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Giampiero M. Gallo

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. Fabrizio Cipollini & Giampiero M. Gallo, 2021. "Multiplicative Error Models: 20 years on," Papers 2107.05923, arXiv.org.

    Cited by:

    1. Abdelhakim Aknouche & Stefanos Dimitrakopoulos, 2023. "Autoregressive conditional proportion: A multiplicative‐error model for (0,1)‐valued time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(4), pages 393-417, July.
    2. 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.
    3. Aknouche, Abdelhakim & Dimitrakopoulos, Stefanos, 2021. "Autoregressive conditional proportion: A multiplicative-error model for (0,1)-valued time series," MPRA Paper 110954, University Library of Munich, Germany, revised 06 Dec 2021.

  2. Alessandra Amendola & Vincenzo Candila & Fabrizio Cipollini & Giampiero M. Gallo, 2020. "Doubly Multiplicative Error Models with Long- and Short-run Components," Papers 2006.03458, arXiv.org.

    Cited by:

    1. Christian Conrad & Robert F. Engle, 2021. "Modelling Volatility Cycles: The (MF)2 GARCH Model," Working Paper series 21-05, Rimini Centre for Economic Analysis.

  3. G.M. Gallo & D. Lacava & E. Otranto, 2020. "Measuring the Effects of Unconventional Policies on Stock Market Volatility," Working Paper CRENoS 202006, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.

    Cited by:

    1. G.M. Gallo & D. Lacava & E. Otranto, 2020. "On Classifying the Effects of Policy Announcements on Volatility," Working Paper CRENoS 202008, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    2. Demetrio Lacava & Luca Scaffidi Domianello, 2021. "The Incidence of Spillover Effects during the Unconventional Monetary Policies Era," JRFM, MDPI, vol. 14(6), pages 1-18, May.

  4. Giampiero M. Gallo & Demetrio Lacava & Edoardo Otranto, 2020. "On Classifying the Effects of Policy Announcements on Volatility," Papers 2011.14094, arXiv.org, revised Feb 2021.

    Cited by:

    1. Giampiero M. Gallo & Demetrio Lacava & Edoardo Otranto, 2023. "Volatility jumps and the classification of monetary policy announcements," Papers 2305.12192, arXiv.org.
    2. Raffaele Mattera & Philipp Otto, 2023. "Network log-ARCH models for forecasting stock market volatility," Papers 2303.11064, arXiv.org.

  5. Demetrio Lacava & Giampiero M. Gallo & Edoardo Otranto, 2020. "Unconventional Policies Effects on Stock Market Volatility: A MAP Approach," Papers 2010.08259, arXiv.org, revised Mar 2021.

    Cited by:

    1. G.M. Gallo & D. Lacava & E. Otranto, 2020. "On Classifying the Effects of Policy Announcements on Volatility," Working Paper CRENoS 202008, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.

  6. 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.

    Cited by:

    1. Alessandra Amendola & Vincenzo Candila & Fabrizio Cipollini & Giampiero M. Gallo, 2020. "Doubly Multiplicative Error Models with Long- and Short-run Components," Papers 2006.03458, arXiv.org.
    2. Beatrice Foroni & Luca Merlo & Lea Petrella, 2023. "Quantile and expectile copula-based hidden Markov regression models for the analysis of the cryptocurrency market," Papers 2307.06400, arXiv.org.

  7. Fabrizio Cipollini & Giampiero M. Gallo & Alessandro Palandri, 2019. "Realized variance modeling: decoupling forecasting from estimation," Econometrics Working Papers Archive 2019_05, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".

    Cited by:

    1. Giampiero M. Gallo & Demetrio Lacava & Edoardo Otranto, 2023. "Volatility jumps and the classification of monetary policy announcements," Papers 2305.12192, arXiv.org.
    2. Chao Zhang & Xingyue Pu & Mihai Cucuringu & Xiaowen Dong, 2023. "Graph Neural Networks for Forecasting Multivariate Realized Volatility with Spillover Effects," Papers 2308.01419, arXiv.org.
    3. Fiammetta Menchetti & Fabrizio Cipollini & Fabrizia Mealli, 2021. "Causal effect of regulated Bitcoin futures on volatility and volume," Papers 2109.15052, arXiv.org.

  8. Fabrizio Cipollini & Giampiero M. Gallo & Edoardo Otranto, 2019. "Realized Volatility Forecasting: Robustness to Measurement Errors," Econometrics Working Papers Archive 2019_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".

    Cited by:

    1. Hwang, Eunju & Hong, Won-Tak, 2021. "A multivariate HAR-RV model with heteroscedastic errors and its WLS estimation," Economics Letters, Elsevier, vol. 203(C).
    2. A Clements & D Preve, 2019. "A Practical Guide to Harnessing the HAR Volatility Model," NCER Working Paper Series 120, National Centre for Econometric Research.
    3. Giampiero M. Gallo & Demetrio Lacava & Edoardo Otranto, 2023. "Volatility jumps and the classification of monetary policy announcements," Papers 2305.12192, arXiv.org.
    4. Vincenzo Candila & Oguzhan Cepni & Giampiero M. Gallo & Rangan Gupta, 2024. "Influence of Local and Global Economic Policy Uncertainty on the Volatility of US State-Level Equity Returns: Evidence from a GARCH-MIDAS Approach with Shrinkage and Cluster Analysis," Working Papers 202437, University of Pretoria, Department of Economics.
    5. Demetrio Lacava & Giampiero M. Gallo & Edoardo Otranto, 2022. "Unconventional policies effects on stock market volatility: The MAP approach," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(5), pages 1245-1265, November.
    6. Fabrizio Cipollini & Giampiero M. Gallo, 2021. "Multiplicative Error Models: 20 years on," Papers 2107.05923, arXiv.org.
    7. Francesco Audrino & Jonathan Chassot, 2024. "HARd to Beat: The Overlooked Impact of Rolling Windows in the Era of Machine Learning," Papers 2406.08041, arXiv.org.
    8. Yaojie Zhang & Mengxi He & Danyan Wen & Yudong Wang, 2022. "Forecasting Bitcoin volatility: A new insight from the threshold regression model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 633-652, April.
    9. Li, Dan & Drovandi, Christopher & Clements, Adam, 2024. "Outlier-robust methods for forecasting realized covariance matrices," International Journal of Forecasting, Elsevier, vol. 40(1), pages 392-408.
    10. Yaojie Zhang & Mengxi He & Yuqi Zhao & Xianfeng Hao, 2023. "Predicting stock realized variance based on an asymmetric robust regression approach," Bulletin of Economic Research, Wiley Blackwell, vol. 75(4), pages 1022-1047, October.
    11. Alessandra Amendola & Vincenzo Candila & Fabrizio Cipollini & Giampiero M. Gallo, 2020. "Doubly Multiplicative Error Models with Long- and Short-run Components," Papers 2006.03458, arXiv.org.
    12. 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.
    13. Papantonis, Ioannis & Rompolis, Leonidas & Tzavalis, Elias, 2023. "Improving variance forecasts: The role of Realized Variance features," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1221-1237.
    14. Naimoli, Antonio & Gerlach, Richard & Storti, Giuseppe, 2022. "Improving the accuracy of tail risk forecasting models by combining several realized volatility estimators," Economic Modelling, Elsevier, vol. 107(C).
    15. Jianqing Fan & Donggyu Kim & Minseok Shin & Yazhen Wang, 2024. "Factor and Idiosyncratic VAR-Ito Volatility Models for Heavy-Tailed High-Frequency Financial Data," Working Papers 202415, University of California at Riverside, Department of Economics.
    16. Bauwens, Luc & Otranto, Edoardo, 2023. "Realized Covariance Models with Time-varying Parameters and Spillover Effects," LIDAM Discussion Papers CORE 2023019, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    17. Danyan Wen & Mengxi He & Yaojie Zhang & Yudong Wang, 2022. "Forecasting realized volatility of Chinese stock market: A simple but efficient truncated approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 230-251, March.
    18. Hwang, Eunju & Jeon, ChanHyeok, 2024. "Nonnegative GARCH-type models with conditional Gamma distributions and their applications," Computational Statistics & Data Analysis, Elsevier, vol. 198(C).

  9. Fabrizio Cipollini & Giampiero M. Gallo, 2018. "Modeling Euro STOXX 50 Volatility with Common and Market–specific Components," Working Paper series 18-26, Rimini Centre for Economic Analysis.

    Cited by:

    1. Claudio Morana, 2021. "A new macro-financial condition index for the euro area," Working Papers 467, University of Milano-Bicocca, Department of Economics, revised Sep 2021.
    2. Fabrizio Cipollini & Giampiero M. Gallo, 2021. "Multiplicative Error Models: 20 years on," Papers 2107.05923, arXiv.org.
    3. 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.
    4. Voges, Michelle & Sibbertsen, Philipp, 2021. "Cyclical fractional cointegration," Econometrics and Statistics, Elsevier, vol. 19(C), pages 114-129.

  10. Giampiero M. Gallo & Edoardo Otranto, 2017. "Combining Sharp and Smooth Transitions in Volatility Dynamics: a Fuzzy Regime Approach," Econometrics Working Papers Archive 2017_05, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".

    Cited by:

    1. Bauwens, Luc & Otranto, Edoardo, 2020. "Nonlinearities and regimes in conditional correlations with different dynamics," LIDAM Reprints CORE 3128, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Demetrio Lacava & Luca Scaffidi Domianello, 2021. "The Incidence of Spillover Effects during the Unconventional Monetary Policies Era," JRFM, MDPI, vol. 14(6), pages 1-18, May.
    3. Pietro Coretto & Michele La Rocca & Giuseppe Storti, 2020. "Improving Many Volatility Forecasts Using Cross-Sectional Volatility Clusters," JRFM, MDPI, vol. 13(4), pages 1-23, March.
    4. Fabrizio Cipollini & Giampiero M. Gallo & Edoardo Otranto, 2019. "Realized Volatility Forecasting: Robustness to Measurement Errors," Econometrics Working Papers Archive 2019_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    5. Abdelhakim Aknouche & Bader Almohaimeed & Stefanos Dimitrakopoulos, 2022. "Periodic autoregressive conditional duration," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(1), pages 5-29, January.
    6. 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.
    7. Aknouche, Abdelhakim & Almohaimeed, Bader & Dimitrakopoulos, Stefanos, 2020. "Periodic autoregressive conditional duration," MPRA Paper 101696, University Library of Munich, Germany, revised 08 Jul 2020.

  11. Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2017. "Copula-based vMEM Specifications versus Alternatives: The Case of Trading Activity," Econometrics Working Papers Archive 2017_02, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".

    Cited by:

    1. Carol Alexander & Daniel F. Heck & Andreas Kaeck, 2022. "The Role of Binance in Bitcoin Volatility Transmission," Applied Mathematical Finance, Taylor & Francis Journals, vol. 29(1), pages 1-32, January.
    2. Fabrizio Cipollini & Giampiero M. Gallo, 2021. "Multiplicative Error Models: 20 years on," Papers 2107.05923, arXiv.org.
    3. E. Otranto, 2024. "A Vector Multiplicative Error Model with Spillover Effects and Co-movements," Working Paper CRENoS 202404, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    4. Robert Engle & Michael J. Fleming & Eric Ghysels & Giang Nguyen, 2012. "Liquidity and volatility in the U.S. treasury market," Staff Reports 590, Federal Reserve Bank of New York.
    5. Cattivelli, Luca & Pirino, Davide, 2019. "A SHARP model of bid–ask spread forecasts," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1211-1225.
    6. Cipollini, Fabrizio & Gallo, Giampiero M., 2019. "Modeling Euro STOXX 50 volatility with common and market-specific components," Econometrics and Statistics, Elsevier, vol. 11(C), pages 22-42.

  12. Francesco Calvori & Matteo Dentella & Giampiero M. Gallo, 2016. "Sovereign Debt Spreads within the Euro Area: When Fears Become Excess Fears," Econometrics Working Papers Archive 2016_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".

    Cited by:

    1. Favero Carlo A. & Missale Alessandro, 2016. "Contagion in the EMU – The Role of Eurobonds with OMTs," Review of Law & Economics, De Gruyter, vol. 12(3), pages 555-584, November.

  13. Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2016. "Copula--based Specification of vector MEMs," Papers 1604.01338, arXiv.org.

    Cited by:

    1. Lien, Donald & Lee, Geul & Yang, Li & Zhang, Yuyin, 2018. "Volatility spillovers among the U.S. and Asian stock markets: A comparison between the periods of Asian currency crisis and subprime credit crisis," The North American Journal of Economics and Finance, Elsevier, vol. 46(C), pages 187-201.

  14. Francesco Calvori & Fabrizio Cipollini & Giampiero M. Gallo, 2014. "Go with the Flow: A GAS model for Predicting Intra-daily Volume Shares," Econometrics Working Papers Archive 2014_01, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Feb 2014.

    Cited by:

    1. Vladimir Markov & Olga Vilenskaia & Vlad Rashkovich, 2019. "Quintet Volume Projection," Papers 1904.01412, arXiv.org.

  15. Giampiero M. Gallo & Edoardo Otranto, 2014. "Forecasting Realized Volatility with Changes of Regimes," Econometrics Working Papers Archive 2014_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Feb 2014.

    Cited by:

    1. Alketa Bejko & Belinda Xarba, 2021. "The Evaluation of the Drafting Process of Regional’s Development Strategies in Albania. the Research on Gjirokastra’s Region," European Journal of Interdisciplinary Studies Articles, Revistia Research and Publishing, vol. 1, September.
    2. Syed Abul Basher & Alfred Haug & Perry Sadorsky, 2017. "The impact of oil-market shocks on stock returns in major oil-exporting countries: A Markov-switching approach," Working Papers 1710, University of Otago, Department of Economics, revised Oct 2017.
    3. Basher, Syed Abul & Haug, Alfred A. & Sadorsky, Perry, 2018. "The impact of oil-market shocks on stock returns in major oil-exporting countries," Journal of International Money and Finance, Elsevier, vol. 86(C), pages 264-280.

  16. Matteo Barigozzi & Christian T. Brownlees & Giampiero M. Gallo & David Veredas, 2014. "Disentangling Systematic and Idiosyncratic Dynamics in Panels of Volatility Measures," Econometrics Working Papers Archive 2014_02, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Feb 2014.

    Cited by:

    1. Zhang, Xingmin & Zhang, Shuai & Lu, Liping, 2022. "The banking instability and climate change: Evidence from China," Energy Economics, Elsevier, vol. 106(C).
    2. Matteo Barigozzi & Christian T. Brownlees, 2013. "Nets: Network estimation for time series," Economics Working Papers 1391, Department of Economics and Business, Universitat Pompeu Fabra.
    3. Duc Thi Luu, 2022. "Portfolio Correlations in the Bank-Firm Credit Market of Japan," Computational Economics, Springer;Society for Computational Economics, vol. 60(2), pages 529-569, August.
    4. Alketa Bejko & Belinda Xarba, 2021. "The Evaluation of the Drafting Process of Regional’s Development Strategies in Albania. the Research on Gjirokastra’s Region," European Journal of Interdisciplinary Studies Articles, Revistia Research and Publishing, vol. 1, September.
    5. Pietro Coretto & Michele La Rocca & Giuseppe Storti, 2020. "Improving Many Volatility Forecasts Using Cross-Sectional Volatility Clusters," JRFM, MDPI, vol. 13(4), pages 1-23, March.
    6. Fabrizio Cipollini & Giampiero M. Gallo & Edoardo Otranto, 2019. "Realized Volatility Forecasting: Robustness to Measurement Errors," Econometrics Working Papers Archive 2019_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    7. Barigozzi, Matteo & Hallin, Mark, 2015. "Generalized dynamic factor models and volatilities: recovering the market volatility shocks," LSE Research Online Documents on Economics 60980, London School of Economics and Political Science, LSE Library.
    8. Jozef Barun'ik & Tobias Kley, 2015. "Quantile Coherency: A General Measure for Dependence between Cyclical Economic Variables," Papers 1510.06946, arXiv.org, revised Dec 2018.
    9. Fabrizio Cipollini & Giampiero M. Gallo, 2021. "Multiplicative Error Models: 20 years on," Papers 2107.05923, arXiv.org.
    10. Paul G. Egan & Anthony J. Leddin, 2016. "Examining Monetary Policy Transmission in the People's Republic of China–Structural Change Models with a Monetary Policy Index," Asian Development Review, MIT Press, vol. 33(1), pages 74-110, March.
    11. Barigozzi, Matteo & Hallin, Marc, 2017. "Generalized dynamic factor models and volatilities estimation and forecasting," LSE Research Online Documents on Economics 67455, London School of Economics and Political Science, LSE Library.
    12. Harry-Paul Vander Elst, 2015. "FloGARCH: Realizing Long Memory and Asymmetries in Returns Valitility," Working Papers ECARES ECARES 2015-12, ULB -- Universite Libre de Bruxelles.
    13. Francisco Blasques & Enzo D'Innocenzo & Siem Jan Koopman, 2021. "Common and Idiosyncratic Conditional Volatility Factors: Theory and Empirical Evidence," Tinbergen Institute Discussion Papers 21-057/III, Tinbergen Institute.
    14. Le, Trung Hai & Do, Hung Xuan & Nguyen, Duc Khuong & Sensoy, Ahmet, 2021. "Covid-19 pandemic and tail-dependency networks of financial assets," Finance Research Letters, Elsevier, vol. 38(C).
    15. Bernard Herskovic & Bryan Kelly & Hanno Lustig & Stijn Van Nieuwerburgh, 2020. "Firm Volatility in Granular Networks," Journal of Political Economy, University of Chicago Press, vol. 128(11), pages 4097-4162.
    16. Alessandra Amendola & Vincenzo Candila & Fabrizio Cipollini & Giampiero M. Gallo, 2020. "Doubly Multiplicative Error Models with Long- and Short-run Components," Papers 2006.03458, arXiv.org.
    17. KALNINA, Ilze & TEWOU, Kokouvi, 2015. "Cross-sectional dependence in idiosyncratic volatility," Cahiers de recherche 2015-04, Universite de Montreal, Departement de sciences economiques.
    18. Marko Mlikota, 2022. "Cross-Sectional Dynamics Under Network Structure: Theory and Macroeconomic Applications," Papers 2211.13610, arXiv.org, revised Sep 2024.
    19. Cipollini, Fabrizio & Gallo, Giampiero M., 2019. "Modeling Euro STOXX 50 volatility with common and market-specific components," Econometrics and Statistics, Elsevier, vol. 11(C), pages 22-42.
    20. Philip L. H. Yu & W. K. Li & F. C. Ng, 2017. "The Generalized Conditional Autoregressive Wishart Model for Multivariate Realized Volatility," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(4), pages 513-527, October.
    21. Giampiero M. Gallo & Edoardo Otranto, 2018. "Combining sharp and smooth transitions in volatility dynamics: a fuzzy regime approach," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(3), pages 549-573, April.
    22. Matteo Barigozzi & Marc Hallin, 2015. "Networks, Dynamic Factors, and the Volatility Analysis of High-Dimensional Financial Series," Papers 1510.05118, arXiv.org, revised Jul 2016.
    23. Matteo Barigozzi & Marc Hallin & Stefano Soccorsi, 2017. "Identification of Global and National Shocks in International Financial Markets via General Dynamic Factor Models," Working Papers ECARES ECARES 2017-10, ULB -- Universite Libre de Bruxelles.

  17. Giampiero M. Gallo & Edoardo Otranto, 2012. "Volatility Swings in the US Financial Markets," Econometrics Working Papers Archive 2012_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Jul 2012.

    Cited by:

    1. Giampiero M. Gallo & Edoardo Otranto, 2012. "Realized Volatility and Change of Regimes," Econometrics Working Papers Archive 2012_02, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Jul 2012.
    2. Giampiero M. Gallo & Edoardo Otranto, 2014. "Forecasting Realized Volatility with Changes of Regimes," Econometrics Working Papers Archive 2014_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Feb 2014.

  18. Giampiero M. Gallo & Edoardo Otranto, 2012. "Realized Volatility and Change of Regimes," Econometrics Working Papers Archive 2012_02, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Jul 2012.

    Cited by:

    1. Gao, Jiti & Peng, Bin & Wu, Wei Biao & Yan, Yayi, 2024. "Time-varying multivariate causal processes," Journal of Econometrics, Elsevier, vol. 240(1).
    2. Massimiliano Caporin & Eduardo Rossi & Paolo Santucci de Magistris, 2014. "Chasing volatility - A persistent multiplicative error model with jumps," CREATES Research Papers 2014-29, Department of Economics and Business Economics, Aarhus University.

  19. Christian T. Brownlees & Fabrizio Cipollini & Giampiero M. Gallo, 2011. "Multiplicative Error Models," Econometrics Working Papers Archive 2011_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Apr 2011.

