), pages 1409-1419, June.
    42. Trino-Manuel Ñíguez, 2008. "Volatility and VaR forecasting in the Madrid Stock Exchange," Spanish Economic Review, Springer;Spanish Economic Association, vol. 10(3), pages 169-196, September.
    43. Conrad, Christian & Karanasos, Menelaos, 2006. "The impulse response function of the long memory GARCH process," Economics Letters, Elsevier, vol. 90(1), pages 34-41, January.
    44. Belkhouja, Mustapha & Boutahary, Mohamed, 2011. "Modeling volatility with time-varying FIGARCH models," Economic Modelling, Elsevier, vol. 28(3), pages 1106-1116, May.
    45. Walid Chkili & Shawkat Hammoudeh & Duc Khuong Nguyen, 2013. "Long memory and asymmetry in the volatility of commodity markets and Basel Accord: choosing between models," Working Papers 2013-9, Department of Research, Ipag Business School.
    46. Richard T. Baille & Claudio Morana, 2009. "Investigating Inflation Dynamics and Structural Change with an Adaptive ARFIMA Approach," ICER Working Papers - Applied Mathematics Series 06-2009, ICER - International Centre for Economic Research.
    47. Hautsch, Nikolaus & Okhrin, Ostap & Ristig, Alexander, 2012. "Modeling time-varying dependencies between positive-valued high-frequency time series," SFB 649 Discussion Papers 2012-054, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    48. Lee, Oesook, 2018. "Stationarity and functional central limit theorem for ARCH(∞) models," Economics Letters, Elsevier, vol. 162(C), pages 107-111.
    49. Zouheir Mighri, 2018. "On the Dynamic Linkages Among International Emerging Currencies," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 16(2), pages 427-473, June.
    50. Adnen Ben Nasr & Mohamed Boutahar & Abdelwahed Trabelsi, 2010. "Fractionally integrated time varying GARCH model," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 19(3), pages 399-430, August.
    51. KIlIç, Rehim, 2011. "Long memory and nonlinearity in conditional variances: A smooth transition FIGARCH model," Journal of Empirical Finance, Elsevier, vol. 18(2), pages 368-378, March.
    52. Klein, Tony & Walther, Thomas, 2017. "Fast fractional differencing in modeling long memory of conditional variance for high-frequency data," Finance Research Letters, Elsevier, vol. 22(C), pages 274-279.
    53. Morten Ørregaard Nielsen & Antoine L. Noël, 2020. "To infinity and beyond: Efficient computation of ARCH(1) models," CREATES Research Papers 2020-13, Department of Economics and Business Economics, Aarhus University.
    54. Conrad, Christian & Schienle, Melanie, 2019. "Testing for an omitted multiplicative long-term component in GARCH models," Working Paper Series in Economics 121, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
    55. Masato Ubukata & Toshiaki Watanabe, 2011. "Pricing Nikkei 225 Options Using Realized Volatility," IMES Discussion Paper Series 11-E-18, Institute for Monetary and Economic Studies, Bank of Japan.
    56. Muyi Li & Wai Keung Li & Guodong Li, 2013. "On Mixture Memory Garch Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(6), pages 606-624, November.
    57. Sang Hoon Kang & Ron McIver & Seong-Min Yoon, 2016. "Modeling Time-Varying Correlations in Volatility Between BRICS and Commodity Markets," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 52(7), pages 1698-1723, July.
    58. Masato Ubukata & Toshiaki Watanabe, 2013. "Pricing Nikkei 225 Options Using Realized Volatility," Global COE Hi-Stat Discussion Paper Series gd12-273, Institute of Economic Research, Hitotsubashi University.
    59. J. Kim & A. Kartsaklas & M. Karanasos, 2005. "The volume–volatility relationship and the opening of the Korean stock market to foreign investors after the financial turmoil in 1997," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 12(3), pages 245-271, September.