    Cited by:

    1. Javier Mencía & Enrique Sentana, 2018. "Volatility-Related Exchange Traded Assets: An Econometric Investigation," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(4), pages 599-614, October.
    2. Liu, Xiaochun, 2015. "Modeling time-varying skewness via decomposition for out-of-sample forecast," International Journal of Forecasting, Elsevier, vol. 31(2), pages 296-311.
    3. Markus Engler & Vahidin Jeleskovic, 2016. "Intraday volatility, trading volume and trading intensity in the interbank market e-MID," MAGKS Papers on Economics 201648, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    4. Sucarrat, Genaro & Grønneberg, Steffen & Escribano, Alvaro, 2013. "Estimation and Inference in Univariate and Multivariate Log-GARCH-X Models When the Conditional Density is Unknown," MPRA Paper 49344, University Library of Munich, Germany.
    5. Leschinski, Christian, 2016. "On the Memory of Products of Long Range Dependent Time Series," Hannover Economic Papers (HEP) dp-569, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    6. Torben G. Andersen & Oleg Bondarenko & Albert S. Kyle & Anna A. Obizhaeva, 2020. "Intraday Trading Invariance in the E-mini S&P 500 Futures Market," Working Papers w0272, New Economic School (NES).
    7. Francq, Christian & Sucarrat, Genaro, 2013. "An Exponential Chi-Squared QMLE for Log-GARCH Models Via the ARMA Representation," MPRA Paper 51783, University Library of Munich, Germany.
    8. Alketa Bejko & Belinda Xarba, 2021. "The Evaluation of the Drafting Process of Regional’s Development Strategies in Albania. the Research on Gjirokastra’s Region," European Journal of Interdisciplinary Studies Articles, Revistia Research and Publishing, vol. 1, September.
    9. Kim, Jiwon & Mahmassani, Hani S., 2015. "Compound Gamma representation for modeling travel time variability in a traffic network," Transportation Research Part B: Methodological, Elsevier, vol. 80(C), pages 40-63.
    10. Bauwens, L. & Hafner C. & Laurent, S., 2011. "Volatility Models," LIDAM Discussion Papers ISBA 2011044, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
      • BAUWENS, Luc & HAFNER, Christian & LAURENT, Sébastien, 2011. "Volatility models," LIDAM Discussion Papers CORE 2011058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
      • Bauwens, L. & Hafner, C. & Laurent, S., 2012. "Volatility Models," LIDAM Reprints ISBA 2012028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    11. Chen, Fei & Diebold, Francis X. & Schorfheide, Frank, 2013. "A Markov-switching multifractal inter-trade duration model, with application to US equities," Journal of Econometrics, Elsevier, vol. 177(2), pages 320-342.
    12. Sucarrat, Genaro & Escribano, Alvaro, 2013. "Unbiased QML Estimation of Log-GARCH Models in the Presence of Zero Returns," MPRA Paper 50699, University Library of Munich, Germany.
    13. COSMA, Antonio & GALLI, Fausto, 2006. "A nonparametric ACD model," LIDAM Discussion Papers CORE 2006067, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    14. Fabrizio Cipollini & Giampiero M Gallo & Alessandro Palandri, 2020. "Realized Variance Modeling: Decoupling Forecasting from Estimation," Journal of Financial Econometrics, Oxford University Press, vol. 18(3), pages 532-555.
    15. Heejoon Han & Myung D. Park & Shen Zhang, 2015. "A Multiplicative Error Model with Heterogeneous Components for Forecasting Realized Volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(3), pages 209-219, April.
    16. Demetrio Lacava & Giampiero M. Gallo & Edoardo Otranto, 2022. "Unconventional policies effects on stock market volatility: The MAP approach," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(5), pages 1245-1265, November.
    17. E. Otranto, 2012. "Spillover Effects in the Volatility of Financial Markets," Working Paper CRENoS 201217, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    18. 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.
    19. Cipollini, Fabrizio & Gallo, Giampiero M., 2019. "Modeling Euro STOXX 50 volatility with common and market-specific components," Econometrics and Statistics, Elsevier, vol. 11(C), pages 22-42.
    20. Massimiliano Caporin & Eduardo Rossi & Paolo Santucci de Magistris, 2014. "Chasing volatility - A persistent multiplicative error model with jumps," CREATES Research Papers 2014-29, Department of Economics and Business Economics, Aarhus University.
    21. G.M. Gallo & D. Lacava & E. Otranto, 2020. "Measuring the Effects of Unconventional Policies on Stock Market Volatility," Working Paper CRENoS 202006, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    22. Sucarrat, Genaro & Grønneberg, Steffen, 2016. "Models of Financial Return With Time-Varying Zero Probability," MPRA Paper 68931, University Library of Munich, Germany.
    23. Giampiero M. Gallo & Edoardo Otranto, 2012. "Volatility Swings in the US Financial Markets," Econometrics Working Papers Archive 2012_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Jul 2012.
    24. Stanislav Anatolyev, 2013. "Objects of nonstructural time series modeling (in Russian)," Quantile, Quantile, issue 11, pages 1-12, December.

  20. Giovanni De Luca & Giampiero Gallo, 2010. "A Time-varying Mixing Multiplicative Error Model for Realized Volatility," Econometrics Working Papers Archive wp2010_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".

    Cited by:

    1. Christian T. Brownlees & Fabrizio Cipollini & Giampiero M. Gallo, 2011. "Multiplicative Error Models," Econometrics Working Papers Archive 2011_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Apr 2011.

  21. Matteo Barigozzi & Christian T. Brownlees & Giampiero M. Gallo & David Veredas, 2010. "Disentangling Systematic and Idiosyncratic Risk for Large Panels of Assets," Econometrics Working Papers Archive wp2010_06, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".

    Cited by:

    1. Herskovic, Bernard & Kelly, Bryan & Lustig, Hanno & Van Nieuwerburgh, Stijn, 2016. "The common factor in idiosyncratic volatility: Quantitative asset pricing implications," Journal of Financial Economics, Elsevier, vol. 119(2), pages 249-283.
    2. Fady Barsoum, 2013. "The Effects of Monetary Policy Shocks on a Panel of Stock Market Volatilities: A Factor-Augmented Bayesian VAR Approach," Working Paper Series of the Department of Economics, University of Konstanz 2013-15, Department of Economics, University of Konstanz.
    3. Matteo Luciani & David Veredas, 2012. "A model for vast panels of volatilities," Working Papers 1230, Banco de España.
    4. Tim Bollerslev & Viktor Todorov, 2010. "Jump Tails, Extreme Dependencies, and the Distribution of Stock Returns," CREATES Research Papers 2010-64, Department of Economics and Business Economics, Aarhus University.
    5. Bernard Herskovic & Bryan Kelly & Hanno Lustig & Stijn Van Nieuwerburgh, 2020. "Firm Volatility in Granular Networks," Journal of Political Economy, University of Chicago Press, vol. 128(11), pages 4097-4162.

  22. Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2009. "Semiparametric vector MEM," Econometrics Working Papers Archive wp2009_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".

    Cited by:

    1. Fabrizio Cipollini & Giampiero Gallo & Andrea Ugolini, 2016. "Median Response to Shocks: A Model for VaR Spillovers in East Asia," Econometrics Working Papers Archive 2016_01, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    2. Giampiero M. Gallo & Edoardo Otranto, 2012. "Realized Volatility and Change of Regimes," Econometrics Working Papers Archive 2012_02, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Jul 2012.
    3. Geert Dhaene & Piet Sercu & Jianbin Wu, 2022. "Volatility spillovers: A sparse multivariate GARCH approach with an application to commodity markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(5), pages 868-887, May.
    4. Bodnar, Taras & Hautsch, Nikolaus, 2016. "Dynamic conditional correlation multiplicative error processes," Journal of Empirical Finance, Elsevier, vol. 36(C), pages 41-67.
    5. Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2017. "Copula-based vMEM Specifications versus Alternatives: The Case of Trading Activity," Econometrics Working Papers Archive 2017_02, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    6. Giampiero M. Gallo & Demetrio Lacava & Edoardo Otranto, 2023. "Volatility jumps and the classification of monetary policy announcements," Papers 2305.12192, arXiv.org.
    7. Ng, F.C. & Li, W.K. & Yu, Philip L.H., 2016. "Diagnostic checking of the vector multiplicative error model," Computational Statistics & Data Analysis, Elsevier, vol. 94(C), pages 86-97.
    8. Alketa Bejko & Belinda Xarba, 2021. "The Evaluation of the Drafting Process of Regional’s Development Strategies in Albania. the Research on Gjirokastra’s Region," European Journal of Interdisciplinary Studies Articles, Revistia Research and Publishing, vol. 1, September.
    9. Donelli, Nicola & Peluso, Stefano & Mira, Antonietta, 2021. "A Bayesian semiparametric vector Multiplicative Error Model," Computational Statistics & Data Analysis, Elsevier, vol. 161(C).
    10. 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.
    11. Fabrizio Cipollini & Giampiero M. Gallo & Edoardo Otranto, 2019. "Realized Volatility Forecasting: Robustness to Measurement Errors," Econometrics Working Papers Archive 2019_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    12. Christian T. Brownlees & Fabrizio Cipollini & Giampiero M. Gallo, 2011. "Multiplicative Error Models," Econometrics Working Papers Archive 2011_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Apr 2011.
    13. Fabrizio Cipollini & Giampiero M. Gallo & Alessandro Palandri, 2020. "A dynamic conditional approach to portfolio weights forecasting," Papers 2004.12400, arXiv.org.
    14. Fabrizio Cipollini & Giampiero M Gallo & Alessandro Palandri, 2020. "Realized Variance Modeling: Decoupling Forecasting from Estimation," Journal of Financial Econometrics, Oxford University Press, vol. 18(3), pages 532-555.
    15. Xu, Yongdeng, 2022. "The Exponential HEAVY Model: An Improved Approach to Volatility Modeling and Forecasting," Cardiff Economics Working Papers E2022/5, Cardiff University, Cardiff Business School, Economics Section.
    16. Fabrizio Cipollini & Giampiero M. Gallo, 2021. "Multiplicative Error Models: 20 years on," Papers 2107.05923, arXiv.org.
    17. E. Otranto, 2012. "Spillover Effects in the Volatility of Financial Markets," Working Paper CRENoS 201217, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    18. E. Otranto, 2024. "A Vector Multiplicative Error Model with Spillover Effects and Co-movements," Working Paper CRENoS 202404, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    19. Naimoli, Antonio & Storti, Giuseppe, 2019. "Heterogeneous component multiplicative error models for forecasting trading volumes," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1332-1355.
    20. Gallo, Giampiero M. & Otranto, Edoardo, 2015. "Forecasting realized volatility with changing average levels," International Journal of Forecasting, Elsevier, vol. 31(3), pages 620-634.
    21. Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2016. "Copula--based Specification of vector MEMs," Econometrics Working Papers Archive 2016_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    22. Cipollini, Fabrizio & Gallo, Giampiero M., 2010. "Automated variable selection in vector multiplicative error models," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2470-2486, November.
    23. Ke, Rui & Lu, Wanbo & Jia, Jing, 2021. "Evaluating multiplicative error models: A residual-based approach," Computational Statistics & Data Analysis, Elsevier, vol. 153(C).
    24. Abdelhakim Aknouche & Stefanos Dimitrakopoulos, 2023. "Autoregressive conditional proportion: A multiplicative‐error model for (0,1)‐valued time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(4), pages 393-417, July.
    25. Francesco Calvori & Drew Creal & Siem Jan Koopman & Andre Lucas, 2014. "Testing for Parameter Instability in Competing Modeling Frameworks," Tinbergen Institute Discussion Papers 14-010/IV/DSF71, Tinbergen Institute.
    26. Lien, Donald & Lee, Geul & Yang, Li & Zhang, Yuyin, 2018. "Volatility spillovers among the U.S. and Asian stock markets: A comparison between the periods of Asian currency crisis and subprime credit crisis," The North American Journal of Economics and Finance, Elsevier, vol. 46(C), pages 187-201.
    27. Bodnar, Taras & Hautsch, Nikolaus, 2013. "Copula-based dynamic conditional correlation multiplicative error processes," CFS Working Paper Series 2013/19, Center for Financial Studies (CFS).
    28. Cipollini, Fabrizio & Gallo, Giampiero M., 2019. "Modeling Euro STOXX 50 volatility with common and market-specific components," Econometrics and Statistics, Elsevier, vol. 11(C), pages 22-42.
    29. Hira L. Koul & Indeewara Perera & Narayana Balakrishna, 2023. "A class of Minimum Distance Estimators in Markovian Multiplicative Error Models," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 87-115, May.
    30. Giampiero M. Gallo & Edoardo Otranto, 2014. "Forecasting Realized Volatility with Changes of Regimes," Econometrics Working Papers Archive 2014_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Feb 2014.
    31. Giampiero M. Gallo & Edoardo Otranto, 2018. "Combining sharp and smooth transitions in volatility dynamics: a fuzzy regime approach," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(3), pages 549-573, April.
    32. Cipollini, Fabrizio & Gallo, Giampiero M. & Palandri, Alessandro, 2021. "A dynamic conditional approach to forecasting portfolio weights," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1111-1126.
    33. Chiranjit Dutta & Nalini Ravishanker & Sumanta Basu, 2022. "Modeling Multivariate Positive-Valued Time Series Using R-INLA," Papers 2206.05374, arXiv.org, revised Jul 2022.

  23. Fabrizio Cipollini & Giampiero M. Gallo, 2009. "Automated Variable Selection in Vector Multiplicative Error Models," Econometrics Working Papers Archive wp2009_02, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".

    Cited by:

    1. Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2017. "Copula-based vMEM Specifications versus Alternatives: The Case of Trading Activity," Econometrics Working Papers Archive 2017_02, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    2. Zhang, Shulin & Okhrin, Ostap & Zhou, Qian M. & Song, Peter X.-K., 2016. "Goodness-of-fit test for specification of semiparametric copula dependence models," Journal of Econometrics, Elsevier, vol. 193(1), pages 215-233.
    3. 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.
    4. Christian T. Brownlees & Fabrizio Cipollini & Giampiero M. Gallo, 2011. "Multiplicative Error Models," Econometrics Working Papers Archive 2011_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Apr 2011.
    5. Fabrizio Cipollini & Giampiero M. Gallo, 2021. "Multiplicative Error Models: 20 years on," Papers 2107.05923, arXiv.org.
    6. 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.

  24. Christian T. Brownlees & Fabrizio Cipollini & Giampiero M. Gallo, 2009. "Intra-daily Volume Modeling and Prediction for Algorithmic Trading," Econometrics Working Papers Archive wp2009_01, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".

    Cited by:

    1. Brownlees, Christian T. & Gallo, Giampiero M., 2011. "Shrinkage estimation of semiparametric multiplicative error models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 365-378.
    2. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107034723, November.
    3. Christian Conrad & Robert F. Engle, 2021. "Modelling Volatility Cycles: The (MF)2 GARCH Model," Working Paper series 21-05, Rimini Centre for Economic Analysis.
    4. Yufan Chen & Lan Wu & Renyuan Xu & Ruixun Zhang, 2024. "Periodic Trading Activities in Financial Markets: Mean-field Liquidation Game with Major-Minor Players," Papers 2408.09505, arXiv.org.
    5. Demetrio Lacava & Luca Scaffidi Domianello, 2021. "The Incidence of Spillover Effects during the Unconventional Monetary Policies Era," JRFM, MDPI, vol. 14(6), pages 1-18, May.
    6. Torben G. Andersen & Oleg Bondarenko & Albert S. Kyle & Anna A. Obizhaeva, 2020. "Intraday Trading Invariance in the E-mini S&P 500 Futures Market," Working Papers w0272, New Economic School (NES).
    7. Bodnar, Taras & Hautsch, Nikolaus, 2016. "Dynamic conditional correlation multiplicative error processes," Journal of Empirical Finance, Elsevier, vol. 36(C), pages 41-67.
    8. Ferriani, Fabrizio, 2010. "Informed and uninformed traders at work: evidence from the French market," MPRA Paper 24487, University Library of Munich, Germany.
    9. 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.
    10. Malec, Peter & Schienle, Melanie, 2012. "Nonparametric Kernel density estimation near the boundary," SFB 649 Discussion Papers 2012-047, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    11. Ito, R., 2016. "Spline-DCS for Forecasting Trade Volume in High-Frequency Finance," Cambridge Working Papers in Economics 1606, Faculty of Economics, University of Cambridge.
    12. Christian T. Brownlees & Fabrizio Cipollini & Giampiero M. Gallo, 2011. "Multiplicative Error Models," Econometrics Working Papers Archive 2011_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Apr 2011.
    13. Demetrio Lacava & Giampiero M. Gallo & Edoardo Otranto, 2022. "Unconventional policies effects on stock market volatility: The MAP approach," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(5), pages 1245-1265, November.
    14. Francesco Calvori & Fabrizio Cipollini & Giampiero M. Gallo, 2014. "Go with the Flow: A GAS model for Predicting Intra-daily Volume Shares," Econometrics Working Papers Archive 2014_01, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Feb 2014.
    15. Fabrizio Cipollini & Giampiero M. Gallo, 2021. "Multiplicative Error Models: 20 years on," Papers 2107.05923, arXiv.org.
    16. E. Otranto, 2012. "Spillover Effects in the Volatility of Financial Markets," Working Paper CRENoS 201217, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    17. Brownlees Christian T. & Vannucci Marina, 2013. "A Bayesian approach for capturing daily heterogeneity in intra-daily durations time series," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(1), pages 21-46, February.
    18. Härdle, Wolfgang Karl & Hautsch, Nikolaus & Mihoci, Andrija, 2012. "Modelling and forecasting liquidity supply using semiparametric factor dynamics," Journal of Empirical Finance, Elsevier, vol. 19(4), pages 610-625.
    19. Naimoli, Antonio & Storti, Giuseppe, 2019. "Heterogeneous component multiplicative error models for forecasting trading volumes," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1332-1355.
    20. Szűcs, Balázs Árpád, 2017. "Forecasting intraday volume: Comparison of two early models," Finance Research Letters, Elsevier, vol. 21(C), pages 249-258.
    21. Nikolaus Hautsch & Peter Malec & Melanie Schienle, 2014. "Capturing the Zero: A New Class of Zero-Augmented Distributions and Multiplicative Error Processes," Journal of Financial Econometrics, Oxford University Press, vol. 12(1), pages 89-121.
    22. Ye, Xunyu & Gao, Ping & Li, Handong, 2015. "Improving estimation of the fractionally differencing parameter in the SARFIMA model using tapered periodogram," Economic Modelling, Elsevier, vol. 46(C), pages 167-179.
    23. Vladimir Markov & Olga Vilenskaia & Vlad Rashkovich, 2019. "Quintet Volume Projection," Papers 1904.01412, arXiv.org.
    24. Alessandra Amendola & Vincenzo Candila & Fabrizio Cipollini & Giampiero M. Gallo, 2020. "Doubly Multiplicative Error Models with Long- and Short-run Components," Papers 2006.03458, arXiv.org.
    25. Shaojun Ma & Pengcheng Li, 2021. "Predicting Daily Trading Volume via Various Hidden States," Papers 2107.07678, arXiv.org.
    26. Bodnar, Taras & Hautsch, Nikolaus, 2013. "Copula-based dynamic conditional correlation multiplicative error processes," CFS Working Paper Series 2013/19, Center for Financial Studies (CFS).
    27. Cattivelli, Luca & Pirino, Davide, 2019. "A SHARP model of bid–ask spread forecasts," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1211-1225.
    28. Ito, Ryoko, 2013. "Modeling Dynamic Diurnal Patterns in High-Frequency Financial Data," Cambridge Working Papers in Economics 1315, Faculty of Economics, University of Cambridge.
    29. Roman Huptas, 2019. "Point forecasting of intraday volume using Bayesian autoregressive conditional volume models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(4), pages 293-310, July.
    30. Dutt, Tanuj & Humphery-Jenner, Mark, 2013. "Stock return volatility, operating performance and stock returns: International evidence on drivers of the ‘low volatility’ anomaly," Journal of Banking & Finance, Elsevier, vol. 37(3), pages 999-1017.
    31. Lei Li & Zhiyuan Zhang & Ruihan Bao & Keiko Harimoto & Xu Sun, 2022. "Distributional Correlation--Aware Knowledge Distillation for Stock Trading Volume Prediction," Papers 2208.07232, arXiv.org.
    32. G.M. Gallo & D. Lacava & E. Otranto, 2020. "Measuring the Effects of Unconventional Policies on Stock Market Volatility," Working Paper CRENoS 202006, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    33. Wolfgang K. Härdle & Nikolaus Hautsch & Andrija Mihoci, 2015. "Local Adaptive Multiplicative Error Models for High‐Frequency Forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(4), pages 529-550, June.
    34. Giampiero M. Gallo & Edoardo Otranto, 2018. "Combining sharp and smooth transitions in volatility dynamics: a fuzzy regime approach," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(3), pages 549-573, April.
    35. Clements, Adam & Hurn, Stan & Volkov, Vladimir, 2021. "A simple linear alternative to multiplicative error models with an application to trading volume," Working Papers 2021-06, University of Tasmania, Tasmanian School of Business and Economics.
    36. Xiaojie Xu & Yun Zhang, 2023. "Neural network predictions of the high-frequency CSI300 first distant futures trading volume," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 37(2), pages 191-207, June.
    37. Perera, Indeewara & Koul, Hira L., 2017. "Fitting a two phase threshold multiplicative error model," Journal of Econometrics, Elsevier, vol. 197(2), pages 348-367.
    38. Xiaojie Xu & Yun Zhang, 2022. "Forecasting the total market value of a shares traded in the Shenzhen stock exchange via the neural network," Economics Bulletin, AccessEcon, vol. 42(3), pages 1266-1279.

  25. Robert F. Engle & Giampiero M. Gallo & Margherita Velucchi, 2008. "A MEM-based Analysis of Volatility Spillovers in East Asian Financial Markets," Econometrics Working Papers Archive wp2008_09, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".

    Cited by:

    1. Balli, Faruk & Balli, Hatice O. & Jean Louis, Rosmy & Vo, Tuan Kiet, 2015. "The transmission of market shocks and bilateral linkages: Evidence from emerging economies," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 349-357.
    2. Vít Bubák & Evžen Kocenda & Filip Zikes, 2010. "Volatility Transmission in Emerging European Foreign Exchange Markets," CESifo Working Paper Series 3063, CESifo.
    3. John Beirne & Guglielmo Maria Caporale & Marianne Schulze-Ghattas & Nicola Spagnolo, 2009. "Global and Regional Spillovers in Emerging Stock Markets: A Multivariate GARCH-in-Mean Analysis," Discussion Papers of DIW Berlin 942, DIW Berlin, German Institute for Economic Research.
    4. Serda Selin Öztürk & Engin Volkan, 2015. "Intraindustry Volatility Spillovers in the MENA Region," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 51(6), pages 1163-1174, November.
    5. Mr. Phurichai Rungcharoenkitkul, 2011. "Risk Sharing and Financial Contagion in Asia: An Asset Price Perspective," IMF Working Papers 2011/242, International Monetary Fund.
    6. Andreou, Elena & Matsi, Maria & Savvides, Andreas, 2013. "Stock and foreign exchange market linkages in emerging economies," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 27(C), pages 248-268.

  26. Christian T. Brownlees & Giampiero M. Gallo, 2007. "Comparison of Volatility Measures: a Risk Management Perspective," Econometrics Working Papers Archive wp2007_15, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".

    Cited by:

    1. Henning Fischer & Ángela Blanco‐FERNÁndez & Peter Winker, 2016. "Predicting Stock Return Volatility: Can We Benefit from Regression Models for Return Intervals?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(2), pages 113-146, March.
    2. Brownlees, Christian T. & Gallo, Giampiero M., 2011. "Shrinkage estimation of semiparametric multiplicative error models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 365-378.
    3. Fabrizio Cipollini & Giampiero Gallo & Andrea Ugolini, 2016. "Median Response to Shocks: A Model for VaR Spillovers in East Asia," Econometrics Working Papers Archive 2016_01, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    4. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107034723, November.
    5. Louzis, Dimitrios P. & Xanthopoulos-Sisinis, Spyros & Refenes, Apostolos P., 2011. "Are realized volatility models good candidates for alternative Value at Risk prediction strategies?," MPRA Paper 30364, University Library of Munich, Germany.
    6. Matteo Barigozzi & Christian T. Brownlees & Giampiero M. Gallo & David Veredas, 2010. "Disentangling Systematic and Idiosyncratic Risk for Large Panels of Assets," Econometrics Working Papers Archive wp2010_06, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    7. Silvennoinen, Annastiina & Teräsvirta, Timo, 2024. "Consistency and asymptotic normality of maximum likelihood estimators of a multiplicative time-varying smooth transition correlation GARCH model," Econometrics and Statistics, Elsevier, vol. 32(C), pages 57-72.
    8. Meng, Xiaochun & Taylor, James W., 2018. "An approximate long-memory range-based approach for value at risk estimation," International Journal of Forecasting, Elsevier, vol. 34(3), pages 377-388.
    9. Giampiero M. Gallo & Edoardo Otranto, 2012. "Realized Volatility and Change of Regimes," Econometrics Working Papers Archive 2012_02, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Jul 2012.
    10. Cristina Amado & Timo Teräsvirta, 2011. "Modelling Volatility by Variance Decomposition," NIPE Working Papers 01/2011, NIPE - Universidade do Minho.
    11. Großmaß Lidan, 2014. "Liquidity and the Value at Risk," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 234(5), pages 572-602, October.
    12. Matteo Barigozzi & Christian T. Brownlees, 2013. "Nets: Network estimation for time series," Economics Working Papers 1391, Department of Economics and Business, Universitat Pompeu Fabra.
    13. Taylor, James W., 2020. "Forecast combinations for value at risk and expected shortfall," International Journal of Forecasting, Elsevier, vol. 36(2), pages 428-441.
    14. Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2017. "Copula-based vMEM Specifications versus Alternatives: The Case of Trading Activity," Econometrics Working Papers Archive 2017_02, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    15. Wei Yang & Ai Han & Yongmiao Hong & Shouyang Wang, 2016. "Analysis of crisis impact on crude oil prices: a new approach with interval time series modelling," Quantitative Finance, Taylor & Francis Journals, vol. 16(12), pages 1917-1928, December.
    16. Barigozzi, Matteo & Hallin, Marc & Soccorsi, Stefano & von Sachs, Rainer, 2021. "Time-varying general dynamic factor models and the measurement of financial connectedness," Journal of Econometrics, Elsevier, vol. 222(1), pages 324-343.
    17. Alketa Bejko & Belinda Xarba, 2021. "The Evaluation of the Drafting Process of Regional’s Development Strategies in Albania. the Research on Gjirokastra’s Region," European Journal of Interdisciplinary Studies Articles, Revistia Research and Publishing, vol. 1, September.
    18. Filip Žikeš & Jozef Baruník, 2016. "Semi-parametric Conditional Quantile Models for Financial Returns and Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 14(1), pages 185-226.
    19. Louzis, Dimitrios P. & Xanthopoulos-Sisinis, Spyros & Refenes, Apostolos P., 2011. "The role of high frequency intra-daily data, daily range and implied volatility in multi-period Value-at-Risk forecasting," MPRA Paper 35252, University Library of Munich, Germany.
    20. Fabrizio Cipollini & Giampiero M. Gallo & Edoardo Otranto, 2019. "Realized Volatility Forecasting: Robustness to Measurement Errors," Econometrics Working Papers Archive 2019_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    21. Wu, Chih-Chiang & Chiu, Junmao, 2017. "Economic evaluation of asymmetric and price range information in gold and general financial markets," Journal of International Money and Finance, Elsevier, vol. 74(C), pages 53-68.
    22. Bonato, Matteo & Caporin, Massimiliano & Ranaldo, Angelo, 2012. "Forecasting Realized (Co)Variances with a Bloc Structure Wishart Autoregressive Model," Working Papers on Finance 1211, University of St. Gallen, School of Finance.
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    27. Cristina Amado & Annastiina Silvennoinen & Timo Teräsvirta, 2018. "Models with Multiplicative Decomposition of Conditional Variances and Correlations," CREATES Research Papers 2018-14, Department of Economics and Business Economics, Aarhus University.
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    34. Neil Shephard & Kevin Sheppard, 2009. "Realising the future: forecasting with high frequency based volatility (HEAVY) models," Economics Papers 2009-W03, Economics Group, Nuffield College, University of Oxford.
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    54. F. Lilla, 2016. "High Frequency vs. Daily Resolution: the Economic Value of Forecasting Volatility Models," Working Papers wp1084, Dipartimento Scienze Economiche, Universita' di Bologna.
    55. Matteo Barigozzi & Christian T. Brownlees & Giampiero M. Gallo & David Veredas, 2014. "Disentangling Systematic and Idiosyncratic Dynamics in Panels of Volatility Measures," Econometrics Working Papers Archive 2014_02, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Feb 2014.
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    58. Andrada-Félix, Julián & Fernández-Rodríguez, Fernando & Fuertes, Ana-Maria, 2016. "Combining nearest neighbor predictions and model-based predictions of realized variance: Does it pay?," International Journal of Forecasting, Elsevier, vol. 32(3), pages 695-715.
    59. Cristina Amado & Timo Teräsvirta, 2017. "Specification and testing of multiplicative time-varying GARCH models with applications," Econometric Reviews, Taylor & Francis Journals, vol. 36(4), pages 421-446, April.
    60. Bertrand B. Maillet & Jean-Philippe R. M�decin, 2010. "Extreme Volatilities, Financial Crises and L-moment Estimations of Tail-indexes," Working Papers 2010_10, Department of Economics, University of Venice "Ca' Foscari".
    61. Cipollini, Fabrizio & Gallo, Giampiero M., 2019. "Modeling Euro STOXX 50 volatility with common and market-specific components," Econometrics and Statistics, Elsevier, vol. 11(C), pages 22-42.
    62. Shephard, Neil & Xiu, Dacheng, 2017. "Econometric analysis of multivariate realised QML: Estimation of the covariation of equity prices under asynchronous trading," Journal of Econometrics, Elsevier, vol. 201(1), pages 19-42.
    63. Dierkes, Maik & Hollstein, Fabian & Prokopczuk, Marcel & Würsig, Christoph Matthias, 2024. "Measuring tail risk," Journal of Econometrics, Elsevier, vol. 241(2).
    64. Xu Cheng & Eric Renault & Paul Sangrey, 2024. "Identifying the Volatility Risk Price Through the Leverage Effect," PIER Working Paper Archive 24-013, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    65. Ana-Maria Fuertes & Elena Kalotychou & Natasa Todorovic, 2015. "Daily volume, intraday and overnight returns for volatility prediction: profitability or accuracy?," Review of Quantitative Finance and Accounting, Springer, vol. 45(2), pages 251-278, August.
    66. 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.
    67. Liu, Bin & Xiao, Wen & Zhu, Xingting, 2023. "How does inter-industry spillover improve the performance of volatility forecasting?," The North American Journal of Economics and Finance, Elsevier, vol. 65(C).
    68. Nieto, Maria Rosa & Ruiz, Esther, 2016. "Frontiers in VaR forecasting and backtesting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 475-501.
    69. Ana-Maria Fuertes & Jose Olmo, 2016. "On Setting Day-Ahead Equity Trading Risk Limits: VaR Prediction at Market Close or Open?," JRFM, MDPI, vol. 9(3), pages 1-20, September.
    70. Jian Kang & Johan Stax Jakobsen & Annastiina Silvennoinen & Timo Teräsvirta & Glen Wade, 2022. "A parsimonious test of constancy of a positive definite correlation matrix in a multivariate time-varying GARCH model," CREATES Research Papers 2022-01, Department of Economics and Business Economics, Aarhus University.
    71. Giampiero M. Gallo & Edoardo Otranto, 2014. "Forecasting Realized Volatility with Changes of Regimes," Econometrics Working Papers Archive 2014_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Feb 2014.
    72. Francisco Blasques & Vladimir Holy & Petra Tomanova, 2019. "Zero-Inflated Autoregressive Conditional Duration Model for Discrete Trade Durations with Excessive Zeros," Tinbergen Institute Discussion Papers 19-004/III, Tinbergen Institute.
    73. Giampiero M. Gallo & Edoardo Otranto, 2018. "Combining sharp and smooth transitions in volatility dynamics: a fuzzy regime approach," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(3), pages 549-573, April.
    74. 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.
    75. Peter Reinhard Hansen & Zhuo (Albert) Huang & Howard Howan Shek, "undated". "Realized GARCH: A Complete Model of Returns and Realized Measures of Volatility," CREATES Research Papers 2010-13, Department of Economics and Business Economics, Aarhus University.
    76. Huang, MeiChi & Wu, Chih-Chiang & Liu, Shih-Min & Wu, Chang-Che, 2016. "Facts or fates of investors' losses during crises? Evidence from REIT-stock volatility and tail dependence structures," International Review of Economics & Finance, Elsevier, vol. 42(C), pages 54-71.
    77. Christian T. Brownlees & Giampiero Gallo, 2007. "Volatility Forecasting Using Explanatory Variables and Focused Selection Criteria," Econometrics Working Papers Archive wp2007_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    78. 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.
    79. F. Lilla, 2017. "High Frequency vs. Daily Resolution: the Economic Value of Forecasting Volatility Models - 2nd ed," Working Papers wp1099, Dipartimento Scienze Economiche, Universita' di Bologna.
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    81. Chen, Wei-Peng & Choudhry, Taufiq & Wu, Chih-Chiang, 2013. "The extreme value in crude oil and US dollar markets," Journal of International Money and Finance, Elsevier, vol. 36(C), pages 191-210.
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    83. Ewald, Christian & Hadina, Jelena & Haugom, Erik & Lien, Gudbrand & Størdal, Ståle & Yahya, Muhammad, 2023. "Sample frequency robustness and accuracy in forecasting Value-at-Risk for Brent Crude Oil futures," Finance Research Letters, Elsevier, vol. 58(PA).
    84. Zeng, Qing & Tang, Yusui & Yang, Hua & Zhang, Xi, 2024. "Stock market volatility and economic policy uncertainty: New insight into a dynamic threshold mixed-frequency model," Finance Research Letters, Elsevier, vol. 59(C).
    85. Hua, Jian & Manzan, Sebastiano, 2013. "Forecasting the return distribution using high-frequency volatility measures," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4381-4403.
    86. Wu, Chih-Chiang & Liang, Shin-Shun, 2011. "The economic value of range-based covariance between stock and bond returns with dynamic copulas," Journal of Empirical Finance, Elsevier, vol. 18(4), pages 711-727, September.

  27. Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2007. "A Model for Multivariate Non-negative Valued Processes in Financial Econometrics," Econometrics Working Papers Archive wp2007_16, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".

    Cited by:

    1. Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2013. "Semiparametric Vector Mem," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(7), pages 1067-1086, November.
    2. Luintel, Kul B & Xu, Yongdeng, 2013. "Testing weak exogeneity in multiplicative error models," Cardiff Economics Working Papers E2013/6, Cardiff University, Cardiff Business School, Economics Section.
    3. Matteo Barigozzi & Christian T. Brownlees & Giampiero M. Gallo & David Veredas, 2010. "Disentangling Systematic and Idiosyncratic Risk for Large Panels of Assets," Econometrics Working Papers Archive wp2010_06, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    4. Bodnar, Taras & Hautsch, Nikolaus, 2016. "Dynamic conditional correlation multiplicative error processes," Journal of Empirical Finance, Elsevier, vol. 36(C), pages 41-67.
    5. Ng, F.C. & Li, W.K. & Yu, Philip L.H., 2016. "Diagnostic checking of the vector multiplicative error model," Computational Statistics & Data Analysis, Elsevier, vol. 94(C), pages 86-97.
    6. Heejoon Han & Dennis Kristensen, 2012. "Asymptotic Theory for the QMLE in GARCH-X Models with Stationary and Non-Stationary Covariates," CREATES Research Papers 2012-25, Department of Economics and Business Economics, Aarhus University.
    7. Huiling Yuan & Guodong Li & Junhui Wang, 2022. "High-Frequency-Based Volatility Model with Network Structure," Papers 2204.12933, arXiv.org.
    8. Christian T. Brownlees & Fabrizio Cipollini & Giampiero M. Gallo, 2011. "Multiplicative Error Models," Econometrics Working Papers Archive 2011_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Apr 2011.
    9. Peter Reinhard Hansen & Zhuo Huang, 2012. "Exponential GARCH Modeling with Realized Measures of Volatility," Economics Working Papers ECO2012/26, European University Institute.
    10. E. Otranto, 2012. "Spillover Effects in the Volatility of Financial Markets," Working Paper CRENoS 201217, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    11. Neil Shephard & Kevin Sheppard, 2009. "Realising the future: forecasting with high frequency based volatility (HEAVY) models," Economics Papers 2009-W03, Economics Group, Nuffield College, University of Oxford.
    12. Stanislav Anatolyev & Nikolay Gospodinov, 2015. "Multivariate return decomposition: theory and implications," FRB Atlanta Working Paper 2015-7, Federal Reserve Bank of Atlanta.
    13. Diaa Noureldin & Neil Shephard & Kevin Sheppard, 2012. "Multivariate high‐frequency‐based volatility (HEAVY) models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(6), pages 907-933, September.
    14. Cipollini, Fabrizio & Gallo, Giampiero M., 2010. "Automated variable selection in vector multiplicative error models," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2470-2486, November.
    15. Heejoon Han & Myung D. Park, 2013. "Comparison of Realized Measure and Implied Volatility in Forecasting Volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(6), pages 522-533, September.
    16. Lien, Donald & Lee, Geul & Yang, Li & Zhang, Yuyin, 2018. "Volatility spillovers among the U.S. and Asian stock markets: A comparison between the periods of Asian currency crisis and subprime credit crisis," The North American Journal of Economics and Finance, Elsevier, vol. 46(C), pages 187-201.
    17. Peter Reinhard Hansen & Zhuo (Albert) Huang & Howard Howan Shek, "undated". "Realized GARCH: A Complete Model of Returns and Realized Measures of Volatility," CREATES Research Papers 2010-13, Department of Economics and Business Economics, Aarhus University.
    18. N. Taylor & Y. Xu, 2017. "The logarithmic vector multiplicative error model: an application to high frequency NYSE stock data," Quantitative Finance, Taylor & Francis Journals, vol. 17(7), pages 1021-1035, July.

  28. Giampiero Gallo & Edoardo Otranto, 2007. "Volatility Spillovers, Interdependence and Comovements: A Markov Switching Approach," Econometrics Working Papers Archive wp2007_11, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".

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    1. el Alaoui, AbdelKader & Masih, Mansur & Bacha, Obiyathulla & Asutay, Mehmet, 2014. "Leverage versus volatility: Evidence from the Capital Structure of European Firms," MPRA Paper 57682, University Library of Munich, Germany.
    2. Dewandaru, Ginanjar & Rizvi, Syed Aun R. & Masih, Rumi & Masih, Mansur & Alhabshi, Syed Othman, 2014. "Stock market co-movements: Islamic versus conventional equity indices with multi-timescales analysis," Economic Systems, Elsevier, vol. 38(4), pages 553-571.
    3. Huo, Rui & Ahmed, Abdullahi D., 2017. "Return and volatility spillovers effects: Evaluating the impact of Shanghai-Hong Kong Stock Connect," Economic Modelling, Elsevier, vol. 61(C), pages 260-272.
    4. Gallegati, Marco, 2012. "A wavelet-based approach to test for financial market contagion," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3491-3497.
    5. Xu, Yongdeng & Taylor, Nick & Lu, Wenna, 2018. "Illiquidity and volatility spillover effects in equity markets during and after the global financial crisis: An MEM approach," International Review of Financial Analysis, Elsevier, vol. 56(C), pages 208-220.
    6. Giampiero M. Gallo & Edoardo Otranto, 2012. "Realized Volatility and Change of Regimes," Econometrics Working Papers Archive 2012_02, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Jul 2012.
    7. Guan, Bo & Mazouz, Khelifa & Xu, Yongdeng, 2023. "Asymmetric volatility spillover between crude oil and other asset markets," Cardiff Economics Working Papers E2023/27, Cardiff University, Cardiff Business School, Economics Section.
    8. Demetrio Lacava & Luca Scaffidi Domianello, 2021. "The Incidence of Spillover Effects during the Unconventional Monetary Policies Era," JRFM, MDPI, vol. 14(6), pages 1-18, May.
    9. Xu, Yongdeng & Guan, Bo & Lu, Wenna & Heravi, Saeed, 2024. "Macroeconomic shocks and volatility spillovers between stock, bond, gold and crude oil markets," Energy Economics, Elsevier, vol. 136(C).
    10. Aliyu, Shehu Usman Rano, 2020. "What have we learnt from modelling stock returns in Nigeria: Higgledy-piggledy?," MPRA Paper 110382, University Library of Munich, Germany, revised 06 Jun 2021.
    11. Papadamou, Stephanos & Markopoulos, Thomas, 2018. "Interest rate pass through in a Markov-switching Vector Autoregression model: Evidence from Greek retail bank interest rates," The Journal of Economic Asymmetries, Elsevier, vol. 17(C), pages 48-60.
    12. Dewandaru, Ginanjar & Masih, Rumi & Masih, A. Mansur M., 2015. "Why is no financial crisis a dress rehearsal for the next? Exploring contagious heterogeneities across major Asian stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 241-259.
    13. Khalifa, Ahmed A. & Alsarhan, Abdulwahab A. & Bertuccelli, Pietro, 2017. "Causes and consequences of energy price shocks on petroleum-based stock market using the spillover asymmetric multiplicative error model," Research in International Business and Finance, Elsevier, vol. 39(PA), pages 307-314.
    14. Afonso, António & Gomes, Pedro & Taamouti, Abderrahim, 2014. "Sovereign credit ratings, market volatility, and financial gains," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 20-33.
    15. Zied Ftiti & Aviral Tiwari & Amél Belanès, 2014. "Tests of Financial Market Contagion: Evolutionary Cospectral Analysis V.S. Wavelet Analysis," Working Papers 2014-62, Department of Research, Ipag Business School.
    16. E. Otranto, 2008. "Clustering Heteroskedastic Time Series by Model-Based Procedures," Working Paper CRENoS 200801, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    17. Wang, Ruting & Althof, Michael & Härdle, Wolfgang Karl, 2023. "A financial risk meter for China," Emerging Markets Review, Elsevier, vol. 56(C).
    18. Balcilar, Mehmet & Kutan, Ali M. & Yaya, Mehmet E., 2017. "Financial integration in small Islands: The case of Cyprus," International Review of Economics & Finance, Elsevier, vol. 47(C), pages 201-219.
    19. Kangogo, Moses & Volkov, Vladimir, 2022. "Detecting signed spillovers in global financial markets: A Markov-switching approach," International Review of Financial Analysis, Elsevier, vol. 82(C).
    20. Dewandaru, Ginanjar & Masih, Rumi & Masih, A. Mansur M., 2016. "What can wavelets unveil about the vulnerabilities of monetary integration? A tale of Eurozone stock markets," Economic Modelling, Elsevier, vol. 52(PB), pages 981-996.
    21. Ana Escribano & Cristina Íñiguez, 2021. "The contagion phenomena of the Brexit process on main stock markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4462-4481, July.
    22. Małgorzata Doman & Ryszard Doman, 2013. "Dynamic linkages between stock markets: the effects of crises and globalization," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 12(2), pages 87-112, August.
    23. R. Gargano & E. Otranto, 2013. "Financial Clustering in Presence of Dominant Markets," Working Paper CRENoS 201318, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    24. Rizvi, Syed Aun R. & Arshad, Shaista & Alam, Nafis, 2015. "Crises and contagion in Asia Pacific — Islamic v/s conventional markets," Pacific-Basin Finance Journal, Elsevier, vol. 34(C), pages 315-326.
    25. Mensi, Walid & Reboredo, Juan C. & Ugolini, Andrea & Vo, Xuan Vinh, 2022. "Switching connectedness between real estate investment trusts, oil, and gold markets," Finance Research Letters, Elsevier, vol. 49(C).
    26. Zheng, Tingguo & Zuo, Haomiao, 2013. "Reexamining the time-varying volatility spillover effects: A Markov switching causality approach," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 643-662.
    27. E. Otranto, 2012. "Spillover Effects in the Volatility of Financial Markets," Working Paper CRENoS 201217, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    28. Nikos Nomikos & Enrique Salvador, 2014. "The role of volatility regimes on volatility transmission patterns," Quantitative Finance, Taylor & Francis Journals, vol. 14(1), pages 1-13, January.
    29. Salem Adel Ziadat & David G. McMillan, 2022. "Oil-stock nexus: the role of oil shocks for GCC markets," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 39(5), pages 801-818, May.
    30. E. Otranto, 2024. "A Vector Multiplicative Error Model with Spillover Effects and Co-movements," Working Paper CRENoS 202404, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    31. Gallo, Giampiero M. & Otranto, Edoardo, 2015. "Forecasting realized volatility with changing average levels," International Journal of Forecasting, Elsevier, vol. 31(3), pages 620-634.
    32. Thomas Dimpfl & Robert C. Jung, 2012. "Financial market spillovers around the globe," Applied Financial Economics, Taylor & Francis Journals, vol. 22(1), pages 45-57, January.
    33. Dewandaru, Ginanjar & Masih, Rumi & Masih, A. Mansur M., 2016. "Contagion and interdependence across Asia-Pacific equity markets: An analysis based on multi-horizon discrete and continuous wavelet transformations," International Review of Economics & Finance, Elsevier, vol. 43(C), pages 363-377.
    34. el Alaoui, AbdelKader & Masih, Mansur & Bacha, Obiyathulla & Asutay, Mehmet, 2014. "Leverage, return, volatility and contagion: Evidence from the portfolio framework," MPRA Paper 57726, University Library of Munich, Germany.
    35. Franck Martin & Jiangxingyun Zhang, 2014. "Correlation and volatility on bond markets during the EMU crisis: does the OMT change the process ?," Economics Bulletin, AccessEcon, vol. 34(2), pages 1327-1349.
    36. Otranto, Edoardo, 2010. "Identifying financial time series with similar dynamic conditional correlation," Computational Statistics & Data Analysis, Elsevier, vol. 54(1), pages 1-15, January.
    37. A. Khalifa & S. Hammoudeh & E. Otranto, 2012. "Volatility Spillover, Interdependence, Comovements across GCC, Oil and U.S. Markets and Portfolio Management Strategies in a Regime-Changing Environment," Working Paper CRENoS 201209, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    38. Burzala, Milda Maria, 2016. "Contagion effects in selected European capital markets during the financial crisis of 2007–2009," Research in International Business and Finance, Elsevier, vol. 37(C), pages 556-571.
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    45. Marcel Aloy & Gilles de Truchis & Gilles Dufrénot & Benjamin Keddad, 2014. "Shift-Volatility Transmission in East Asian Equity Markets," AMSE Working Papers 1402, Aix-Marseille School of Economics, France, revised Mar 2014.
    46. Chung Baek, 2020. "Risk Transmissions between Major Foreign Currencies: An Empirical Analysis from the U.S. Perspective," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 19(2), pages 151-168, September.
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    53. Wuyi Ye & Kebing Luo & Shaofu Du, 2014. "Measuring Contagion of Subprime Crisis Based on MVMQ-CAViaR Method," Discrete Dynamics in Nature and Society, Hindawi, vol. 2014, pages 1-12, June.
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    56. 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.
    57. Shegorika Rajwani & Dilip Kumar, 2016. "Asymmetric Dynamic Conditional Correlation Approach to Financial Contagion: A Study of Asian Markets," Global Business Review, International Management Institute, vol. 17(6), pages 1339-1356, December.
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    60. Khalifa, Ahmed A.A. & Hammoudeh, Shawkat & Otranto, Edoardo, 2014. "Patterns of volatility transmissions within regime switching across GCC and global markets," International Review of Economics & Finance, Elsevier, vol. 29(C), pages 512-524.
    61. Ginanjar Dewandaru & Rumi Masih & Mansur Masih, 2018. "Unraveling the Financial Contagion in European Stock Markets During Financial Crises: Multi-Timescale Analysis," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 54(4), pages 859-880, March.
    62. Alqaralleh, Huthaifa & Canepa, Alessandra & Chini, Zanetti, 2021. "Financial Contagion During the Covid-19 Pandemic: A Wavelet-Copula-GARCH Approach," Department of Economics and Statistics Cognetti de Martiis. Working Papers 202110, University of Turin.
    63. A. Khalifa & S. Hammoudeh & E. Otranto & S. Ramchander, 2012. "Volatility Transmission across Currency, Commodity and Equity Markets under Multi-Chain Regime Switching: Implications for Hedging and Portfolio Allocation," Working Paper CRENoS 201214, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    64. Giampiero M. Gallo & Edoardo Otranto, 2014. "Forecasting Realized Volatility with Changes of Regimes," Econometrics Working Papers Archive 2014_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Feb 2014.
    65. BenSaïda, Ahmed & Litimi, Houda & Abdallah, Oussama, 2018. "Volatility spillover shifts in global financial markets," Economic Modelling, Elsevier, vol. 73(C), pages 343-353.
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  29. Christian T. Brownlees & Giampiero Gallo, 2007. "Flexible Time Series Forecasting Using Shrinkage Techniques and Focused Selection Criteria," Econometrics Working Papers Archive wp2007_02, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".