    60. Rehim Kilic, 2011. "A conditional variance tale from an emerging economy's freely floating exchange rate," Applied Economics, Taylor & Francis Journals, vol. 43(19), pages 2465-2480.
    61. Christian M. Hafner & Arie Preminger, 2017. "On Asymptotic Theory for ARCH (∞) Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(6), pages 865-879, November.
    62. 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.
    63. Slim, Skander & Koubaa, Yosra & BenSaïda, Ahmed, 2017. "Value-at-Risk under Lévy GARCH models: Evidence from global stock markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 46(C), pages 30-53.
    64. Mawuli Segnon & Stelios Bekiros, 2019. "Forecasting Volatility in Cryptocurrency Markets," CQE Working Papers 7919, Center for Quantitative Economics (CQE), University of Muenster.

  22. Conrad, Christian & Karanasos, Menelaos, 2006. "The impulse response function of the long memory GARCH process," Economics Letters, Elsevier, vol. 90(1), pages 34-41, January.

    Cited by:

    1. Chi-Wei Su & Hui Yu & Hsu-Ling Chang & Xiao-Lin Li, 2017. "How does inflation determine inflation uncertainty? A Chinese perspective," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(3), pages 1417-1434, May.
    2. Claudio Morana, 2014. "Factor Vector Autoregressive Estimation of Heteroskedastic Persistent and Non Persistent Processes Subject to Structural Breaks," Working Papers 273, University of Milano-Bicocca, Department of Economics, revised May 2014.
    3. I-Chun Tsai & Shu-Hen Chiang, 2018. "Risk Transfer among Housing Markets in Major Cities in China," Sustainability, MDPI, vol. 10(7), pages 1-20, July.
    4. Neil Kellard & Denise Osborn & Jerry Coakley & Christian Conrad & Menelaos Karanasos, 2015. "On the Transmission of Memory in Garch-in-Mean Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(5), pages 706-720, September.
    5. Conrad, Christian & Weber, Enzo, 2013. "Measuring Persistence in Volatility Spillovers," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79850, Verein für Socialpolitik / German Economic Association.
    6. M. Karanasos & S. Yfanti & A. Christopoulos, 2021. "The long memory HEAVY process: modeling and forecasting financial volatility," Annals of Operations Research, Springer, vol. 306(1), pages 111-130, November.
    7. Yuanhua Feng & Thomas Gries & Sebastian Letmathe, 2023. "FIEGARCH, modulus asymmetric FILog-GARCH and trend-stationary dual long memory time series," Working Papers CIE 156, Paderborn University, CIE Center for International Economics.
    8. Conrad, Christian, 2010. "Non-negativity conditions for the hyperbolic GARCH model," Journal of Econometrics, Elsevier, vol. 157(2), pages 441-457, August.
    9. Kim, Yujin & Hwang, Eunju, 2018. "A dynamic Markov regime-switching GARCH model and its cumulative impulse response function," Statistics & Probability Letters, Elsevier, vol. 139(C), pages 20-30.
    10. Tim Bollerslev, 2008. "Glossary to ARCH (GARCH)," CREATES Research Papers 2008-49, Department of Economics and Business Economics, Aarhus University.
    11. Conrad, Christian & Karanasos, Menelaos & Zeng, Ning, 2011. "Multivariate fractionally integrated APARCH modeling of stock market volatility: A multi-country study," Journal of Empirical Finance, Elsevier, vol. 18(1), pages 147-159, January.
    12. Karanasos, M. & Kartsaklas, A., 2009. "Dual long-memory, structural breaks and the link between turnover and the range-based volatility," Journal of Empirical Finance, Elsevier, vol. 16(5), pages 838-851, December.
    13. Qiang Xiao & Yang Gao & Dan Hu & Hong Tan & Tianxiang Wang, 2011. "Assessment of the Interactions between Economic Growth and Industrial Wastewater Discharges Using Co-integration Analysis: A Case Study for China’s Hunan Province," IJERPH, MDPI, vol. 8(7), pages 1-14, July.