    Cited by:

    1. Christian T. Brownlees & Giampiero Gallo, 2007. "Volatility Forecasting Using Explanatory Variables and Focused Selection Criteria," Econometrics Working Papers Archive wp2007_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".

  30. Giampiero Gallo & Edoardo Otranto, 2006. "Volatility Transmission Across Markets: A Multi-Chain Markov Switching Model," Econometrics Working Papers Archive wp2006_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".

    Cited by:

    1. Xu, Yongdeng & Taylor, Nick & Lu, Wenna, 2018. "Illiquidity and volatility spillover effects in equity markets during and after the global financial crisis: An MEM approach," International Review of Financial Analysis, Elsevier, vol. 56(C), pages 208-220.
    2. Giampiero M. Gallo & Edoardo Otranto, 2012. "Realized Volatility and Change of Regimes," Econometrics Working Papers Archive 2012_02, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Jul 2012.
    3. Khalifa, Ahmed A. & Alsarhan, Abdulwahab A. & Bertuccelli, Pietro, 2017. "Causes and consequences of energy price shocks on petroleum-based stock market using the spillover asymmetric multiplicative error model," Research in International Business and Finance, Elsevier, vol. 39(PA), pages 307-314.
    4. E. Otranto, 2008. "Clustering Heteroskedastic Time Series by Model-Based Procedures," Working Paper CRENoS 200801, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    5. Vít Bubák & Evžen Kocenda & Filip Zikes, 2010. "Volatility Transmission in Emerging European Foreign Exchange Markets," CESifo Working Paper Series 3063, CESifo.
    6. R. Gargano & E. Otranto, 2013. "Financial Clustering in Presence of Dominant Markets," Working Paper CRENoS 201318, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    7. P. K. Mishra & S. K. Mishra, 2022. "Is the Impact of COVID-19 Significant in Determining Equity Market Integration? Insights from BRICS Economies," Global Journal of Emerging Market Economies, Emerging Markets Forum, vol. 14(2), pages 137-162, May.
    8. Emanuele Bacchiocchi & Marta Bevilacqua, 2009. "International crises, instability periods and contagion: the case of the ERM," International Review of Economics, Springer;Happiness Economics and Interpersonal Relations (HEIRS), vol. 56(2), pages 105-122, June.
    9. Maghyereh, Aktham I. & Awartani, Basel & Hilu, Khalil Al, 2015. "Dynamic transmissions between the U.S. and equity markets in the MENA countries: New evidence from pre- and post-global financial crisis," The Quarterly Review of Economics and Finance, Elsevier, vol. 56(C), pages 123-138.
    10. E. Otranto, 2012. "Spillover Effects in the Volatility of Financial Markets," Working Paper CRENoS 201217, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    11. Robert F. Engle & Giampiero M. Gallo & Margherita Velucchi, 2012. "Volatility Spillovers in East Asian Financial Markets: A Mem-Based Approach," The Review of Economics and Statistics, MIT Press, vol. 94(1), pages 222-223, February.
    12. Gallo, Giampiero M. & Otranto, Edoardo, 2015. "Forecasting realized volatility with changing average levels," International Journal of Forecasting, Elsevier, vol. 31(3), pages 620-634.
    13. Gagliardini, Patrick & Gouriéroux, Christian, 2013. "Correlated risks vs contagion in stochastic transition models," Journal of Economic Dynamics and Control, Elsevier, vol. 37(11), pages 2241-2269.
    14. Mohanasundaram Thangamuthu & Suneel Maheshwari & Deepak Raghava Naik, 2022. "Volatility Spillover Effects during Pre-and-Post COVID-19 Outbreak on Indian Market from the USA, China, Japan, Germany, and Australia," JRFM, MDPI, vol. 15(9), pages 1-15, August.
    15. A. Khalifa & S. Hammoudeh & E. Otranto, 2012. "Volatility Spillover, Interdependence, Comovements across GCC, Oil and U.S. Markets and Portfolio Management Strategies in a Regime-Changing Environment," Working Paper CRENoS 201209, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    16. Mariya Gubareva & Benjamin Keddad, 2022. "Emerging markets financial sector debt: A Markov‐switching study of interest rate sensitivity," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 3851-3863, October.
    17. Marcel Aloy & Gilles de Truchis & Gilles Dufrénot & Benjamin Keddad, 2014. "Shift-Volatility Transmission in East Asian Equity Markets," AMSE Working Papers 1402, Aix-Marseille School of Economics, France, revised Mar 2014.
    18. Awartani, Basel & Maghyereh, Aktham I. & Shiab, Mohammad Al, 2013. "Directional spillovers from the U.S. and the Saudi market to equities in the Gulf Cooperation Council countries," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 27(C), pages 224-242.
    19. Margherita Velucchi, 2009. "Regime switching: Italian financial markets over a century," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 18(1), pages 67-86, March.
    20. Khalifa, Ahmed A.A. & Hammoudeh, Shawkat & Otranto, Edoardo, 2014. "Patterns of volatility transmissions within regime switching across GCC and global markets," International Review of Economics & Finance, Elsevier, vol. 29(C), pages 512-524.
    21. A. Khalifa & S. Hammoudeh & E. Otranto & S. Ramchander, 2012. "Volatility Transmission across Currency, Commodity and Equity Markets under Multi-Chain Regime Switching: Implications for Hedging and Portfolio Allocation," Working Paper CRENoS 201214, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    22. Giampiero M. Gallo & Edoardo Otranto, 2014. "Forecasting Realized Volatility with Changes of Regimes," Econometrics Working Papers Archive 2014_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Feb 2014.
    23. Khalifa, Ahmed A.A. & Hammoudeh, Shawkat & Otranto, Edoardo, 2014. "Extracting portfolio management strategies from volatility transmission models in regime-changing environments: Evidence from GCC and global markets," Economic Modelling, Elsevier, vol. 41(C), pages 365-374.
    24. Koulakiotis, Athanasios & Dasilas, Apostolos & Papasyriopoulos, Nicholas, 2009. "Volatility and error transmission spillover effects: Evidence from three European financial regions," The Quarterly Review of Economics and Finance, Elsevier, vol. 49(3), pages 858-869, August.
    25. Giampiero M. Gallo & Margherita Velucchi, 2009. "Market interdependence and financial volatility transmission in East Asia," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 14(1), pages 24-44.
    26. Khalifa, Ahmed A.A. & Otranto, Edoardo & Hammoudeh, Shawkat & Ramchander, Sanjay, 2016. "Volatility transmission across currencies and commodities with US uncertainty measures," The North American Journal of Economics and Finance, Elsevier, vol. 37(C), pages 63-83.
    27. A. Maghyereh & B. Awartani, 2012. "Return and volatility spillovers between Dubai financial market and Abu Dhabi Stock Exchange in the UAE," Applied Financial Economics, Taylor & Francis Journals, vol. 22(10), pages 837-848, May.

  31. Christian T. Brownlees & Giampiero Gallo, 2006. "Financial Econometric Analysis at Ultra–High Frequency: Data Handling Concerns," Econometrics Working Papers Archive wp2006_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".

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    1. Tadle, Raul Cruz, 2022. "FOMC minutes sentiments and their impact on financial markets," Journal of Economics and Business, Elsevier, vol. 118(C).
    2. Brownlees, Christian T. & Gallo, Giampiero M., 2011. "Shrinkage estimation of semiparametric multiplicative error models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 365-378.
    3. Scherrer, Cristina Mabel, 2021. "Information processing on equity prices and exchange rate for cross-listed stocks," Journal of Financial Markets, Elsevier, vol. 54(C).
    4. Marshall, Ben R. & Nguyen, Nhut H. & Visaltanachoti, Nuttawat, 2013. "Liquidity commonality in commodities," Journal of Banking & Finance, Elsevier, vol. 37(1), pages 11-20.
    5. Márcio Gomes Pinto Garcia & Marcelo Cunha Medeiros & Francisco Eduardo de Luna e Almeida Santos, 2014. "Economic gains of realized volatility in the Brazilian stock market," Brazilian Review of Finance, Brazilian Society of Finance, vol. 12(3), pages 319-349.
    6. Ng, Jason & Forbes, Catherine S. & Martin, Gael M. & McCabe, Brendan P.M., 2013. "Non-parametric estimation of forecast distributions in non-Gaussian, non-linear state space models," International Journal of Forecasting, Elsevier, vol. 29(3), pages 411-430.
    7. Matteo Barigozzi & Christian T. Brownlees & Giampiero M. Gallo & David Veredas, 2010. "Disentangling Systematic and Idiosyncratic Risk for Large Panels of Assets," Econometrics Working Papers Archive wp2010_06, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    8. Siem Jan Koopman & Rutger Lit & Andre Lucas, 2015. "Intraday Stochastic Volatility in Discrete Price Changes: the Dynamic Skellam Model," Tinbergen Institute Discussion Papers 15-076/IV/DSF94, Tinbergen Institute.
    9. Nina Karnaukh & Angelo Ranaldo & Paul Söderlind, 2015. "Understanding FX Liquidity," The Review of Financial Studies, Society for Financial Studies, vol. 28(11), pages 3073-3108.
    10. Leopoldo Catania & Tommaso Proietti, 2019. "Forecasting Volatility with Time-Varying Leverage and Volatility of Volatility Effects," CEIS Research Paper 450, Tor Vergata University, CEIS, revised 06 Feb 2019.
    11. S. Bordignon & D. Raggi, 2010. "Long memory and nonlinearities in realized volatility: a Markov switching approach," Working Papers 694, Dipartimento Scienze Economiche, Universita' di Bologna.
    12. Perera, Indeewara & Silvapulle, Mervyn J., 2021. "Bootstrap based probability forecasting in multiplicative error models," Journal of Econometrics, Elsevier, vol. 221(1), pages 1-24.
    13. Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2017. "Copula-based vMEM Specifications versus Alternatives: The Case of Trading Activity," Econometrics Working Papers Archive 2017_02, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    14. Ole E. Barndorff-Nielsen & Peter Reinhard Hansen & Asger Lunde & Neil Shephard, 2011. "Multivariate realised kernels: Consistent positive semi-definite estimators of the covariation of equity prices with noise and non-synchronous trading," Post-Print hal-00815564, HAL.
    15. Anne Opschoor & André Lucas, 2019. "Time-varying tail behavior for realized kernels," Tinbergen Institute Discussion Papers 19-051/IV, Tinbergen Institute.
    16. Fulvia Fringuellotti & Thomas Kroen, 2024. "Payout Restrictions and Bank Risk-Shifting," Staff Reports 1123, Federal Reserve Bank of New York.
    17. Cheng, Mingmian & Liao, Yuan & Yang, Xiye, 2023. "Uniform predictive inference for factor models with instrumental and idiosyncratic betas," Journal of Econometrics, Elsevier, vol. 237(2).
    18. Alfeus, Mesias & Nikitopoulos, Christina Sklibosios, 2022. "Forecasting volatility in commodity markets with long-memory models," Journal of Commodity Markets, Elsevier, vol. 28(C).
    19. Ranjan R. Chakravarty & Sudhanshu Pani, 2021. "A Data Paradigm to Operationalise Expanded Filtration: Realized Volatilities and Kernels from Non-Synchronous NASDAQ Quotes and Trades," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(4), pages 617-652, December.
    20. Giampiero M. Gallo & Demetrio Lacava & Edoardo Otranto, 2023. "Volatility jumps and the classification of monetary policy announcements," Papers 2305.12192, arXiv.org.
    21. Maria Čuljak & Josip Arnerić & Ante Žigman, 2022. "Is Jump Robust Two Times Scaled Estimator Superior among Realized Volatility Competitors?," Mathematics, MDPI, vol. 10(12), pages 1-11, June.
    22. Novotný, Jan & Petrov, Dmitri & Urga, Giovanni, 2015. "Trading price jump clusters in foreign exchange markets," Journal of Financial Markets, Elsevier, vol. 24(C), pages 66-92.
    23. Farshid Abdi & Botao Wu, 2018. "Informed Corporate Credit Market Before Monetary Policy Surprises: Explaining Pre-FOMC Stock Market Movements," Working Papers on Finance 1828, University of St. Gallen, School of Finance.
    24. Keren Shen & Jianfeng Yao & Wai Keung Li, 2016. "On the Surprising Explanatory Power of Higher Realized Moments in Practice," Papers 1604.07969, arXiv.org.
    25. Lucio Maria Calcagnile & Fulvio Corsi & Stefano Marmi, 2016. "Entropy and efficiency of the ETF market," Papers 1609.04199, arXiv.org.
    26. Opschoor, Anne & Lucas, André, 2021. "Observation-driven models for realized variances and overnight returns applied to Value-at-Risk and Expected Shortfall forecasting," International Journal of Forecasting, Elsevier, vol. 37(2), pages 622-633.
    27. Alketa Bejko & Belinda Xarba, 2021. "The Evaluation of the Drafting Process of Regional’s Development Strategies in Albania. the Research on Gjirokastra’s Region," European Journal of Interdisciplinary Studies Articles, Revistia Research and Publishing, vol. 1, September.
    28. Jean-Yves Gnabo & J�rôme Lahaye & S�bastien Laurent & Christelle Lecourt, 2012. "Do jumps mislead the FX market?," Quantitative Finance, Taylor & Francis Journals, vol. 12(10), pages 1521-1532, October.
    29. Worapree Maneesoonthorn & Catherine S. Forbes & Gael M. Martin, 2014. "Inference on Self-Exciting Jumps in Prices and Volatility using High Frequency Measures," Monash Econometrics and Business Statistics Working Papers 30/14, Monash University, Department of Econometrics and Business Statistics.
    30. Scherrer, Cristina Mabel, 2021. "Information processing on equity prices and exchange rate for cross-listed stocks," LSE Research Online Documents on Economics 125649, London School of Economics and Political Science, LSE Library.
    31. Caporin, Massimiliano & Ranaldo, Angelo & Velo, Gabriel G., 2013. "Stylized Facts and Dynamic Modeling of High-frequency Data on Precious Metals," Working Papers on Finance 1318, University of St. Gallen, School of Finance.
    32. Fabrizio Cipollini & Giampiero M. Gallo & Edoardo Otranto, 2019. "Realized Volatility Forecasting: Robustness to Measurement Errors," Econometrics Working Papers Archive 2019_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    33. Wei Lin & Gloria González‐Rivera, 2019. "Extreme returns and intensity of trading," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(7), pages 1121-1140, November.
    34. Alfred Wong & Jiayue Zhang, 2018. "Breakdown of covered interest parity: mystery or myth?," BIS Papers chapters, in: Bank for International Settlements (ed.), The price, real and financial effects of exchange rates, volume 96, pages 57-78, Bank for International Settlements.
    35. 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.
    36. Kim Christensen & Ulrich Hounyo & Mark Podolskij, 2017. "Is the diurnal pattern sufficient to explain the intraday variation in volatility? A nonparametric assessment," CREATES Research Papers 2017-30, Department of Economics and Business Economics, Aarhus University.
    37. Andrey Shternshis & Piero Mazzarisi & Stefano Marmi, 2022. "Efficiency of the Moscow Stock Exchange before 2022," Papers 2207.10476, arXiv.org, revised Jul 2022.
    38. O. E. Barndorff-Nielsen & P. Reinhard Hansen & A. Lunde & N. Shephard, 2009. "Realized kernels in practice: trades and quotes," Econometrics Journal, Royal Economic Society, vol. 12(3), pages 1-32, November.
    39. Cristina M. Scherrer, 2014. "Cross listing: price discovery dynamics and exchange rate effects," CREATES Research Papers 2014-53, Department of Economics and Business Economics, Aarhus University.
    40. Christian T. Brownlees & Fabrizio Cipollini & Giampiero M. Gallo, 2011. "Multiplicative Error Models," Econometrics Working Papers Archive 2011_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Apr 2011.
    41. Fabrizio Cipollini & Giampiero M. Gallo & Alessandro Palandri, 2020. "A dynamic conditional approach to portfolio weights forecasting," Papers 2004.12400, arXiv.org.
    42. Mancino, M.E. & Sanfelici, S., 2008. "Robustness of Fourier estimator of integrated volatility in the presence of microstructure noise," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2966-2989, February.
    43. Shternshis, Andrey & Mazzarisi, Piero & Marmi, Stefano, 2022. "Measuring market efficiency: The Shannon entropy of high-frequency financial time series," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).
    44. Petrasek, Lubomir, 2010. "Multimarket trading and the cost of debt: evidence from global bonds," Working Paper Series 1212, European Central Bank.
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  32. Simone Bertoli & Giampiero Gallo & Giorgio Ricchiuti, 2006. "Exchange Market Pressure: Some Caveats In Empirical Applications," Econometrics Working Papers Archive wp2006_17, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".

    Cited by:

    1. Ahmad K. Naimzada & Giorgio Ricchiuti, 2014. "Complexity with Heterogeneous Fundamentalists and a Multiplicative Price Mechanism," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 43(3), pages 233-247, November.
    2. Simone Bertoli & Giampiero Gallo & Giorgio Ricchiuti, 2010. "Exchange market pressure: some caveats in empirical applications," Applied Economics, Taylor & Francis Journals, vol. 42(19), pages 2435-2448.
    3. Scott W. Hegerty, 2014. "Measuring Exchange Market Pressure and Its Contagion in the East African Community," South African Journal of Economics, Economic Society of South Africa, vol. 82(2), pages 239-257, June.
    4. Scott W. Hegerty, 2012. "How integrated are the exchange markets of the Baltic Sea Region? An examination of market pressure and its contagion," Baltic Journal of Economics, Baltic International Centre for Economic Policy Studies, vol. 12(2), pages 109-122, December.
    5. Stavarek, Daniel, 2010. "Determinants of the exchange market pressure in the euro-candidate countries," MPRA Paper 26933, University Library of Munich, Germany.
    6. Senanu Kwasi Klutse & Judit Sági & Gábor Dávid Kiss, 2022. "Exchange Rate Crisis among Inflation Targeting Countries in Sub-Saharan Africa," Risks, MDPI, vol. 10(5), pages 1-13, May.
    7. Mr. Selim A Elekdag & Mr. Ayhan Kose & Mr. Roberto Cardarelli, 2009. "Capital Inflows: Macroeconomic Implications and Policy Responses," IMF Working Papers 2009/040, International Monetary Fund.
    8. HEGERTY, Scott W., 2014. "Exchange Market Pressure And Regional Price Spillovers In Russia, Ukraine, And Belarus," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 14(2).
    9. Fabio Filipozzi & Kersti Harkmann, 2010. "The Financial Crisis in Central and Eastern Europe: the Measures and Determinants of the Exchange Market Pressure Index and the Money Market Pressure Index," Research in Economics and Business: Central and Eastern Europe, Tallinn School of Economics and Business Administration, Tallinn University of Technology, vol. 2(2).
    10. Abdul Aziz, Muhammad & Widodo, Tri, 2017. "Exchange Market Pressure: Evidences from ASEAN Inflation Targeting Countries," MPRA Paper 80919, University Library of Munich, Germany.
    11. Scott William Hegerty, 2013. "Principal component measures of exchange market pressure: comparisons with variance-weighted measures," Applied Financial Economics, Taylor & Francis Journals, vol. 23(18), pages 1483-1495, September.
    12. Franc Klaassen, 2011. "Identifying the Weights in Exchange Market Pressure," Tinbergen Institute Discussion Papers 11-030/2, Tinbergen Institute.
    13. Devendra Kumar Jain & Rup Singh & Arvind Patel & Ronal Chand, 2023. "Foreign exchange market asymmetries in Pacific small island developing states: Evidence from Fiji," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 4353-4364, October.
    14. Jorge Braga de Macedo & Luis Pereira & Afonso Reis, 2009. "Comparing Exchange Market Pressure across Five African Countries," Open Economies Review, Springer, vol. 20(5), pages 645-682, November.
    15. Scott W Hegerty, 2013. "Exchange Market Pressure, Output Drops, and Domestic Credit: Do Emerging Markets Behave Differently?," Economics Bulletin, AccessEcon, vol. 33(4), pages 2583-2595.
    16. Scott W. Hegerty, 2015. "Time-Varying Versus Fixed Weights in Exchange-Market Pressure Indices: Evidence From Tests Using Latin American Data," Bulletin of Applied Economics, Risk Market Journals, vol. 2(1), pages 21-36.

  33. Fabrizio Cipollini & Robert F. Engle & Giampiero Gallo, 2006. "Vector Multiplicative Error Models: Representation and Inference," Econometrics Working Papers Archive wp2006_15, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".

    Cited by:

    1. Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2013. "Semiparametric Vector Mem," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(7), pages 1067-1086, November.
    2. Anders Eriksson & Daniel P. A. Preve & Jun Yu, 2019. "Forecasting Realized Volatility Using a Nonnegative Semiparametric Model," JRFM, MDPI, vol. 12(3), pages 1-23, August.
    3. Geert Dhaene & Piet Sercu & Jianbin Wu, 2022. "Volatility spillovers: A sparse multivariate GARCH approach with an application to commodity markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(5), pages 868-887, May.
    4. Alketa Bejko & Belinda Xarba, 2021. "The Evaluation of the Drafting Process of Regional’s Development Strategies in Albania. the Research on Gjirokastra’s Region," European Journal of Interdisciplinary Studies Articles, Revistia Research and Publishing, vol. 1, September.
    5. Donelli, Nicola & Peluso, Stefano & Mira, Antonietta, 2021. "A Bayesian semiparametric vector Multiplicative Error Model," Computational Statistics & Data Analysis, Elsevier, vol. 161(C).
    6. Ahoniemi, Katja & Lanne, Markku, 2007. "Joint Modeling of Call and Put Implied Volatility," MPRA Paper 6318, University Library of Munich, Germany.
    7. Drew Creal & Siem Jan Koopman & André Lucas, 2008. "A General Framework for Observation Driven Time-Varying Parameter Models," Tinbergen Institute Discussion Papers 08-108/4, Tinbergen Institute.
    8. Fabrizio Cipollini & Giampiero M. Gallo, 2021. "Multiplicative Error Models: 20 years on," Papers 2107.05923, arXiv.org.
    9. E. Otranto, 2012. "Spillover Effects in the Volatility of Financial Markets," Working Paper CRENoS 201217, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    10. Naimoli, Antonio & Storti, Giuseppe, 2019. "Heterogeneous component multiplicative error models for forecasting trading volumes," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1332-1355.
    11. Robert F. Engle & Giampiero M. Gallo & Margherita Velucchi, 2012. "Volatility Spillovers in East Asian Financial Markets: A Mem-Based Approach," The Review of Economics and Statistics, MIT Press, vol. 94(1), pages 222-223, February.
    12. Nikolaus Hautsch & Peter Malec & Melanie Schienle, 2014. "Capturing the Zero: A New Class of Zero-Augmented Distributions and Multiplicative Error Processes," Journal of Financial Econometrics, Oxford University Press, vol. 12(1), pages 89-121.
    13. Christian T. Brownlees & Giampiero Gallo, 2008. "Comparison of Volatility Measures: a Risk Management Perspective," Econometrics Working Papers Archive wp2008_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    14. Hautsch, Nikolaus, 2008. "Capturing common components in high-frequency financial time series: A multivariate stochastic multiplicative error model," Journal of Economic Dynamics and Control, Elsevier, vol. 32(12), pages 3978-4015, December.
    15. Lien, Donald & Lee, Geul & Yang, Li & Zhang, Yuyin, 2018. "Volatility spillovers among the U.S. and Asian stock markets: A comparison between the periods of Asian currency crisis and subprime credit crisis," The North American Journal of Economics and Finance, Elsevier, vol. 46(C), pages 187-201.
    16. Bodnar, Taras & Hautsch, Nikolaus, 2013. "Copula-based dynamic conditional correlation multiplicative error processes," CFS Working Paper Series 2013/19, Center for Financial Studies (CFS).
    17. Matteo Barigozzi & Christian T. Brownlees & Giampiero M. Gallo & David Veredas, 2014. "Disentangling Systematic and Idiosyncratic Dynamics in Panels of Volatility Measures," Econometrics Working Papers Archive 2014_02, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Feb 2014.
    18. Hautsch, Nikolaus & Jeleskovic, Vahidin, 2008. "Modelling high-frequency volatility and liquidity using multiplicative error models," SFB 649 Discussion Papers 2008-047, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    19. Tafakori, Laleh & Pourkhanali, Armin & Fard, Farzad Alavi, 2018. "Forecasting spikes in electricity return innovations," Energy, Elsevier, vol. 150(C), pages 508-526.

  34. Giovanni De Luca & Giampiero M. Gallo, 2005. "Time-varying Mixing Weights in Mixture Autoregressive Conditional Duration Models," Econometrics Working Papers Archive wp2005_11, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".

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    1. Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2017. "Copula-based vMEM Specifications versus Alternatives: The Case of Trading Activity," Econometrics Working Papers Archive 2017_02, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    2. Roman Huptas, 2014. "Bayesian Estimation and Prediction for ACD Models in the Analysis of Trade Durations from the Polish Stock Market," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 6(4), pages 237-273, December.
    3. Luc, BAUWENS & Nikolaus, HAUTSCH, 2006. "Modelling Financial High Frequency Data Using Point Processes," Discussion Papers (ECON - Département des Sciences Economiques) 2006039, Université catholique de Louvain, Département des Sciences Economiques.
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    14. Giovanni De Luca & Giampiero Gallo, 2010. "A Time-varying Mixing Multiplicative Error Model for Realized Volatility," Econometrics Working Papers Archive wp2010_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    15. Roman Huptas, 2016. "The UHF-GARCH-Type Model in the Analysis of Intraday Volatility and Price Durations – the Bayesian Approach," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 8(1), pages 1-20, March.

  35. Giampiero M. Gallo & Edoardo Otranto, 2005. "Volatility Transmission in Financial Markets: A New Approach," Econometrics Working Papers Archive wp2005_10, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".

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    1. George Horia Ionescu & DragoÅŸ Mihai Ungureanu & Ruxandra Dana Vilag & Florian Bogdan Stoian, 2009. "Financial Contagion And Investors Behavior," Annales Universitatis Apulensis Series Oeconomica, Faculty of Sciences, "1 Decembrie 1918" University, Alba Iulia, vol. 1(11), pages 1-57.

  36. Teodosio Perez-Amaral & Giampiero M. Gallo & Halbert L. White, 2004. "A Comparison of Complementary Automatic Modeling Methods: RETINA and PcGets," Econometrics Working Papers Archive wp2004_12, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".

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    1. Antipa, Pamfili & Barhoumi, Karim & Brunhes-Lesage, Véronique & Darné, Olivier, 2012. "Nowcasting German GDP: A comparison of bridge and factor models," Journal of Policy Modeling, Elsevier, vol. 34(6), pages 864-878.
    2. Golinelli, Roberto & Parigi, Giuseppe, 2008. "Real-time squared: A real-time data set for real-time GDP forecasting," International Journal of Forecasting, Elsevier, vol. 24(3), pages 368-385.
    3. Camila Epprecht & Dominique Guegan & Álvaro Veiga, 2013. "Comparing variable selection techniques for linear regression: LASSO and Autometrics," Documents de travail du Centre d'Economie de la Sorbonne 13080, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    4. Phillips, Peter C.B., 2005. "Automated Discovery In Econometrics," Econometric Theory, Cambridge University Press, vol. 21(1), pages 3-20, February.
    5. Jennifer Castle & David Hendry, 2013. "Semi-automatic Non-linear Model selection," Economics Series Working Papers 654, University of Oxford, Department of Economics.
    6. Camila Epprecht & Dominique Guegan & Álvaro Veiga & Joel Correa da Rosa, 2017. "Variable selection and forecasting via automated methods for linear models: LASSO/adaLASSO and Autometrics," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00917797, HAL.
    7. Brunhes-Lesage, Véronique & Darné, Olivier, 2012. "Nowcasting the French index of industrial production: A comparison from bridge and factor models," Economic Modelling, Elsevier, vol. 29(6), pages 2174-2182.
    8. Barhoumi, K. & Brunhes-Lesage, V. & Darné, O. & Ferrara, L. & Pluyaud, B. & Rouvreau, B., 2008. "Monthly forecasting of French GDP: A revised version of the OPTIM model," Working papers 222, Banque de France.
    9. Giampiero M. Gallo, 2017. "Hendry, David F. and Doornik, Jurgen A.: Empirical model discovery and theory evaluation: automatic selection methods in econometrics," Journal of Economics, Springer, vol. 120(3), pages 279-281, April.
    10. Leonel Cerno & Teodosio Pérez Amaral, 2006. "Medición y Determinantes de la Brecha Tecnológica en España," Documentos de Trabajo del ICAE 0601, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    11. Marcin Blazejowski & Pawel Kufel & Tadeusz Kufel, 2009. "Automatic Procedure of Building Congruent Dynamic Model in Gretl," EHUCHAPS, in: Ignacio Díaz-Emparanza & Petr Mariel & María Victoria Esteban (ed.), Econometrics with gretl. Proceedings of the gretl Conference 2009, edition 1, chapter 5, pages 75-89, Universidad del País Vasco - Facultad de Ciencias Económicas y Empresariales.
    12. Giuseppe Parigi & Roberto Golinelli, 2007. "The use of monthly indicators to forecast quarterly GDP in the short run: an application to the G7 countries," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(2), pages 77-94.

  37. Robert F. Engle & Giampiero M. Gallo, 2003. "A Multiple Indicators Model For Volatility Using Intra-Daily Data," Econometrics Working Papers Archive wp2003_07, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".

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    1. Drew Creal & Bernd Schwaab & Siem Jan Koopman & Andr� Lucas, 2014. "Observation-Driven Mixed-Measurement Dynamic Factor Models with an Application to Credit Risk," The Review of Economics and Statistics, MIT Press, vol. 96(5), pages 898-915, December.
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    4. Chi, Tsung-Li & Liu, Hung-Tsen & Chang, Chia-Chien, 2023. "Hedging performance using google Trends–Evidence from the indian forex options market," International Review of Economics & Finance, Elsevier, vol. 85(C), pages 107-123.
    5. Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2013. "Semiparametric Vector Mem," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(7), pages 1067-1086, November.
    6. Gunther Capelle-Blancard & Olena Havrylchyk, 2014. "The Impact of the French Securities Transaction Tax on Market Liquidity and Volatility," EconomiX Working Papers 2014-27, University of Paris Nanterre, EconomiX.
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    8. Brownlees, Christian T. & Gallo, Giampiero M., 2011. "Shrinkage estimation of semiparametric multiplicative error models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 365-378.
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    10. Markus Engler & Vahidin Jeleskovic, 2016. "Intraday volatility, trading volume and trading intensity in the interbank market e-MID," MAGKS Papers on Economics 201648, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    11. Rombouts, Jeroen V.K. & Stentoft, Lars & Violante, Francesco, 2020. "Dynamics of variance risk premia: A new model for disentangling the price of risk," Journal of Econometrics, Elsevier, vol. 217(2), pages 312-334.
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    16. G.M. Gallo & D. Lacava & E. Otranto, 2020. "On Classifying the Effects of Policy Announcements on Volatility," Working Paper CRENoS 202008, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
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    236. Nguyen, Phuc Lam Thy & Alsakka, Rasha & Mantovan, Noemi, 2023. "Political preferences and stock markets," International Review of Financial Analysis, Elsevier, vol. 90(C).
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    243. Christian T. Brownlees & Giampiero Gallo, 2007. "Volatility Forecasting Using Explanatory Variables and Focused Selection Criteria," Econometrics Working Papers Archive wp2007_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    244. Zhuo Huang & Chen Tong & Tianyi Wang, 2019. "VIX term structure and VIX futures pricing with realized volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(1), pages 72-93, January.
    245. Asai, Manabu & Chang, Chia-Lin & McAleer, Michael, 2022. "Realized matrix-exponential stochastic volatility with asymmetry, long memory and higher-moment spillovers," Journal of Econometrics, Elsevier, vol. 227(1), pages 285-304.
    246. Clements, Adam & Hurn, Stan & Volkov, Vladimir, 2021. "A simple linear alternative to multiplicative error models with an application to trading volume," Working Papers 2021-06, University of Tasmania, Tasmanian School of Business and Economics.
    247. Jiangyu Ji & Andre Lucas, 2012. "A New Semiparametric Volatility Model," Tinbergen Institute Discussion Papers 12-055/2/DSF35, Tinbergen Institute.
    248. Lu, Hengzhen & Zhu, Xiaoyu & Wang, Jianli & Yick, Ho Yin, 2021. "Share pledge transactions as an investor sentiment indicator - Evidence from China," The Quarterly Review of Economics and Finance, Elsevier, vol. 82(C), pages 230-238.
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    250. Khalifa, Ahmed A.A. & Otranto, Edoardo & Hammoudeh, Shawkat & Ramchander, Sanjay, 2016. "Volatility transmission across currencies and commodities with US uncertainty measures," The North American Journal of Economics and Finance, Elsevier, vol. 37(C), pages 63-83.
    251. Tian, Shuairu & Hamori, Shigeyuki, 2015. "Modeling interest rate volatility: A Realized GARCH approach," Journal of Banking & Finance, Elsevier, vol. 61(C), pages 158-171.
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  38. Teodosio Perez-Amaral & Giampiero M. Gallo & Halbert L. White, 2003. "A Flexible Tool for Model Building: the Relevant Transformation of the Inputs Network Approach (RETINA)," Econometrics Working Papers Archive wp2003_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".

    Cited by:

    1. Ivan Savin & Peter Winker, 2010. "Heuristic Optimization Methods for Dynamic Panel Data Model Selection. Application on the Russian Innovative Performance," Working Papers 027, COMISEF.
    2. Castle, Jennifer L. & Doornik, Jurgen A. & Hendry, David F., 2012. "Model selection when there are multiple breaks," Journal of Econometrics, Elsevier, vol. 169(2), pages 239-246.
    3. Gernot Doppelhofer & Melvyn Weeks, 2007. "Jointness of Growth Determinants," CESifo Working Paper Series 1978, CESifo.
    4. Andreas Sachs & Frauke Schleer, 2013. "Labour Market Performance in OECD Countries: A Comprehensive Empirical Modelling Approach of Institutional Interdependencies. WWWforEurope Working Paper No. 7," WIFO Studies, WIFO, number 46851, January.
    5. Camila Epprecht & Dominique Guegan & Álvaro Veiga & Joel Correa da Rosa, 2017. "Variable selection and forecasting via automated methods for linear models: LASSO/adaLASSO and Autometrics," Post-Print halshs-00917797, HAL.
    6. Kock, Anders Bredahl & Teräsvirta, Timo, 2014. "Forecasting performances of three automated modelling techniques during the economic crisis 2007–2009," International Journal of Forecasting, Elsevier, vol. 30(3), pages 616-631.
    7. Eduardo Acosta-González & Fernando Fernández-Rodríguez, 2014. "Forecasting Financial Failure of Firms via Genetic Algorithms," Computational Economics, Springer;Society for Computational Economics, vol. 43(2), pages 133-157, February.
    8. Camila Epprecht & Dominique Guegan & Álvaro Veiga, 2013. "Comparing variable selection techniques for linear regression: LASSO and Autometrics," Documents de travail du Centre d'Economie de la Sorbonne 13080, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    9. Ivan Savin, 2010. "A comparative study of the Lasso-type and heuristic model selection methods," Working Papers 042, COMISEF.
    10. Jennifer Castle & David Hendry, 2013. "Semi-automatic Non-linear Model selection," Economics Series Working Papers 654, University of Oxford, Department of Economics.
    11. Sachs, Andreas & Schleer, Frauke, 2013. "Labour market performance in OECD countries: A comprehensive empirical modelling approach of institutional interdependencies," ZEW Discussion Papers 13-040, ZEW - Leibniz Centre for European Economic Research.
    12. David F. Hendry & Hans-Martin Krolzig, 2004. "We Ran One Regression," Economics Papers 2004-W17, Economics Group, Nuffield College, University of Oxford.
    13. Eduardo Acosta-González & Fernando Fernández-Rodríguez, 2007. "Model selection via genetic algorithms illustrated with cross-country growth data," Empirical Economics, Springer, vol. 33(2), pages 313-337, September.
    14. Eduardo Acosta-González & Fernando Fernández-Rodríguez & Hicham Ganga, 2019. "Predicting Corporate Financial Failure Using Macroeconomic Variables and Accounting Data," Computational Economics, Springer;Society for Computational Economics, vol. 53(1), pages 227-257, January.
    15. Massimiliano Marinucci & Teodosio Pérez-Amaral, 2005. "Econometric modeling of business Telecommunications demand using Retina and Finite Mixtues," Documentos de Trabajo del ICAE 0501, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    16. Jurgen A. Doornik, 2008. "Encompassing and Automatic Model Selection," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(s1), pages 915-925, December.
    17. Camila Epprecht & Dominique Guegan & Álvaro Veiga & Joel Correa da Rosa, 2017. "Variable selection and forecasting via automated methods for linear models: LASSO/adaLASSO and Autometrics," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00917797, HAL.
    18. Teodosio Pérez Amaral & Angel Valarezo Unda & Rafael López Zorzano & Teresa Garín Muñoz, 2021. "Digital divides across consumers of internet services in Spain using panel data 2007-2019. Narrowing or not?," Documentos de Trabajo del ICAE 2021-01, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    19. Ivan Savin & Peter Winker, 2012. "Lasso-type and Heuristic Strategies in Model Selection and Forecasting," Jena Economics Research Papers 2012-055, Friedrich-Schiller-University Jena.
    20. Anders Bredahl Kock & Timo Teräsvirta, 2016. "Forecasting Macroeconomic Variables Using Neural Network Models and Three Automated Model Selection Techniques," Econometric Reviews, Taylor & Francis Journals, vol. 35(8-10), pages 1753-1779, December.
    21. Jennifer Castle & David Hendry & Jurgen A. Doornik, 2010. "Evaluating Automatic Model Selection," Economics Series Working Papers 474, University of Oxford, Department of Economics.
    22. Jennifer Castle & David Hendry, 2010. "Automatic Selection for Non-linear Models," Economics Series Working Papers 473, University of Oxford, Department of Economics.
    23. Gernot Doppelhofer & Xavier Sala I Martin & Melvyn Weeks, 2005. "Jointness of Determinants of Economics Growth," Money Macro and Finance (MMF) Research Group Conference 2005 54, Money Macro and Finance Research Group.
    24. Leonel Cerno & Teodosio Pérez Amaral, 2006. "Medición y Determinantes de la Brecha Tecnológica en España," Documentos de Trabajo del ICAE 0601, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    25. Marcin Blazejowski & Pawel Kufel & Tadeusz Kufel, 2009. "Automatic Procedure of Building Congruent Dynamic Model in Gretl," EHUCHAPS, in: Ignacio Díaz-Emparanza & Petr Mariel & María Victoria Esteban (ed.), Econometrics with gretl. Proceedings of the gretl Conference 2009, edition 1, chapter 5, pages 75-89, Universidad del País Vasco - Facultad de Ciencias Económicas y Empresariales.
    26. David F. Hendry, 2024. "A Brief History of General‐to‐specific Modelling," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 86(1), pages 1-20, February.
    27. Ericsson Neil R., 2016. "Testing for and estimating structural breaks and other nonlinearities in a dynamic monetary sector," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(4), pages 377-398, September.

  39. Alessandro Rossi & Giampiero M. Gallo, 2002. "Volatility Estimation via Hidden Markov Models," Econometrics Working Papers Archive wp2002_14, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".

    Cited by:

    1. Fulvia Pennoni & Francesco Bartolucci & Gianfranco Forte & Ferdinando Ametrano, 2022. "Exploring the dependencies among main cryptocurrency log‐returns: A hidden Markov model," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 51(1), February.
    2. Markus Eller & Michael Frömmel & Nora Srzentic, 2010. "Private Sector Credit in CESEE: Long-Run Relationships and Short-Run Dynamics," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue 2, pages 50-78.
    3. Lux, Thomas & Morales-Arias, Leonardo, 2010. "Forecasting volatility under fractality, regime-switching, long memory and student-t innovations," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2676-2692, November.
    4. Michael Frömmel, 2010. "Volatility Regimes in Central and Eastern European Countries’ Exchange Rates," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 60(1), pages 2-21, February.
    5. Luca De Angelis & Leonard J. Paas, 2013. "A dynamic analysis of stock markets using a hidden Markov model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(8), pages 1682-1700, August.
    6. Lux, Thomas & Morales-Arias, Leonardo, 2009. "Forecasting volatility under fractality, regime-switching, long memory and student-t innovations," Kiel Working Papers 1532, Kiel Institute for the World Economy (IfW Kiel).
    7. Langrock, Roland & MacDonald, Iain L. & Zucchini, Walter, 2012. "Some nonstandard stochastic volatility models and their estimation using structured hidden Markov models," Journal of Empirical Finance, Elsevier, vol. 19(1), pages 147-161.
    8. Michael C. Fu & Bingqing Li & Rongwen Wu & Tianqi Zhang, 2020. "Option Pricing Under a Discrete-Time Markov Switching Stochastic Volatility with Co-Jump Model," Papers 2006.15054, arXiv.org.
    9. Arnaud Dufays & Maciej Augustyniak & Luc Bauwens, 2016. "A new approach to volatility modeling: the High-Dimensional Markov model," Cahiers de recherche 1609, Centre de recherche sur les risques, les enjeux économiques, et les politiques publiques.
    10. Hugh Christensen & Simon Godsill & Richard E Turner, 2020. "Hidden Markov Models Applied To Intraday Momentum Trading With Side Information," Papers 2006.08307, arXiv.org.
    11. Lux, Thomas & Morales-Arias, Leonardo & Sattarhoff, Cristina, 2011. "A Markov-switching multifractal approach to forecasting realized volatility," Kiel Working Papers 1737, Kiel Institute for the World Economy (IfW Kiel).
    12. L. Grossi & G. Morelli, 2006. "Robust volatility forecasts and model selection in financial time series," Economics Department Working Papers 2006-SE02, Department of Economics, Parma University (Italy).
    13. Carlos A. Abanto‐Valle & Roland Langrock & Ming‐Hui Chen & Michel V. Cardoso, 2017. "Maximum likelihood estimation for stochastic volatility in mean models with heavy‐tailed distributions," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 33(4), pages 394-408, August.
    14. Xun Huang & Huiyue Tang, 2022. "Measuring multi‐volatility states of financial markets based on multifractal clustering model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 422-434, April.
    15. Fulvio Corsi, 2009. "A Simple Approximate Long-Memory Model of Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 7(2), pages 174-196, Spring.
    16. Francesco Bartolucci & Silvia Bacci & Fulvia Pennoni, 2014. "Longitudinal analysis of self-reported health status by mixture latent auto-regressive models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 63(2), pages 267-288, February.
    17. Dias, José G. & Vermunt, Jeroen K. & Ramos, Sofia, 2015. "Clustering financial time series: New insights from an extended hidden Markov model," European Journal of Operational Research, Elsevier, vol. 243(3), pages 852-864.

  40. Massimiliano Cecconi & Giampiero M. Gallo & Marco J. Lombardi, 2002. "GARCH-based Volatility Forecasts for Market Volatility Indices," Econometrics Working Papers Archive wp2002_06, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".

    Cited by:

    1. Ryan Lemand, 2003. "New Technology Stock Market Indexes Contagion: A VAR-dccMVGARCH Approach," Econometrics 0307003, University Library of Munich, Germany, revised 07 Dec 2020.
    2. Ryan Lemand, 2003. "The Contagion Effect Between the Volatilities of the NASDAQ-100 and the IT.CA :A Univariate and A Bivariate Switching Approach," Econometrics 0307002, University Library of Munich, Germany, revised 07 Dec 2020.
    3. Ryan Lemand, 2003. "Should Stock Market Indexes Time Varying Correlations Be Taken Into Account? A Conditional Variance Multivariate Approach," Econometrics 0307004, University Library of Munich, Germany, revised 07 Dec 2020.

  41. Marco J. Lombardi & Giampiero M. Gallo, 2002. "Analytic Hessian Matrices and the Computation of FIGARCH Estimates," Econometrics Working Papers Archive wp2002_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".

    Cited by:

    1. Li, Muyi & Li, Wai Keung & Li, Guodong, 2015. "A new hyperbolic GARCH model," Journal of Econometrics, Elsevier, vol. 189(2), pages 428-436.
    2. Massimiliano Caporin & Francesco Lisi, 2010. "Misspecification tests for periodic long memory GARCH models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 19(1), pages 47-62, March.
    3. Mateusz Tomal, 2021. "Modelling the Impact of Different COVID-19 Pandemic Waves on Real Estate Stock Returns and Their Volatility Using a GJR-GARCHX Approach: An International Perspective," JRFM, MDPI, vol. 14(8), pages 1-8, August.
    4. Kwan, Wilson & Li, Wai Keung & Li, Guodong, 2012. "On the estimation and diagnostic checking of the ARFIMA–HYGARCH model," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3632-3644.
    5. Charles, Amélie & Darné, Olivier, 2019. "The accuracy of asymmetric GARCH model estimation," International Economics, Elsevier, vol. 157(C), pages 179-202.