    14. Yuanhua Feng & Jan Beran & Sebastian Letmathe & Sucharita Ghosh, 2020. "Fractionally integrated Log-GARCH with application to value at risk and expected shortfall," Working Papers CIE 137, Paderborn University, CIE Center for International Economics.

  23. Conrad Christian & Karanasos Menelaos, 2005. "Dual Long Memory in Inflation Dynamics across Countries of the Euro Area and the Link between Inflation Uncertainty and Macroeconomic Performance," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(4), pages 1-38, December.

    Cited by:

    1. Ngene, Geoffrey & Tah, Kenneth A. & Darrat, Ali F., 2017. "Long memory or structural breaks: Some evidence for African stock markets," Review of Financial Economics, Elsevier, vol. 34(C), pages 61-73.
    2. Meller, Barbara & Nautz, Dieter, 2012. "Inflation persistence in the Euro area before and after the European Monetary Union," Economic Modelling, Elsevier, vol. 29(4), pages 1170-1176.
    3. Geoffrey Ngene & Ann Nduati Mungai & Allen K. Lynch, 2018. "Long-Term Dependency Structure and Structural Breaks: Evidence from the U.S. Sector Returns and Volatility," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 21(02), pages 1-38, June.
    4. Meller, Barbara & Nautz, Dieter, 2009. "The impact of the European Monetary Union on inflation persistence in the Euro area," SFB 649 Discussion Papers 2009-037, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    5. Fountas, Stilianos & Karanasos, Menelaos, 2007. "Inflation, output growth, and nominal and real uncertainty: Empirical evidence for the G7," Journal of International Money and Finance, Elsevier, vol. 26(2), pages 229-250, March.
    6. Yuanhua Feng & Thomas Gries & Sebastian Letmathe, 2023. "FIEGARCH, modulus asymmetric FILog-GARCH and trend-stationary dual long memory time series," Working Papers CIE 156, Paderborn University, CIE Center for International Economics.
    7. Hasan Dinçer & Serhat Yüksel & Fatih Pınarbaşı & Mehmet Ali Alhan, 2020. "Risky Financial Assets in Financial Integration and the Impacts of Derivatives on Banking Returns," World Scientific Book Chapters, in: Stéphane Goutte & Khaled Guesmi (ed.), Risk Factors and Contagion in Commodity Markets and Stocks Markets, chapter 6, pages 133-159, World Scientific Publishing Co. Pte. Ltd..
    8. Caporale, Guglielmo Maria & Onorante, Luca & Paesani, Paolo, 2010. "Inflation and inflation uncertainty in the euro area," Working Paper Series 1229, European Central Bank.
    9. Guglielmo Maria Caporale & Alexandros Kontonikas, 2006. "The Euro and Inflation Uncertainty in the European Monetary Union," CESifo Working Paper Series 1842, CESifo.
    10. Abdullah Sultan Al Shammre & Benaissa Chidmi, 2023. "Oil Price Forecasting Using FRED Data: A Comparison between Some Alternative Models," Energies, MDPI, vol. 16(11), pages 1-24, May.
    11. Mehmet Balcilar & Zeynel Abidin Ozdemir, 2013. "Asymmetric and Time-Varying Causality between Inflation and Inflation Uncertainty in G-7 Countries," Scottish Journal of Political Economy, Scottish Economic Society, vol. 60(1), pages 1-42, February.
    12. Conrad, Christian, 2010. "Non-negativity conditions for the hyperbolic GARCH model," Journal of Econometrics, Elsevier, vol. 157(2), pages 441-457, August.
    13. Conrad, Christian & Hartmann, Matthias, 2019. "On the determinants of long-run inflation uncertainty: Evidence from a panel of 17 developed economies," European Journal of Political Economy, Elsevier, vol. 56(C), pages 233-250.
    14. Canarella, Giorgio & Miller, Stephen M., 2017. "Inflation targeting and inflation persistence: New evidence from fractional integration and cointegration," Journal of Economics and Business, Elsevier, vol. 92(C), pages 45-62.