  42. Giampiero M. Gallo & Yongmiao Hong & Tae-Why Lee, 2001. "Modelling the Impact of Overnight Surprises on Intra-daily Stock Returns," Econometrics Working Papers Archive wp2001_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".

    Cited by:

    1. Jayawardena, Nirodha I. & Todorova, Neda & Li, Bin & Su, Jen-Je, 2020. "Volatility forecasting using related markets’ information for the Tokyo stock exchange," Economic Modelling, Elsevier, vol. 90(C), pages 143-158.
    2. Dimos S. Kambouroudis & David G. McMillan & Katerina Tsakou, 2021. "Forecasting realized volatility: The role of implied volatility, leverage effect, overnight returns, and volatility of realized volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(10), pages 1618-1639, October.
    3. Blanc, Pierre & Chicheportiche, Rémy & Bouchaud, Jean-Philippe, 2014. "The fine structure of volatility feedback II: Overnight and intra-day effects," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 402(C), pages 58-75.
    4. Insana, Alessandra, 2022. "Does systematic risk change when markets close? An analysis using stocks’ beta," Economic Modelling, Elsevier, vol. 109(C).
    5. Peter Reinhard Hansen & Asger Lunde, 2005. "A Realized Variance for the Whole Day Based on Intermittent High-Frequency Data," Journal of Financial Econometrics, Oxford University Press, vol. 3(4), pages 525-554.
    6. Nicholas Taylor, 2008. "The predictive value of temporally disaggregated volatility: evidence from index futures markets," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(8), pages 721-742.
    7. Ana-Maria Fuertes & Elena Kalotychou & Natasa Todorovic, 2015. "Daily volume, intraday and overnight returns for volatility prediction: profitability or accuracy?," Review of Quantitative Finance and Accounting, Springer, vol. 45(2), pages 251-278, August.
    8. Tong, Bin & Diao, Xundi & Wu, Chongfeng, 2015. "Modeling asymmetric and dynamic dependence of overnight and daytime returns: An empirical evidence from China Banking Sector," Economic Modelling, Elsevier, vol. 51(C), pages 366-382.
    9. Tseng-Chan Tseng & Hung-Cheng Lai & Cha-Fei Lin, 2012. "The impact of overnight returns on realized volatility," Applied Financial Economics, Taylor & Francis Journals, vol. 22(5), pages 357-364, March.
    10. 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.
    11. Dimos Kambouroudis & David McMillan & Katerina Tsakou, 2019. "Forecasting Realized Volatility: The role of implied volatility, leverage effect, overnight returns and volatility of realized volatility," Working Papers 2019-03, Swansea University, School of Management.

  43. Giampiero M. Gallo & Clive W.J. Granger & Yongil Jeon, 2001. "Copycats and Common Swings: the Impact of the Use of Forecasts in Information Sets," Econometrics Working Papers Archive wp2001_01, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".

    Cited by:

    1. Chia-Lin Chang & Bert de Bruijn & Philip Hans Franses & Michael McAleer, 2013. "Analyzing Fixed-event Forecast Revisions," Documentos de Trabajo del ICAE 2013-14, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico, revised Apr 2013.
    2. Cameron A. Shelton, 2007. "The Information Content of Elections and Varieties of the Partisan Political Business Cycle," Wesleyan Economics Working Papers 2007-003, Wesleyan University, Department of Economics.
    3. Isiklar, Gultekin & Lahiri, Kajal, 2007. "How far ahead can we forecast? Evidence from cross-country surveys," International Journal of Forecasting, Elsevier, vol. 23(2), pages 167-187.
    4. Dan Bernhardt & Murillo Campbello & Edward Kutsoati, 2002. "Who Herds?," Discussion Papers Series, Department of Economics, Tufts University 0213, Department of Economics, Tufts University.
    5. Dovern, Jonas & Fritsche, Ulrich & Loungani, Prakash & Tamirisa, Natalia, 2015. "Information rigidities: Comparing average and individual forecasts for a large international panel," International Journal of Forecasting, Elsevier, vol. 31(1), pages 144-154.
    6. de Mendonça, Helder Ferreira & Vereda, Luciano & Araujo, Mateus de Azevedo, 2022. "What type of information calls the attention of forecasters? Evidence from survey data in an emerging market," Journal of International Money and Finance, Elsevier, vol. 129(C).
    7. Michael P. Clements, 2018. "Do Macroforecasters Herd?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(2-3), pages 265-292, March.
    8. Michael P Clements, 2014. "Assessing the Evidence of Macro- Forecaster Herding: Forecasts of Inflation and Output Growth," ICMA Centre Discussion Papers in Finance icma-dp2014-12, Henley Business School, University of Reading.
    9. Michael Groemling, 2005. "Konjunkturprognosen – Verfahren, Erfolgskontrolle und Prognosefehler," Departmental Discussion Papers 123, University of Goettingen, Department of Economics.
    10. Ager, Philipp & Kappler, Marcus & Osterloh, Steffen, 2007. "The Accuracy and Efficiency of the Consensus Forecasts: A Further Application and Extension of the Pooled Approach," ZEW Discussion Papers 07-058, ZEW - Leibniz Centre for European Economic Research.
    11. Jonas Dovern & Mr. Ulrich Fritsche & Mr. Prakash Loungani & Ms. Natalia T. Tamirisa, 2013. "Information Rigidities in Economic Growth Forecasts: Evidence from a Large International Panel," IMF Working Papers 2013/056, International Monetary Fund.
    12. Lin, Mei-Chen, 2018. "The impact of aggregate uncertainty on herding in analysts' stock recommendations," International Review of Financial Analysis, Elsevier, vol. 57(C), pages 90-105.
    13. Stefan Günnel & Karl-Heinz Tödter, 2009. "Does Benford’s Law hold in economic research and forecasting?," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 36(3), pages 273-292, August.
    14. John B. Broughton & Bento J. Lobo, 2018. "Herding and anchoring in macroeconomic forecasts: the case of the PMI," Empirical Economics, Springer, vol. 55(3), pages 1337-1355, November.
    15. Meade, Nigel & Driver, Ciaran, 2023. "Differing behaviours of forecasters of UK GDP growth," International Journal of Forecasting, Elsevier, vol. 39(2), pages 772-790.
    16. Borgioli, Stefano & Gallo, Giampiero M. & Ongari, Chiara, 2024. "Financial returns, sentiment and market volatility. A dynamic assessment," Working Paper Series 2999, European Central Bank.
    17. Menz, Jan-Oliver & Poppitz, Philipp, 2013. "Households' disagreement on inflation expectations and socioeconomic media exposure in Germany," Discussion Papers 27/2013, Deutsche Bundesbank.
    18. Gultekin Isiklar & Kajal Lahiri & Prakash Loungani, 2006. "How quickly do forecasters incorporate news? Evidence from cross‐country surveys," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(6), pages 703-725, September.
    19. Yanwei Jia & Jussi Keppo & Ville Satopää, 2023. "Herding in Probabilistic Forecasts," Management Science, INFORMS, vol. 69(5), pages 2713-2732, May.
    20. Bruno Deschamps & Christos Ioannidis, 2014. "The Efficiency of Multivariate Macroeconomic Forecasts," Manchester School, University of Manchester, vol. 82(5), pages 509-523, September.
    21. Jonas Dovern & Johannes Weisser, 2009. "Accuracy, Unbiasedness and Efficiency of Professional Macroeconomic Forecasts: An empirical Comparison for the G7," Jena Economics Research Papers 2009-091, Friedrich-Schiller-University Jena.
    22. Reslow, André, 2019. "Inefficient Use of Competitors’ Forecasts?," Working Paper Series 2019:9, Uppsala University, Department of Economics.
    23. Döhrn, Roland, 2019. "Comparing forecast accuracy in small samples," Ruhr Economic Papers 833, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    24. Jonas Dovern & Ulrich Fritsche, 2008. "Estimating Fundamental Cross-Section Dispersion from Fixed Event Forecasts," Discussion Papers of DIW Berlin 787, DIW Berlin, German Institute for Economic Research.
    25. Kaminska, Iryna & Roberts-Sklar, Matt, 2017. "Volatility in equity markets and monetary policy rate uncertainty," Bank of England working papers 700, Bank of England.
    26. Jordi Pons-Novell, 2006. "An analysis of a panel of Spanish GDP forecasts," Applied Economics, Taylor & Francis Journals, vol. 38(11), pages 1287-1292.
    27. Bizer, Kilian & Meub, Lukas & Proeger, Till & Spiwoks, Markus, 2014. "Strategic coordination in forecasting: An experimental study," University of Göttingen Working Papers in Economics 195, University of Goettingen, Department of Economics.
    28. Deschamps, Bruno & Ioannidis, Christos & Ka, Kook, 2020. "High-frequency credit spread information and macroeconomic forecast revision," International Journal of Forecasting, Elsevier, vol. 36(2), pages 358-372.
    29. Rülke, Jan-Christoph & Silgoner, Maria & Wörz, Julia, 2016. "Herding behavior of business cycle forecasters," International Journal of Forecasting, Elsevier, vol. 32(1), pages 23-33.
    30. Dovern, Jonas, 2013. "When are GDP forecasts updated? Evidence from a large international panel," Economics Letters, Elsevier, vol. 120(3), pages 521-524.
    31. Yoichi Tsuchiya, 2021. "Crises, market shocks, and herding behavior in stock price forecasts," Empirical Economics, Springer, vol. 61(2), pages 919-945, August.
    32. Lahiri, Kajal & Sheng, Xuguang, 2008. "Evolution of forecast disagreement in a Bayesian learning model," Journal of Econometrics, Elsevier, vol. 144(2), pages 325-340, June.

  44. Giampiero M. Gallo, 2001. "Modelling the Impact of Overnight Surprises on Intra-daily Volatility," Econometrics Working Papers Archive wp2001_02, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".

    Cited by:

    1. Jayawardena, Nirodha I. & Todorova, Neda & Li, Bin & Su, Jen-Je, 2020. "Volatility forecasting using related markets’ information for the Tokyo stock exchange," Economic Modelling, Elsevier, vol. 90(C), pages 143-158.
    2. Massimiliano Caporin & Chia-Lin Chang & Michael McAleer, 2016. "Are the S&P 500 Index and Crude Oil, Natural Gas and Ethanol Futures Related for Intra-Day Data?," Documentos de Trabajo del ICAE 2016-01, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    3. Dimos S. Kambouroudis & David G. McMillan & Katerina Tsakou, 2021. "Forecasting realized volatility: The role of implied volatility, leverage effect, overnight returns, and volatility of realized volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(10), pages 1618-1639, October.
    4. Blanc, Pierre & Chicheportiche, Rémy & Bouchaud, Jean-Philippe, 2014. "The fine structure of volatility feedback II: Overnight and intra-day effects," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 402(C), pages 58-75.
    5. Insana, Alessandra, 2022. "Does systematic risk change when markets close? An analysis using stocks’ beta," Economic Modelling, Elsevier, vol. 109(C).
    6. Christian T. Brownlees & Giampiero Gallo, 2008. "Comparison of Volatility Measures: a Risk Management Perspective," Econometrics Working Papers Archive wp2008_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    7. Hiroki Masuda & Takayuki Morimoto, 2012. "Optimal Weight For Realized Variance Based On Intermittent High-Frequency Data," The Japanese Economic Review, Japanese Economic Association, vol. 63(4), pages 497-527, December.
    8. Peter Reinhard Hansen & Asger Lunde, 2005. "A Realized Variance for the Whole Day Based on Intermittent High-Frequency Data," Journal of Financial Econometrics, Oxford University Press, vol. 3(4), pages 525-554.
    9. Nicholas Taylor, 2008. "The predictive value of temporally disaggregated volatility: evidence from index futures markets," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(8), pages 721-742.
    10. Pierre Blanc & R'emy Chicheportiche & Jean-Philippe Bouchaud, 2013. "The fine structure of volatility feedback II: overnight and intra-day effects," Papers 1309.5806, arXiv.org, revised May 2014.
    11. Ana-Maria Fuertes & Elena Kalotychou & Natasa Todorovic, 2015. "Daily volume, intraday and overnight returns for volatility prediction: profitability or accuracy?," Review of Quantitative Finance and Accounting, Springer, vol. 45(2), pages 251-278, August.
    12. Tseng-Chan Tseng & Hung-Cheng Lai & Cha-Fei Lin, 2012. "The impact of overnight returns on realized volatility," Applied Financial Economics, Taylor & Francis Journals, vol. 22(5), pages 357-364, March.
    13. Christian T. Brownlees & Giampiero Gallo, 2007. "Volatility Forecasting Using Explanatory Variables and Focused Selection Criteria," Econometrics Working Papers Archive wp2007_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    14. 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.
    15. Yi-Hao Lai & Yi-Chiuan Wang & Yu-Ching Chang, 2024. "Forecasting Trading-Session Return Volatility in Taiwan Futures Market: A Periodic Regime Switching with Jump Approach," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 31(2), pages 285-305, June.
    16. Dimos Kambouroudis & David McMillan & Katerina Tsakou, 2019. "Forecasting Realized Volatility: The role of implied volatility, leverage effect, overnight returns and volatility of realized volatility," Working Papers 2019-03, Swansea University, School of Management.
    17. Todorova, Neda & Souček, Michael, 2014. "The impact of trading volume, number of trades and overnight returns on forecasting the daily realized range," Economic Modelling, Elsevier, vol. 36(C), pages 332-340.

  45. Edoardo Otranto & Giampiero M. Gallo, 2001. "A Nonparametric Bayesian Approach to Detect the Number of Regimes in Markov Switching Models," Econometrics Working Papers Archive wp2001_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".

    Cited by:

    1. Bruno Giancarlo & Edoardo Otranto, 2004. "Dating the Italian BUsiness Cycle: A Comparison of Procedures," ISAE Working Papers 41, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
    2. Alessandro Rossi & Giampiero M. Gallo, 2002. "Volatility Estimation via Hidden Markov Models," Econometrics Working Papers Archive wp2002_14, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    3. Christina Erlwein & Rogemar Mamon, 2009. "An online estimation scheme for a Hull–White model with HMM-driven parameters," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 18(1), pages 87-107, March.
    4. Roberta Colavecchio & Michael Funke, 2007. "Volatility dependence across Asia-Pacific on-shore and off-shore U.S. dollar futures markets," Quantitative Macroeconomics Working Papers 20708, Hamburg University, Department of Economics.
    5. Gallo, Giampiero M. & Otranto, Edoardo, 2015. "Forecasting realized volatility with changing average levels," International Journal of Forecasting, Elsevier, vol. 31(3), pages 620-634.
    6. Giampiero M. Gallo & Edoardo Otranto, 2007. "Volatility transmission across markets: a Multichain Markov Switching model," Applied Financial Economics, Taylor & Francis Journals, vol. 17(8), pages 659-670.
    7. Julyan Arbel & Riccardo Corradin & Bernardo Nipoti, 2021. "Dirichlet process mixtures under affine transformations of the data," Computational Statistics, Springer, vol. 36(1), pages 577-601, March.
    8. I.Fatnassi & S.Chawechi & Z.Ftiti & A.Ben Maatoug, 2014. "Effects of Monetary Policy on the REIT Returns," Working Papers 2014-63, Department of Research, Ipag Business School.
    9. E. Otranto, 2011. "Classification of Volatility in Presence of Changes in Model Parameters," Working Paper CRENoS 201113, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    10. Roberta Colavecchio & Michael Funke, 2009. "Volatility Dependence across Asia-Pacific Onshore and Offshore Currency Forwards Markets," Working Papers 112009, Hong Kong Institute for Monetary Research.
    11. Otranto, Edoardo, 2006. "Modelling the discrete and infrequent official interest rate change in the UK," DES - Working Papers. Statistics and Econometrics. WS ws062007, Universidad Carlos III de Madrid. Departamento de Estadística.
    12. Federico Bassetti & Roberto Casarin & Fabrizio Leisen, 2013. "Beta-Product Dependent Pitman-Yor Processes for Bayesian Inference," Working Papers 2013:13, Department of Economics, University of Venice "Ca' Foscari".
    13. 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.
    14. Bäuerle Nicole & Gilitschenski Igor & Hanebeck Uwe, 2015. "Exact and approximate hidden Markov chain filters based on discrete observations," Statistics & Risk Modeling, De Gruyter, vol. 32(3-4), pages 159-176, December.
    15. Yong Song, 2014. "Modelling Regime Switching And Structural Breaks With An Infinite Hidden Markov Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(5), pages 825-842, August.
    16. Bruno, Giancarlo & Otranto, Edoardo, 2008. "Models to date the business cycle: The Italian case," Economic Modelling, Elsevier, vol. 25(5), pages 899-911, September.
    17. Silvestro Di Sanzo, 2009. "Testing for linearity in Markov switching models: a bootstrap approach," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 18(2), pages 153-168, July.
    18. L. Scaffidi Domianello & E. Otranto, 2023. "On the relationship between Markov Switching inference and Fuzzy Clustering: A Monte Carlo evidence," Working Paper CRENoS 202304, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    19. Giampiero M. Gallo & Edoardo Otranto, 2014. "Forecasting Realized Volatility with Changes of Regimes," Econometrics Working Papers Archive 2014_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Feb 2014.
    20. Giampiero M. Gallo & Edoardo Otranto, 2018. "Combining sharp and smooth transitions in volatility dynamics: a fuzzy regime approach," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(3), pages 549-573, April.
    21. Nicole Bauerle & Igor Gilitschenski & Uwe D. Hanebeck, 2014. "Exact and Approximate Hidden Markov Chain Filters Based on Discrete Observations," Papers 1411.0849, arXiv.org, revised Dec 2014.
    22. Edoardo Otranto, 2005. "The multi-chain Markov switching model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(7), pages 523-537.
    23. JdD Tena & E. Otranto, 2008. "A Realistic Model for Official Interest Rates," Working Paper CRENoS 200802, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    24. Fatnassi, Ibrahim & Slim, Chaouachi & Ftiti, Zied & Ben Maatoug, Abderrazek, 2014. "Effects of monetary policy on the REIT returns: Evidence from the United Kingdom," Research in International Business and Finance, Elsevier, vol. 32(C), pages 15-26.
    25. Yong Song & Tomasz Wo'zniak, 2020. "Markov Switching," Papers 2002.03598, arXiv.org.

  46. Gallo, Giampiero M. & Granger, Clive W.J. & Jeon, Yongil, 1999. "The Impact of the Use of Forecasts in Information Sets," University of California at San Diego, Economics Working Paper Series qt1w33d4b2, Department of Economics, UC San Diego.

    Cited by:

    1. Loungani, Prakash, 2001. "How accurate are private sector forecasts? Cross-country evidence from consensus forecasts of output growth," International Journal of Forecasting, Elsevier, vol. 17(3), pages 419-432.
    2. Dovern, Jonas & Fritsche, Ulrich & Loungani, Prakash & Tamirisa, Natalia, 2015. "Information rigidities: Comparing average and individual forecasts for a large international panel," International Journal of Forecasting, Elsevier, vol. 31(1), pages 144-154.
    3. Jonas Dovern & Mr. Ulrich Fritsche & Mr. Prakash Loungani & Ms. Natalia T. Tamirisa, 2013. "Information Rigidities in Economic Growth Forecasts: Evidence from a Large International Panel," IMF Working Papers 2013/056, International Monetary Fund.
    4. Jonathan B. Cohn & Jennifer L. Juergens, 2014. "How Much Do Analysts Influence Each Other's Forecasts?," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 4(03), pages 1-35.
    5. Alfredo Pistelli M., 2012. "Análisis de Sesgos y Eficiencia en Proyecciones de Consensus Forecasts," Notas de Investigación Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 15(1), pages 98-104, April.
    6. Blanca Moreno & Ana Jesus Lopez, 2007. "Combining economic forecasts through information measures," Applied Economics Letters, Taylor & Francis Journals, vol. 14(12), pages 899-903.
    7. Granger, Clive W. J. & Jeon, Yongil, 2004. "Thick modeling," Economic Modelling, Elsevier, vol. 21(2), pages 323-343, March.
    8. Krekó, Judit & Vonnák, Balázs, 2003. "Makroelemzők inflációs várakozásai Magyarországon [The inflationary expectations of macro analysts in Hungary]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(4), pages 315-334.

  47. Gallo, G.M. & Pacini, B., 1998. "Early News Is Good News. The Effects of Market Opening on Market Volatility," Economics Working Papers eco98/3, European University Institute.

    Cited by:

    1. Beatriz Vaz de Melo Mendes & Victor Bello Accioly, 2017. "Improving (E)GARCH forecasts with robust realized range measures: Evidence from international markets," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 41(4), pages 631-658, October.
    2. Qi Zhang & Charlie X Cai & Kevin Keasey, 2009. "Forecasting using high-frequency data: a comparison of asymmetric financial duration models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(5), pages 371-386.
    3. Giampiero M. Gallo, 2001. "Modelling the Impact of Overnight Surprises on Intra‐daily Volatility," Australian Economic Papers, Wiley Blackwell, vol. 40(4), pages 567-580, December.
    4. Paola Zuccolotto, 2002. "Modelling the impact of open volume on inter-trade autoregressive durations," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3-4), pages 49-63.
    5. Li, Gang & Li, Yong, 2015. "Forecasting copper futures volatility under model uncertainty," Resources Policy, Elsevier, vol. 46(P2), pages 167-176.
    6. Janina Ketterer, 2012. "The Impact of Wind Power Generation on the Electricity Price in Germany," ifo Working Paper Series 143, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    7. Chen, Chun-Hung & Yu, Wei-Choun & Zivot, Eric, 2012. "Predicting stock volatility using after-hours information: Evidence from the NASDAQ actively traded stocks," International Journal of Forecasting, Elsevier, vol. 28(2), pages 366-383.
    8. Giampiero M. Gallo & Yongmiao Hong & Tae-Why Lee, 2001. "Modelling the Impact of Overnight Surprises on Intra-daily Stock Returns," Econometrics Working Papers Archive wp2001_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    9. Victor Bello Accioly & Beatriz Vaz de Melo Mendes, 2016. "Assessing the Impact of the Realized Range on the (E)GARCH Volatility: Evidence from Brazil," Brazilian Business Review, Fucape Business School, vol. 13(2), pages 1-26, March.

  48. Renzo G. Avesani & Giampiero M. Gallo, 1991. "Jumping in the Band: Undeclared Intervention Thresholds in a Target Zone," Department of Economics Working Papers 9104, Department of Economics, University of Trento, Italia.

    Cited by:

    1. Maurizio Pugno, 2004. "Rationality and affective motivation: new ideas from neurobiology and psychiatry for economic theory," Department of Economics Working Papers 0401B, Department of Economics, University of Trento, Italia.
    2. Sandun Perera & Winston Buckley, 2017. "On the existence and uniqueness of the optimal central bank intervention policy in a forex market with jumps," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(8), pages 877-885, August.

  49. Giampiero M. Gallo & Massimiliano Marcellino, "undated". "Ex Post and Ex Ante Analysis of Provisional Data," Working Papers 141, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.

    Cited by:

    1. Andres Fernandez & Norman R. Swanson, 2009. "Real-time datasets really do make a difference: definitional change, data release, and forecasting," Working Papers 09-28, Federal Reserve Bank of Philadelphia.
    2. Fabio Busetti, 2006. "Preliminary data and econometric forecasting: an application with the Bank of Italy Quarterly Model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(1), pages 1-23.
    3. Jacobs, Jan P.A.M. & van Norden, Simon, 2011. "Modeling data revisions: Measurement error and dynamics of "true" values," Journal of Econometrics, Elsevier, vol. 161(2), pages 101-109, April.

Articles

  1. Cipollini, Fabrizio & Gallo, Giampiero M., 2025. "Multiplicative Error Models: 20 years on," Econometrics and Statistics, Elsevier, vol. 33(C), pages 209-229.
    See citations under working paper version above.
  2. 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).
    See citations under working paper version above.
  3. Demetrio Lacava & Giampiero M. Gallo & Edoardo Otranto, 2022. "Unconventional policies effects on stock market volatility: The MAP approach," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(5), pages 1245-1265, November.
    See citations under working paper version above.
  4. Cipollini, Fabrizio & Gallo, Giampiero M. & Palandri, Alessandro, 2021. "A dynamic conditional approach to forecasting portfolio weights," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1111-1126.

    Cited by:

    1. Vincenzo Candila, 2021. "Multivariate Analysis of Cryptocurrencies," Econometrics, MDPI, vol. 9(3), pages 1-17, July.
    2. Xu, Peng, 2024. "Testing out-of-sample portfolio performance using second-order stochastic dominance constrained optimization approach," International Review of Financial Analysis, Elsevier, vol. 95(PA).

  5. Cipollini, Fabrizio & Gallo, Giampiero M. & Otranto, Edoardo, 2021. "Realized volatility forecasting: Robustness to measurement errors," International Journal of Forecasting, Elsevier, vol. 37(1), pages 44-57.
    See citations under working paper version above.
  6. 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.

    Cited by:

    1. Vincenzo Candila & Oguzhan Cepni & Giampiero M. Gallo & Rangan Gupta, 2024. "Influence of Local and Global Economic Policy Uncertainty on the Volatility of US State-Level Equity Returns: Evidence from a GARCH-MIDAS Approach with Shrinkage and Cluster Analysis," Working Papers 202437, University of Pretoria, Department of Economics.
    2. Weiß, Christian H. & Ruiz Marín, Manuel & Keller, Karsten & Matilla-García, Mariano, 2022. "Non-parametric analysis of serial dependence in time series using ordinal patterns," Computational Statistics & Data Analysis, Elsevier, vol. 168(C).
    3. Li, Wei & Zhang, Junchao & Cao, Xiangye & Han, Wei, 2024. "Is the prediction of precious metal market volatility influenced by internet searches regarding uncertainty?," Finance Research Letters, Elsevier, vol. 62(PB).
    4. 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.
    5. 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.
    6. Haohua Li & Elie Bouri & Rangan Gupta & Libing Fang, 2023. "Return Volatility, Correlation, and Hedging of Green and Brown Stocks: Is there a Role for Climate Risk Factors?," Working Papers 202301, University of Pretoria, Department of Economics.

  7. 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.

    Cited by:

    1. Md Samsul Alam & Alessandra Amendola & Vincenzo Candila & Shahram Dehghan Jabarabadi, 2024. "Is Monetary Policy a Driver of Cryptocurrencies? Evidence from a Structural Break GARCH-MIDAS Approach," Econometrics, MDPI, vol. 12(1), pages 1-20, January.
    2. 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.

  8. Luca Cattivelli & Giampiero M. Gallo, 2020. "Adaptive Lasso for vector Multiplicative Error Models," Quantitative Finance, Taylor & Francis Journals, vol. 20(2), pages 255-274, February.

    Cited by:

    1. Fabrizio Cipollini & Giampiero M. Gallo & Edoardo Otranto, 2019. "Realized Volatility Forecasting: Robustness to Measurement Errors," Econometrics Working Papers Archive 2019_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    2. Fabrizio Cipollini & Giampiero M. Gallo, 2021. "Multiplicative Error Models: 20 years on," Papers 2107.05923, arXiv.org.
    3. Alessandra Amendola & Vincenzo Candila & Fabrizio Cipollini & Giampiero M. Gallo, 2020. "Doubly Multiplicative Error Models with Long- and Short-run Components," Papers 2006.03458, arXiv.org.

  9. 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.

    Cited by:

    1. 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).
    2. Xiafei Li & Dongxin Li & Xuhui Zhang & Guiwu Wei & Lan Bai & Yu Wei, 2021. "Forecasting regular and extreme gold price volatility: The roles of asymmetry, extreme event, and jump," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1501-1523, December.
    3. Oscar V. De la Torre-Torres & Evaristo Galeana-Figueroa & José Álvarez-García, 2020. "Markov-Switching Stochastic Processes in an Active Trading Algorithm in the Main Latin-American Stock Markets," Mathematics, MDPI, vol. 8(6), pages 1-23, June.
    4. Yu Wei & Lan Bai & Kun Yang & Guiwu Wei, 2021. "Are industry‐level indicators more helpful to forecast industrial stock volatility? Evidence from Chinese manufacturing purchasing managers index," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 17-39, January.
    5. Marco Tronzano, 2021. "Financial Crises, Macroeconomic Variables, and Long-Run Risk: An Econometric Analysis of Stock Returns Correlations (2000 to 2019)," JRFM, MDPI, vol. 14(3), pages 1-25, March.
    6. Alessandra Amendola & Vincenzo Candila & Fabrizio Cipollini & Giampiero M. Gallo, 2020. "Doubly Multiplicative Error Models with Long- and Short-run Components," Papers 2006.03458, arXiv.org.
    7. Oscar V. De la Torre-Torres & Francisco Venegas-Martínez & Mᵃ Isabel Martínez-Torre-Enciso, 2021. "Enhancing Portfolio Performance and VIX Futures Trading Timing with Markov-Switching GARCH Models," Mathematics, MDPI, vol. 9(2), pages 1-22, January.
    8. Mila Andreani & Vincenzo Candila & Giacomo Morelli & Lea Petrella, 2021. "Multivariate Analysis of Energy Commodities during the COVID-19 Pandemic: Evidence from a Mixed-Frequency Approach," Risks, MDPI, vol. 9(8), pages 1-20, August.
    9. Yu-Hui Liao & Yeong-Jia Goo, 2019. "Do Higher Asymmetry Threshold Effects Exist on the Gold Return Volatility during Highly Fluctuating Periods?," Sustainability, MDPI, vol. 11(18), pages 1-14, September.
    10. Pan, Beier, 2023. "The asymmetric dynamics of stock–bond liquidity correlation in China: The role of macro-financial determinants," Economic Modelling, Elsevier, vol. 124(C).
    11. Vincenzo Candila, 2021. "Multivariate Analysis of Cryptocurrencies," Econometrics, MDPI, vol. 9(3), pages 1-17, July.
    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. Vincenzo Candila & Salvatore Farace, 2018. "On the Volatility Spillover between Agricultural Commodities and Latin American Stock Markets," Risks, MDPI, vol. 6(4), pages 1-16, October.

  10. Cipollini, Fabrizio & Gallo, Giampiero M., 2019. "Modeling Euro STOXX 50 volatility with common and market-specific components," Econometrics and Statistics, Elsevier, vol. 11(C), pages 22-42.
    See citations under working paper version above.
  11. Giampiero M. Gallo & Edoardo Otranto, 2018. "Combining sharp and smooth transitions in volatility dynamics: a fuzzy regime approach," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(3), pages 549-573, April.
    See citations under working paper version above.
  12. Giovanni De Luca & Giampiero M. Gallo & Danilo Carità, 2017. "Evaluating Combined Forecasts for Realized Volatility Using Asymmetric Loss Functions," Econometric Research in Finance, SGH Warsaw School of Economics, Collegium of Economic Analysis, vol. 2(2), pages 99-111, December.

    Cited by:

    1. Perera, Indeewara & Silvapulle, Mervyn J., 2021. "Bootstrap based probability forecasting in multiplicative error models," Journal of Econometrics, Elsevier, vol. 221(1), pages 1-24.

  13. Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2017. "Copula–Based vMEM Specifications versus Alternatives: The Case of Trading Activity," Econometrics, MDPI, vol. 5(2), pages 1-24, April.
    See citations under working paper version above.
  14. Gallo, Giampiero M. & Otranto, Edoardo, 2015. "Forecasting realized volatility with changing average levels," International Journal of Forecasting, Elsevier, vol. 31(3), pages 620-634.

    Cited by:

    1. G.M. Gallo & D. Lacava & E. Otranto, 2020. "On Classifying the Effects of Policy Announcements on Volatility," Working Paper CRENoS 202008, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    2. Cavicchioli, Maddalena, 2017. "Asymptotic Fisher information matrix of Markov switching VARMA models," Journal of Multivariate Analysis, Elsevier, vol. 157(C), pages 124-135.
    3. Arnaud Dufays & Jeroen V. K. Rombouts, 2019. "Sparse Change-point HAR Models for Realized Variance," Econometric Reviews, Taylor & Francis Journals, vol. 38(8), pages 857-880, September.
    4. Bauwens, Luc & Otranto, Edoardo, 2020. "Nonlinearities and regimes in conditional correlations with different dynamics," LIDAM Reprints CORE 3128, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    5. Demetrio Lacava & Luca Scaffidi Domianello, 2021. "The Incidence of Spillover Effects during the Unconventional Monetary Policies Era," JRFM, MDPI, vol. 14(6), pages 1-18, May.
    6. Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2017. "Copula-based vMEM Specifications versus Alternatives: The Case of Trading Activity," Econometrics Working Papers Archive 2017_02, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    7. Thomas Chuffart, 2013. "Selection Criteria in Regime Switching Conditional Volatility Models," AMSE Working Papers 1339, Aix-Marseille School of Economics, France, revised 14 Jul 2013.
    8. Fabrizio Cipollini & Giampiero M. Gallo & Edoardo Otranto, 2019. "Realized Volatility Forecasting: Robustness to Measurement Errors," Econometrics Working Papers Archive 2019_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    9. E. Otranto, 2015. "Adding Flexibility to Markov Switching Models," Working Paper CRENoS 201509, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    10. Xu, Yongdeng, 2022. "The Exponential HEAVY Model: An Improved Approach to Volatility Modeling and Forecasting," Cardiff Economics Working Papers E2022/5, Cardiff University, Cardiff Business School, Economics Section.
    11. Bartoš, Erik & Pinčák, Richard, 2017. "Identification of market trends with string and D2-brane maps," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 57-70.
    12. Caporin, Massimiliano & Rossi, Eduardo & Santucci de Magistris, Paolo, 2017. "Chasing volatility," Journal of Econometrics, Elsevier, vol. 198(1), pages 122-145.
    13. Fabrizio Cipollini & Giampiero M. Gallo, 2021. "Multiplicative Error Models: 20 years on," Papers 2107.05923, arXiv.org.
    14. Naimoli, Antonio & Storti, Giuseppe, 2019. "Heterogeneous component multiplicative error models for forecasting trading volumes," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1332-1355.
    15. Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2016. "Copula--based Specification of vector MEMs," Econometrics Working Papers Archive 2016_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    16. Arnaud Dufays & Maciej Augustyniak & Luc Bauwens, 2016. "A new approach to volatility modeling: the High-Dimensional Markov model," Cahiers de recherche 1609, Centre de recherche sur les risques, les enjeux économiques, et les politiques publiques.
    17. Alessandra Amendola & Vincenzo Candila & Fabrizio Cipollini & Giampiero M. Gallo, 2020. "Doubly Multiplicative Error Models with Long- and Short-run Components," Papers 2006.03458, arXiv.org.
    18. Liu, Guangqiang & Wei, Yu & Chen, Yongfei & Yu, Jiang & Hu, Yang, 2018. "Forecasting the value-at-risk of Chinese stock market using the HARQ model and extreme value theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 288-297.
    19. Zhipeng, Yan & Shenghong, Li, 2018. "Hedge ratio on Markov regime-switching diagonal Bekk–Garch model," Finance Research Letters, Elsevier, vol. 24(C), pages 49-55.
    20. 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.
    21. Richard D. F. Harris & Murat Mazibas, 2022. "A component Markov regime‐switching autoregressive conditional range model," Bulletin of Economic Research, Wiley Blackwell, vol. 74(2), pages 650-683, April.
    22. Tapia, Sebastian & Kristjanpoller, Werner, 2022. "Framework based on multiplicative error and residual analysis to forecast bitcoin intraday-volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 589(C).
    23. Giampiero M. Gallo & Edoardo Otranto, 2018. "Combining sharp and smooth transitions in volatility dynamics: a fuzzy regime approach," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(3), pages 549-573, April.
    24. Lu, Botao & Ma, Feng & Wang, Jiqian & Ding, Hui & Wahab, M.I.M., 2021. "Harnessing the decomposed realized measures for volatility forecasting: Evidence from the US stock market," International Review of Economics & Finance, Elsevier, vol. 72(C), pages 672-689.
    25. Wang, Jiqian & Huang, Yisu & Ma, Feng & Chevallier, Julien, 2020. "Does high-frequency crude oil futures data contain useful information for predicting volatility in the US stock market? New evidence," Energy Economics, Elsevier, vol. 91(C).
    26. Yuan, Ying & Zhang, Tonghui, 2020. "Forecasting stock market in high and low volatility periods: a modified multifractal volatility approach," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
    27. Liu, Guangqiang & Wang, Yan & Chen, Xiaodan & Zhang, Yifeng & Shang, Yue, 2020. "Forecasting volatility of the Chinese stock markets using TVP HAR-type models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    28. Maria Ghani & Feng Ma & Dengshi Huang, 2024. "Forecasting the Asian stock market volatility: Evidence from WTI and INE oil futures," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(2), pages 1496-1512, April.
    29. Giampiero M. Gallo & Edoardo Otranto, 2016. "Combining Markov Switching and Smooth Transition in Modeling Volatility: A Fuzzy Regime MEM," Econometrics Working Papers Archive 2016_02, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".

  15. Barigozzi, Matteo & Brownlees, Christian & Gallo, Giampiero M. & Veredas, David, 2014. "Disentangling systematic and idiosyncratic dynamics in panels of volatility measures," Journal of Econometrics, Elsevier, vol. 182(2), pages 364-384.
    See citations under working paper version above.
  16. Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2013. "Semiparametric Vector Mem," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(7), pages 1067-1086, November.
    See citations under working paper version above.
  17. Robert F. Engle & Giampiero M. Gallo & Margherita Velucchi, 2012. "Volatility Spillovers in East Asian Financial Markets: A Mem-Based Approach," The Review of Economics and Statistics, MIT Press, vol. 94(1), pages 222-223, February.

    Cited by:

    1. Faruk, Balli & Syed Abul, Basher & Hassan, Ghassan & Hassan, Hajhoj, 2015. "An Analysis of Returns and Volatility Spillovers and their Determinants in Emerging Asian and Middle Eastern Countries," MPRA Paper 63847, University Library of Munich, Germany.
    2. Fei Su & Lili Zhai & Yunyan Zhou & Zixi Zhuang & Feifan Wang, 2024. "Risk contagion in financial markets: A systematic review using bibliometric methods," Australian Economic Papers, Wiley Blackwell, vol. 63(1), pages 163-199, March.
    3. Fabrizio Cipollini & Giampiero Gallo & Andrea Ugolini, 2016. "Median Response to Shocks: A Model for VaR Spillovers in East Asia," Econometrics Working Papers Archive 2016_01, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    4. Huo, Rui & Ahmed, Abdullahi D., 2017. "Return and volatility spillovers effects: Evaluating the impact of Shanghai-Hong Kong Stock Connect," Economic Modelling, Elsevier, vol. 61(C), pages 260-272.
    5. Luintel, Kul B & Xu, Yongdeng, 2013. "Testing weak exogeneity in multiplicative error models," Cardiff Economics Working Papers E2013/6, Cardiff University, Cardiff Business School, Economics Section.
    6. Suraj Kumar & Krishna Prasanna, 2019. "Global Financial Crisis: Dynamics of Liquidity Risk in Emerging Asia," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 18(3), pages 339-362, December.
    7. Ellington, Michael, 2022. "Fat tails, serial dependence, and implied volatility index connections," European Journal of Operational Research, Elsevier, vol. 299(2), pages 768-779.
    8. Xu, Yongdeng & Taylor, Nick & Lu, Wenna, 2018. "Illiquidity and volatility spillover effects in equity markets during and after the global financial crisis: An MEM approach," International Review of Financial Analysis, Elsevier, vol. 56(C), pages 208-220.
    9. Guan, Bo & Mazouz, Khelifa & Xu, Yongdeng, 2023. "Asymmetric volatility spillover between crude oil and other asset markets," Cardiff Economics Working Papers E2023/27, Cardiff University, Cardiff Business School, Economics Section.
    10. Demetrio Lacava & Luca Scaffidi Domianello, 2021. "The Incidence of Spillover Effects during the Unconventional Monetary Policies Era," JRFM, MDPI, vol. 14(6), pages 1-18, May.
    11. Zhang, Xingmin & Zhang, Shuai & Lu, Liping, 2022. "The banking instability and climate change: Evidence from China," Energy Economics, Elsevier, vol. 106(C).
    12. Xu, Yongdeng & Guan, Bo & Lu, Wenna & Heravi, Saeed, 2024. "Macroeconomic shocks and volatility spillovers between stock, bond, gold and crude oil markets," Energy Economics, Elsevier, vol. 136(C).
    13. Matteo Barigozzi & Christian T. Brownlees, 2013. "Nets: Network estimation for time series," Economics Working Papers 1391, Department of Economics and Business, Universitat Pompeu Fabra.
    14. Khalifa, Ahmed A. & Alsarhan, Abdulwahab A. & Bertuccelli, Pietro, 2017. "Causes and consequences of energy price shocks on petroleum-based stock market using the spillover asymmetric multiplicative error model," Research in International Business and Finance, Elsevier, vol. 39(PA), pages 307-314.
    15. Afonso, António & Gomes, Pedro & Taamouti, Abderrahim, 2014. "Sovereign credit ratings, market volatility, and financial gains," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 20-33.
    16. Dimitrios P. Louzis, 2013. "Measuring return and volatility spillovers in euro area financial markets," Working Papers 154, Bank of Greece.
    17. Camille Baulant & Nivine Albouz, 2021. "Has financial globalization since 1990 reduced income inequality: the role of rating announcements on the volatility and the returns of the Brazilian Financial Market [Les annonces de notation souv," Working Papers hal-03258994, HAL.
    18. Murat Akkaya, 2021. "An Analysis of the Stock Market Volatility Spread in Emerging Countries," Istanbul Business Research, Istanbul University Business School, vol. 50(2), pages 215-233, November.
    19. Donelli, Nicola & Peluso, Stefano & Mira, Antonietta, 2021. "A Bayesian semiparametric vector Multiplicative Error Model," Computational Statistics & Data Analysis, Elsevier, vol. 161(C).
    20. Baruník, Jozef & Bevilacqua, Mattia & Tunaru, Radu, 2022. "Asymmetric network connectedness of fears," LSE Research Online Documents on Economics 108199, London School of Economics and Political Science, LSE Library.
    21. Timothy Krause & Sina Ehsani & Donald Lien, 2014. "Exchange-traded funds, liquidity and volatility," Applied Financial Economics, Taylor & Francis Journals, vol. 24(24), pages 1617-1630, December.
    22. Alexander Karmann & Rodrigo Herrera, 2014. "Special Issue: Issues in Asia. Guest Editor: Laixun Zhao," Review of Development Economics, Wiley Blackwell, vol. 18(2), pages 354-371, May.
    23. Christian T. Brownlees & Fabrizio Cipollini & Giampiero M. Gallo, 2011. "Multiplicative Error Models," Econometrics Working Papers Archive 2011_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Apr 2011.
    24. Antonios K. Alexandridis & Mohammad S. Hasan, 2020. "Global financial crisis and multiscale systematic risk: Evidence from selected European stock markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 25(4), pages 518-546, October.
    25. Yarovaya, Larisa & Brzeszczyński, Janusz & Goodell, John W. & Lucey, Brian & Lau, Chi Keung Marco, 2022. "Rethinking financial contagion: Information transmission mechanism during the COVID-19 pandemic," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
    26. Jozef Barunik & Tomas Krehlik, 2015. "Measuring the frequency dynamics of financial connectedness and systemic risk," Papers 1507.01729, arXiv.org, revised Dec 2017.
    27. Fabrizio Cipollini & Giampiero M. Gallo, 2021. "Multiplicative Error Models: 20 years on," Papers 2107.05923, arXiv.org.
    28. Nishimura, Yusaku & Sun, Bianxia, 2018. "The intraday volatility spillover index approach and an application in the Brexit vote," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 55(C), pages 241-253.
    29. Zheng, Tingguo & Zuo, Haomiao, 2013. "Reexamining the time-varying volatility spillover effects: A Markov switching causality approach," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 643-662.
    30. Dimitrios Louzis, 2015. "Measuring spillover effects in Euro area financial markets: a disaggregate approach," Empirical Economics, Springer, vol. 49(4), pages 1367-1400, December.
    31. Usman M. Umer, Metin Coskun, Kasim Kiraci, 2018. "Time-varying Return and Volatility Spillover among EAGLEs Stock Markets: A Multivariate GARCH Analysis," Journal of Finance and Economics Research, Geist Science, Iqra University, Faculty of Business Administration, vol. 3(1), pages 23-42, March.
    32. Golosnoy, Vasyl & Gribisch, Bastian & Liesenfeld, Roman, 2012. "Intra-daily volatility spillovers between the US and German stock markets," Economics Working Papers 2012-06, Christian-Albrechts-University of Kiel, Department of Economics.
    33. Clements, A.E. & Hurn, A.S. & Volkov, V.V., 2015. "Volatility transmission in global financial markets," Journal of Empirical Finance, Elsevier, vol. 32(C), pages 3-18.
    34. Imran Yousaf & Shoaib Ali & Wing-Keung Wong, 2020. "An Empirical Analysis of the Volatility Spillover Effect between World-Leading and the Asian Stock Markets: Implications for Portfolio Management," JRFM, MDPI, vol. 13(10), pages 1-28, September.
    35. Bales, Kyle & Malikane, Christopher, 2020. "The effect of credit ratings on emerging market volatility," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 65(C).
    36. Gilles de Truchis & Benjamin Keddad, 2013. "Analyzing Financial Integration in East Asia through Fractional Cointegration in Volatilities," AMSE Working Papers 1346, Aix-Marseille School of Economics, France, revised Sep 2013.
    37. Gomez-Gonzalez, Jose E. & Rojas-Espinosa, Wilmer, 2019. "Detecting contagion in Asian exchange rate markets using asymmetric DCC-GARCH and R-vine copulas," Economic Systems, Elsevier, vol. 43(3).
    38. Cipollini, Fabrizio & Gallo, Giampiero M., 2010. "Automated variable selection in vector multiplicative error models," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2470-2486, November.
    39. Marcel Aloy & Gilles de Truchis & Gilles Dufrénot & Benjamin Keddad, 2014. "Shift-Volatility Transmission in East Asian Equity Markets," AMSE Working Papers 1402, Aix-Marseille School of Economics, France, revised Mar 2014.
    40. António Afonso & João Tovar Jalles, 2020. "Economic volatility and sovereign yields’ determinants: a time-varying approach," Empirical Economics, Springer, vol. 58(2), pages 427-451, February.
    41. Rajni Kant Rajhans & Anuradha Jain, 2015. "Volatility Spillover in Foreign Exchange Markets," Paradigm, , vol. 19(2), pages 137-151, December.
    42. Lien, Donald & Lee, Geul & Yang, Li & Zhang, Yuyin, 2018. "Volatility spillovers among the U.S. and Asian stock markets: A comparison between the periods of Asian currency crisis and subprime credit crisis," The North American Journal of Economics and Finance, Elsevier, vol. 46(C), pages 187-201.
    43. Yang, Zihui & Zhou, Yinggang, 2018. "Systemic Risk in Global Volatility Spillover Networks: Evidence from Option-implied Volatility Indices," IRTG 1792 Discussion Papers 2018-003, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    44. Gilles de Truchis & Benjamin Keddad, 2016. "Long-Run Comovements in East Asian Stock Market Volatility," Post-Print hal-01549713, HAL.
    45. Cipollini, Fabrizio & Gallo, Giampiero M., 2019. "Modeling Euro STOXX 50 volatility with common and market-specific components," Econometrics and Statistics, Elsevier, vol. 11(C), pages 22-42.
    46. Barunik, Jozef & Krehlik, Tomas, 2016. "Measuring the frequency dynamics of financial and macroeconomic connectedness," FinMaP-Working Papers 54, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    47. Nicholas Taylor, 2015. "Realized volatility forecasting in an international context," Applied Economics Letters, Taylor & Francis Journals, vol. 22(6), pages 503-509, April.
    48. Zhou, Wei & Chen, Yan & Chen, Jin, 2024. "Dynamic volatility spillover and market emergency: Matching and forecasting," The North American Journal of Economics and Finance, Elsevier, vol. 71(C).
    49. Apostolou, Apostolos & Beirne, John, 2019. "Volatility spillovers of unconventional monetary policy to emerging market economies," Economic Modelling, Elsevier, vol. 79(C), pages 118-129.
    50. Hafner, C. M., 2022. "Dynamic Autoregressive Liquidity (DArLiQ)," Janeway Institute Working Papers 2206, Faculty of Economics, University of Cambridge.
    51. Sohel Azad, A.S.M. & Batten, Jonathan A. & Fang, Victor & Wickramanayake, Jayasinghe, 2015. "International swap market contagion and volatility," Economic Modelling, Elsevier, vol. 47(C), pages 355-371.
    52. Gomez-Gonzalez, Jose & Rojas-Espinosa, Wilmer, 2018. "Detecting exchange rate contagion in Asian exchange rate markets using asymmetric DDC-GARCH and R-vine copulas," MPRA Paper 88578, University Library of Munich, Germany.
    53. Roni Bhowmik & Abbas Ghulam & Wang Shouyang, 2018. "Return and Volatility Spillovers Effects: Study of Asian Emerging Stock Markets," Journal of Systems Science and Information, De Gruyter, vol. 6(2), pages 97-119, April.
    54. Giampiero M. Gallo & Edoardo Otranto, 2012. "Volatility Swings in the US Financial Markets," Econometrics Working Papers Archive 2012_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Jul 2012.
    55. Iwanicz-Drozdowska, Małgorzata & Rogowicz, Karol & Kurowski, Łukasz & Smaga, Paweł, 2021. "Two decades of contagion effect on stock markets: Which events are more contagious?," Journal of Financial Stability, Elsevier, vol. 55(C).
    56. 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.
    57. Golosnoy, Vasyl & Gribisch, Bastian & Liesenfeld, Roman, 2015. "Intra-daily volatility spillovers in international stock markets," Journal of International Money and Finance, Elsevier, vol. 53(C), pages 95-114.
    58. Apostolou, Apostolos & Beirne, John, 2017. "Volatility spillovers of Federal Reserve and ECB balance sheet expansions to emerging market economies," Working Paper Series 2044, European Central Bank.
    59. Harald Schmidbauer & Angi Rösch & Erhan Uluceviz & Narod Erkol, 2016. "The Russian Stock Market during the Ukrainian Crisis: A Network Perspective," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 66(6), pages 478-509, December.
    60. Mário Nuno Mata & Muhammad Najib Razali & Sónia R. Bentes & Isabel Vieira, 2021. "Volatility Spillover Effect of Pan-Asia’s Property Portfolio Markets," Mathematics, MDPI, vol. 9(12), pages 1-20, June.
    61. Daniel Felix Ahelegbey & Luis Carvalho & Eric D. Kolaczyk, 2020. "A Bayesian Covariance Graph And Latent Position Model For Multivariate Financial Time Series," DEM Working Papers Series 181, University of Pavia, Department of Economics and Management.
    62. 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.
    63. Christian M. Hafner & Oliver B. Linton & Linqi Wang, 2024. "Dynamic Autoregressive Liquidity (DArLiQ)," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(2), pages 774-785, April.
    64. N. Taylor & Y. Xu, 2017. "The logarithmic vector multiplicative error model: an application to high frequency NYSE stock data," Quantitative Finance, Taylor & Francis Journals, vol. 17(7), pages 1021-1035, July.
    65. Jauhar Abbas & Hammad Hassan Mirza & Haroon Hussain & Rana Yassir Hussain & Muhammad Saad & Masud Akhtar, 2021. "Stock Market Reaction towards Terrorism: An Evidence Based on Seasonal Variation in Pakistan," Journal of Economic Impact, Science Impact Publishers, vol. 3(3), pages 167-177.