    15. E. Tsanana & X. Chapsa & C. Katrakilidis, 2016. "Is growth corrupted or bureaucratic? Panel evidence from the enlarged EU," Applied Economics, Taylor & Francis Journals, vol. 48(33), pages 3131-3147, July.
    16. Mahadevan, Renuka & Suardi, Sandy, 2011. "The effects of uncertainty dynamics on exports, imports and productivity growth," Journal of Asian Economics, Elsevier, vol. 22(2), pages 174-188, April.
    17. Rinke, Saskia & Busch, Marie & Leschinski, Christian, 2017. "Long Memory, Breaks, and Trends: On the Sources of Persistence in Inflation Rates," Hannover Economic Papers (HEP) dp-584, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    18. Karanasos, M. & Kartsaklas, A., 2009. "Dual long-memory, structural breaks and the link between turnover and the range-based volatility," Journal of Empirical Finance, Elsevier, vol. 16(5), pages 838-851, December.
    19. Daniela Viorica & Danut Jemna & Carmen Pintilescu & Mircea Asandului, 2014. "The Relationship between Inflation and Inflation Uncertainty. Empirical Evidence for the Newest EU Countries," PLOS ONE, Public Library of Science, vol. 9(3), pages 1-11, March.
    20. Glas, Alexander & Hartmann, Matthias, 2016. "Inflation uncertainty, disagreement and monetary policy: Evidence from the ECB Survey of Professional Forecasters," VfS Annual Conference 2016 (Augsburg): Demographic Change 145888, Verein für Socialpolitik / German Economic Association.
    21. Conrad, Christian & Karanasos, Menelaos, 2006. "The impulse response function of the long memory GARCH process," Economics Letters, Elsevier, vol. 90(1), pages 34-41, January.
    22. Said Zamin Shah & Said Zamin Shah & Ahmad Zubaidi Baharumshah & Muzafar Shah Habibullah & Law Siong Hook, 2017. "The Asymmetric Effects of Real and Nominal Uncertainty on Inflation and Output Growth: Empirical Evidence from Bangladesh," International Journal of Economics and Financial Issues, Econjournals, vol. 7(1), pages 377-386.
    23. Rehab OSMAN, 2010. "SADC EPAs with the EU: the Right or a Blight Way for Development," EcoMod2010 259600127, EcoMod.
    24. Apostolos Serletis & Jinan Liu, 2022. "Inflation and economic activity in advanced and emerging economies," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4196-4223, October.
    25. Kang, Sang Hoon & Yoon, Seong-Min, 2013. "Modeling and forecasting the volatility of petroleum futures prices," Energy Economics, Elsevier, vol. 36(C), pages 354-362.
    26. J. Kim & A. Kartsaklas & M. Karanasos, 2005. "The volume–volatility relationship and the opening of the Korean stock market to foreign investors after the financial turmoil in 1997," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 12(3), pages 245-271, September.
    27. Xanthippi Chapsa & Athanasios L. Athanasenas & Nikolaos Tabakis, 2019. "Real Convergence in EU-15: A Comparative Analysis of North versus South Europe," European Research Studies Journal, European Research Studies Journal, vol. 0(3), pages 3-21.
    28. Jacques Sapir, 2018. "The EMU’s Twisted Foundations: How to Use and Misuse Economic Theory," Studies on Russian Economic Development, Springer, vol. 29(5), pages 497-506, September.
    29. Fountas, Stilianos & Karanasos, Menelaos, 2006. "The relationship between economic growth and real uncertainty in the G3," Economic Modelling, Elsevier, vol. 23(4), pages 638-647, July.
    30. Gündüz, Yalin & Kaya, Orcun, 2014. "Impacts of the financial crisis on eurozone sovereign CDS spreads," Journal of International Money and Finance, Elsevier, vol. 49(PB), pages 425-442.

  24. Conrad, C. & Karanasos, M., 2005. "On the inflation-uncertainty hypothesis in the USA, Japan and the UK: a dual long memory approach," Japan and the World Economy, Elsevier, vol. 17(3), pages 327-343, August.

    Cited by:

    1. Zeynel Abidin Ozdemir, 2010. "Dynamics Of Inflation, Output Growth And Their Uncertainty In The Uk: An Empirical Analysis," Manchester School, University of Manchester, vol. 78(6), pages 511-537, December.
    2. Jinquan Liu & Tingguo Zheng & Jianli Sui, 2008. "Dual long memory of inflation and test of the relationship between inflation and inflation uncertainty," Psychometrika, Springer;The Psychometric Society, vol. 3(2), pages 240-254, June.
    3. Carmen Broto & Esther Ruiz, 2008. "Testing for conditional heteroscedasticity in the components of inflation," Working Papers 0812, Banco de España.
    4. Bhar, Ramprasad & Mallik, Girijasankar, 2010. "Inflation, inflation uncertainty and output growth in the USA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(23), pages 5503-5510.
    5. James Payne, 2009. "Inflation targeting and the inflation-inflation uncertainty relationship: evidence from Thailand," Applied Economics Letters, Taylor & Francis Journals, vol. 16(3), pages 233-238.
    6. Ilhan Kilic & Faruk Balli, 2024. "Measuring economic country-specific uncertainty in Türkiye," Empirical Economics, Springer, vol. 67(4), pages 1649-1689, October.
    7. Kyriakos C. Neanidis & Christos S. Savva, 2010. "Macroeconomic Uncertainty, Inflation and Growth: Regime-Dependent Effects in the G7," Centre for Growth and Business Cycle Research Discussion Paper Series 145, Economics, The University of Manchester.
    8. Muhammad Khan & Nikolay Nenovsky, 2017. "Monetary Regimes and External Shocks Reaction: Empirical Investigations on Eastern European Economies," Romanian Economic Journal, Department of International Business and Economics from the Academy of Economic Studies Bucharest, vol. 20(66), pages 63-81, December.
    9. Fernandes, Cecilia Melo, 2021. "ECB communication as a stabilization and coordination device: evidence from ex-ante inflation uncertainty," Working Paper Series 2582, European Central Bank.
    10. Nora Abu Asab & Juan Carlos Cuestas & Alberto Montagnoli, 2015. "Inflation targeting or Exchange Rate Targeting: Which Framework Supports The Goal of Price Stability in Emerging Market Economics?," Working Papers 2015025, The University of Sheffield, Department of Economics.
    11. Shah, Said Zamin & Baharumshah, Ahmad Zubaidi & Hook, Law Siong & Habibullah, Muzafar Shah, 2017. "Nominal uncertainty, real uncertainty and macroeconomic performance in a time-varying asymmetric framework: Implications for monetary policy," Research in International Business and Finance, Elsevier, vol. 42(C), pages 75-93.
    12. Hartmann, Matthias & Conrad, Christian, 2014. "Cross sectional evidence on the relation between monetary policy, macroeconomic conditions and low-frequency inflation uncertainty," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100477, Verein für Socialpolitik / German Economic Association.
    13. Mesbah Fathy Sharaf, 2015. "Inflation and Inflation Uncertainty Revisited: Evidence from Egypt," Economies, MDPI, vol. 3(3), pages 1-19, July.
    14. Hanabusa, Kunihiro, 2012. "The effect of 107th OPEC Ordinary Meeting on oil prices and economic performances in Japan," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(3), pages 1666-1672.
    15. Nasr, Adnen Ben & Balcilar, Mehmet & Ajmi, Ahdi N. & Aye, Goodness C. & Gupta, Rangan & van Eyden, Reneé, 2015. "Causality between inflation and inflation uncertainty in South Africa: Evidence from a Markov-switching vector autoregressive model," Emerging Markets Review, Elsevier, vol. 24(C), pages 46-68.
    16. Fountas, Stilianos & Karanasos, Menelaos, 2007. "Inflation, output growth, and nominal and real uncertainty: Empirical evidence for the G7," Journal of International Money and Finance, Elsevier, vol. 26(2), pages 229-250, March.
    17. Mehdi Hajamini, 2019. "Asymmetric Causality Between Inflation and Uncertainty: Evidences from 33 Developed and Developing Countries," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 17(2), pages 287-309, June.
    18. Algieri, Bernardina, 2014. "The influence of biofuels, economic and financial factors on daily returns of commodity futures prices," Discussion Papers 164963, University of Bonn, Center for Development Research (ZEF).
    19. Diego Ferreira & Andreza Aparecida Palma, 2018. "Inflation And Inflation Uncertainty In Latin America: A Time-Varying Stochastic Volatility In Mean Approach," Anais do XLIV Encontro Nacional de Economia [Proceedings of the 44th Brazilian Economics Meeting] 125, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    20. Dejan Živkov & Jovan Njegic & Marko Pecanac, 2014. "Bidirectional linkage between inflation and inflation uncertainty – the case of Eastern European countries," Baltic Journal of Economics, Baltic International Centre for Economic Policy Studies, vol. 14(1-2), pages 124-139, December.
    21. Narayan, Paresh Kumar & Narayan, Seema & Smyth, Russell, 2009. "Understanding the inflation-output nexus for China," China Economic Review, Elsevier, vol. 20(1), pages 82-90, March.
    22. Erdem Havvanur Feyza & Yamak Rahmi, 2014. "The relationship between inflation and inflation uncertainty in Turkey," Экономика региона, CyberLeninka;Федеральное государственное бюджетное учреждение науки «Институт экономики Уральского отделения Российской академии наук», issue 4, pages 246-254.
    23. Abdullah Sultan Al Shammre & Benaissa Chidmi, 2023. "Oil Price Forecasting Using FRED Data: A Comparison between Some Alternative Models," Energies, MDPI, vol. 16(11), pages 1-24, May.
    24. Falahi , Mohammad Ali & Hajamini , Mehdi, 2015. "Relationship between Inflation and Inflation Uncertainty in Iran: An Application of SETAR-GARCH Model," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 10(2), pages 69-91, January.
    25. Barnett William A. & Jawadi Fredj & Ftiti Zied, 2020. "Causal relationships between inflation and inflation uncertainty," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(5), pages 1-26, December.
    26. Hassan Heidari & Salih Turan Katircioglu & Sahar Bashiri, 2013. "Inflation, inflation uncertainty and growth in the Iranian economy: an application of BGARCH-M model with BEKK approach," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 14(5), pages 819-832, November.
    27. Mehmet Balcilar & Zeynel Abidin Ozdemir, 2013. "Asymmetric and Time-Varying Causality between Inflation and Inflation Uncertainty in G-7 Countries," Scottish Journal of Political Economy, Scottish Economic Society, vol. 60(1), pages 1-42, February.
    28. Conrad, Christian, 2010. "Non-negativity conditions for the hyperbolic GARCH model," Journal of Econometrics, Elsevier, vol. 157(2), pages 441-457, August.
    29. Buth, Bora & Kakinaka, Makoto & Miyamoto, Hiroaki, 2015. "Inflation and inflation uncertainty: The case of Cambodia, Lao PDR, and Vietnam," Journal of Asian Economics, Elsevier, vol. 38(C), pages 31-43.
    30. Conrad, Christian & Hartmann, Matthias, 2019. "On the determinants of long-run inflation uncertainty: Evidence from a panel of 17 developed economies," European Journal of Political Economy, Elsevier, vol. 56(C), pages 233-250.
    31. Vasilios Plakandaras & Rangan Gupta & Periklis Gogas & Theophilos Papadimitriou, 2017. "Macroeconomic Uncertainty, Growth and Inflation in the Eurozone: A Causal Approach," Working Papers 201737, University of Pretoria, Department of Economics.
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