  18. Brownlees, Christian T. & Gallo, Giampiero M., 2011. "Shrinkage estimation of semiparametric multiplicative error models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 365-378, April.

    Cited by:

    1. Kim, Jiwon & Mahmassani, Hani S., 2015. "Compound Gamma representation for modeling travel time variability in a traffic network," Transportation Research Part B: Methodological, Elsevier, vol. 80(C), pages 40-63.
    2. Fabrizio Cipollini & Giampiero M. Gallo & Edoardo Otranto, 2019. "Realized Volatility Forecasting: Robustness to Measurement Errors," Econometrics Working Papers Archive 2019_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    3. COSMA, Antonio & GALLI, Fausto, 2006. "A nonparametric ACD model," LIDAM Discussion Papers CORE 2006067, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. Xinyu Zhang & Alan T. K. Wan & Sherry Z. Zhou, 2011. "Focused Information Criteria, Model Selection, and Model Averaging in a Tobit Model With a Nonzero Threshold," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 132-142, June.
    5. Deng, Ai, 2023. "Time series cross validation: A theoretical result and finite sample performance," Economics Letters, Elsevier, vol. 233(C).
    6. Yuanhua Feng & Sarah Forstinger & Christian Peitz, 2013. "On the iterative plug-in algorithm for estimating diurnal patterns of financial trade durations," Working Papers CIE 66, Paderborn University, CIE Center for International Economics.
    7. Giampiero M. Gallo & Edoardo Otranto, 2018. "Combining sharp and smooth transitions in volatility dynamics: a fuzzy regime approach," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(3), pages 549-573, April.

  19. Christian T. Brownlees & Fabrizio Cipollini & Giampiero M. Gallo, 2011. "Intra-daily Volume Modeling and Prediction for Algorithmic Trading," Journal of Financial Econometrics, Oxford University Press, vol. 9(3), pages 489-518, Summer.
    See citations under working paper version above.
  20. Cipollini, Fabrizio & Gallo, Giampiero M., 2010. "Automated variable selection in vector multiplicative error models," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2470-2486, November.
    See citations under working paper version above.
  21. Christian T. Brownlees & Giampiero M. Gallo, 2010. "Comparison of Volatility Measures: a Risk Management Perspective," Journal of Financial Econometrics, Oxford University Press, vol. 8(1), pages 29-56, Winter.
    See citations under working paper version above.
  22. Simone Bertoli & Giampiero Gallo & Giorgio Ricchiuti, 2010. "Exchange market pressure: some caveats in empirical applications," Applied Economics, Taylor & Francis Journals, vol. 42(19), pages 2435-2448.
    See citations under working paper version above.
  23. Giovanni Luca & Giampiero Gallo, 2009. "Time-Varying Mixing Weights in Mixture Autoregressive Conditional Duration Models," Econometric Reviews, Taylor & Francis Journals, vol. 28(1-3), pages 102-120.
    See citations under working paper version above.
  24. Giampiero M. Gallo & Margherita Velucchi, 2009. "Market interdependence and financial volatility transmission in East Asia," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 14(1), pages 24-44.

    Cited by:

    1. Khalifa, Ahmed A. & Alsarhan, Abdulwahab A. & Bertuccelli, Pietro, 2017. "Causes and consequences of energy price shocks on petroleum-based stock market using the spillover asymmetric multiplicative error model," Research in International Business and Finance, Elsevier, vol. 39(PA), pages 307-314.
    2. Małgorzata Doman & Ryszard Doman, 2013. "Dynamic linkages between stock markets: the effects of crises and globalization," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 12(2), pages 87-112, August.
    3. Abbas, Qaisar & Khan, Sabeen & Shah, Syed Zulfiqar Ali, 2013. "Volatility transmission in regional Asian stock markets," Emerging Markets Review, Elsevier, vol. 16(C), pages 66-77.
    4. Zheng, Tingguo & Zuo, Haomiao, 2013. "Reexamining the time-varying volatility spillover effects: A Markov switching causality approach," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 643-662.
    5. Usman M. Umer, Metin Coskun, Kasim Kiraci, 2018. "Time-varying Return and Volatility Spillover among EAGLEs Stock Markets: A Multivariate GARCH Analysis," Journal of Finance and Economics Research, Geist Science, Iqra University, Faculty of Business Administration, vol. 3(1), pages 23-42, March.
    6. Dufrénot, Gilles & Keddad, Benjamin, 2014. "Spillover effects of the 2008 global financial crisis on the volatility of the Indian equity markets: Coupling or uncoupling? A study on sector-based data," International Review of Financial Analysis, Elsevier, vol. 33(C), pages 17-32.
    7. Khalifa, Ahmed A.A. & Hammoudeh, Shawkat & Otranto, Edoardo, 2014. "Patterns of volatility transmissions within regime switching across GCC and global markets," International Review of Economics & Finance, Elsevier, vol. 29(C), pages 512-524.
    8. Jasmina Ðuraškovic & Slavica Manic & Dejan Živkov, 2019. "Multiscale Volatility Transmission and Portfolio Construction Between the Baltic Stock Markets," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 69(2), pages 211-235, April.

  25. Gallo, Giampiero M. & Otranto, Edoardo, 2008. "Volatility spillovers, interdependence and comovements: A Markov Switching approach," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 3011-3026, February.
    See citations under working paper version above.
  26. Christian T. Brownlees & Giampiero M. Gallo, 2008. "On Variable Selection for Volatility Forecasting: The Role of Focused Selection Criteria," Journal of Financial Econometrics, Oxford University Press, vol. 6(4), pages 513-539, Fall.

    Cited by:

    1. Brownlees, Christian T. & Gallo, Giampiero M., 2011. "Shrinkage estimation of semiparametric multiplicative error models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 365-378.
    2. Behl, Peter & Dette, Holger & Frondel, Manuel & Vance, Colin, 2019. "A focused information criterion for quantile regression: Evidence for the rebound effect," The Quarterly Review of Economics and Finance, Elsevier, vol. 71(C), pages 223-227.
    3. Behl, Peter & Dette, Holger & Frondel, Manuel & Tauchmann, Harald, 2011. "Choice is Suffering: A Focused Information Criterion for Model Selection," Ruhr Economic Papers 250, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    4. Gerda Claeskens, 2012. "Focused estimation and model averaging with penalization methods: an overview," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 66(3), pages 272-287, August.
    5. Cipollini, Fabrizio & Gallo, Giampiero M., 2010. "Automated variable selection in vector multiplicative error models," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2470-2486, November.
    6. Behl, Peter & Dette, Holger & Frondel, Manuel & Tauchmann, Harald, 2013. "Energy substitution: When model selection depends on the focus," Energy Economics, Elsevier, vol. 39(C), pages 233-238.
    7. Christian Brownlees & Giuseppe Cavaliere & Alice Monti, 2018. "Evaluating The Accuracy Of Tail Risk Forecasts For Systemic Risk Measurement," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 13(02), pages 1-25, June.
    8. Céline Cunen & Nils Lid Hjort, 2020. "Confidence Distributions for FIC Scores," Econometrics, MDPI, vol. 8(3), pages 1-28, July.
    9. Kley, Tobias & Preuss, Philip & Fryzlewicz, Piotr, 2019. "Predictive, finite-sample model choice for time series under stationarity and non-stationarity," LSE Research Online Documents on Economics 101748, London School of Economics and Political Science, LSE Library.

  27. Giampiero M. Gallo & Edoardo Otranto, 2007. "Volatility transmission across markets: a Multichain Markov Switching model," Applied Financial Economics, Taylor & Francis Journals, vol. 17(8), pages 659-670.
    See citations under working paper version above.
  28. Engle, Robert F. & Gallo, Giampiero M., 2006. "A multiple indicators model for volatility using intra-daily data," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 3-27.
    See citations under working paper version above.
  29. Rossi, Alessandro & Gallo, Giampiero M., 2006. "Volatility estimation via hidden Markov models," Journal of Empirical Finance, Elsevier, vol. 13(2), pages 203-230, March.
    See citations under working paper version above.
  30. Brownlees, C.T. & Gallo, G.M., 2006. "Financial econometric analysis at ultra-high frequency: Data handling concerns," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2232-2245, December.
    See citations under working paper version above.
  31. Perez-Amaral, Teodosio & Gallo, Giampiero M. & White, Halbert, 2005. "A COMPARISON OF COMPLEMENTARY AUTOMATIC MODELING METHODS: RETINA AND PcGets," Econometric Theory, Cambridge University Press, vol. 21(1), pages 262-277, February.
    See citations under working paper version above.
  32. De Luca Giovanni & Gallo Giampiero M., 2004. "Mixture Processes for Financial Intradaily Durations," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 8(2), pages 1-20, May.

    Cited by:

    1. Zhongxian Men & Tony S. Wirjanto & Adam W. Kolkiewicz, 2016. "A Multiscale Stochastic Conditional Duration Model," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 11(04), pages 1-28, December.
    2. Luc, BAUWENS & Nikolaus, HAUTSCH, 2006. "Modelling Financial High Frequency Data Using Point Processes," Discussion Papers (ECON - Département des Sciences Economiques) 2006039, Université catholique de Louvain, Département des Sciences Economiques.
    3. Yong Shi & Wei Dai & Wen Long & Bo Li, 2021. "Improved ACD-based financial trade durations prediction leveraging LSTM networks and Attention Mechanism," Papers 2101.02736, arXiv.org.
    4. Hiroyuki Kasahara & Katsumi Shimotsu, 2017. "Asymptotic Properties of the Maximum Likelihood Estimator in Regime Switching Econometric Models," CIRJE F-Series CIRJE-F-1049, CIRJE, Faculty of Economics, University of Tokyo.
    5. Wing Lon NG, 2004. "Duration and Order Type Clusters," Econometric Society 2004 Far Eastern Meetings 730, Econometric Society.
    6. Gallo, Giampiero M. & Otranto, Edoardo, 2015. "Forecasting realized volatility with changing average levels," International Journal of Forecasting, Elsevier, vol. 31(3), pages 620-634.
    7. Zhongxian Men & Adam W. Kolkiewicz & Tony S. Wirjanto, 2019. "Threshold Stochastic Conditional Duration Model for Financial Transaction Data," JRFM, MDPI, vol. 12(2), pages 1-21, May.
    8. Nikolaus Hautsch & Peter Malec & Melanie Schienle, 2014. "Capturing the Zero: A New Class of Zero-Augmented Distributions and Multiplicative Error Processes," Journal of Financial Econometrics, Oxford University Press, vol. 12(1), pages 89-121.
    9. Zhongxian Men & Tony S. Wirjanto & Adam W. Kolkiewicz, 2013. "Bayesian Inference of Multiscale Stochastic Conditional Duration Models," Working Paper series 63_13, Rimini Centre for Economic Analysis.
    10. Pérez-Rodríguez, Jorge V. & Gómez-Déniz, Emilio & Sosvilla-Rivero, Simón, 2021. "Testing unobserved market heterogeneity in financial markets: The case of Banco Popular," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 151-160.
    11. Jorge Pérez-Rodríguez & Emilio Gómez-Déniza & Simón Sosvilla-Rivero, 2019. "“Testing for private information using trade duration models with unobserved market heterogeneity: The case of Banco Popular”," IREA Working Papers 201907, University of Barcelona, Research Institute of Applied Economics, revised Apr 2019.
    12. Li, Zhicheng & Chen, Xinyun & Xing, Haipeng, 2023. "A multifactor regime-switching model for inter-trade durations in the high-frequency limit order market," Economic Modelling, Elsevier, vol. 118(C).
    13. Tony S. Wirjanto & Adam W. Kolkiewicz & Zhongxian Men, 2013. "Stochastic Conditional Duration Models with Mixture Processes," Working Paper series 29_13, Rimini Centre for Economic Analysis.
    14. Giovanni Luca & Giampiero Gallo, 2009. "Time-Varying Mixing Weights in Mixture Autoregressive Conditional Duration Models," Econometric Reviews, Taylor & Francis Journals, vol. 28(1-3), pages 102-120.
    15. Giampiero M. Gallo & Edoardo Otranto, 2014. "Forecasting Realized Volatility with Changes of Regimes," Econometrics Working Papers Archive 2014_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Feb 2014.
    16. Dungey, Mardi & Jeyasreedharan, Nagaratnam & Li, Tuo, 2010. "Modelling the Time Between Trades in the After-Hours Electronic Equity Futures Market," Working Papers 10451, University of Tasmania, Tasmanian School of Business and Economics, revised 30 May 2012.
    17. Markku Lanne, 2006. "A Mixture Multiplicative Error Model for Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 4(4), pages 594-616.
    18. Hujer, Reinhard & Vuletic, Sandra, 2007. "Econometric analysis of financial trade processes by discrete mixture duration models," Journal of Economic Dynamics and Control, Elsevier, vol. 31(2), pages 635-667, February.
    19. Pipat Wongsaart & Jiti Gao, 2011. "Nonparametric Kernel Testing in Semiparametric Autoregressive Conditional Duration Model," Monash Econometrics and Business Statistics Working Papers 18/11, Monash University, Department of Econometrics and Business Statistics.
    20. Samuel Gingras & William J. McCausland, 2020. "A Flexible Stochastic Conditional Duration Model," Papers 2005.09166, arXiv.org.
    21. Wing Lon NG, 2004. "Duration and Order Type Clusters," Econometric Society 2004 Australasian Meetings 272, Econometric Society.

  33. Teodosio Perez‐Amaral & Giampiero M. Gallo & Halbert White, 2003. "A Flexible Tool for Model Building: the Relevant Transformation of the Inputs Network Approach (RETINA)," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 65(s1), pages 821-838, December.
    See citations under working paper version above.
  34. Giampiero M. Gallo & Clive W.J. Granger & Yongil Jeon, 2002. "Copycats and Common Swings: The Impact of the Use of Forecasts in Information Sets," IMF Staff Papers, Palgrave Macmillan, vol. 49(1), pages 1-2.
    See citations under working paper version above.
  35. Edoardo Otranto & Giampiero Gallo, 2002. "A Nonparametric Bayesian Approach To Detect The Number Of Regimes In Markov Switching Models," Econometric Reviews, Taylor & Francis Journals, vol. 21(4), pages 477-496.
    See citations under working paper version above.
  36. Marco J. Lombardi & Giampiero M. Gallo, 2002. "Analytic Hessian matrices and the computation of FIGARCH estimates," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 11(2), pages 247-264, June.
    See citations under working paper version above.
  37. Giampiero M. Gallo, 2001. "Modelling the Impact of Overnight Surprises on Intra‐daily Volatility," Australian Economic Papers, Wiley Blackwell, vol. 40(4), pages 567-580, December.
    See citations under working paper version above.
  38. Giampiero Gallo & Barbara Pacini, 2000. "The effects of trading activity on market volatility," The European Journal of Finance, Taylor & Francis Journals, vol. 6(2), pages 163-175.

    Cited by:

    1. Henryk GURGUL & Tomasz WÓJTOWICZ, 2006. "Long Memory on the German Stock Exchange," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 56(09-10), pages 447-468, September.
    2. Sinha, Pankaj & Agnihotri, Shalini, 2014. "Investigating impact of volatility persistence, market asymmetry and information inflow on volatility of stock indices using bivariate GJR-GARCH," MPRA Paper 58303, University Library of Munich, Germany.
    3. Par Sjolander, 2009. "Are the Basel II requirements justified in the presence of structural breaks?," Applied Financial Economics, Taylor & Francis Journals, vol. 19(12), pages 985-998.
    4. Nguyen, Trang & Chaiechi, Taha & Eagle, Lynne & Low, David, 2020. "Dynamic transmissions between main stock markets and SME stock markets: Evidence from tropical economies," The Quarterly Review of Economics and Finance, Elsevier, vol. 75(C), pages 308-324.
    5. Zheng, Li & Sun, Yuying & Wang, Shouyang, 2024. "A novel interval-based hybrid framework for crude oil price forecasting and trading," Energy Economics, Elsevier, vol. 130(C).
    6. Daouda Lawa tan Toe & Salifou Ouedraogo, 2022. "Dynamic relationship between trading volume, returns and returns volatility: an empirical investigation on the main African’s stock markets," Journal of Asset Management, Palgrave Macmillan, vol. 23(5), pages 429-444, September.
    7. Heejoon Han & Dennis Kristensen, 2012. "Asymptotic Theory for the QMLE in GARCH-X Models with Stationary and Non-Stationary Covariates," CREATES Research Papers 2012-25, Department of Economics and Business Economics, Aarhus University.
    8. Gerlach, Richard & Chen, Cathy W.S. & Lin, Doris S.Y. & Huang, Ming-Hsiang, 2006. "Asymmetric responses of international stock markets to trading volume," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 360(2), pages 422-444.
    9. Benavides Guillermo, 2010. "Forecasting Short-Run Inflation Volatility using Futures Prices: An Empirical Analysis from a Value at Risk Perspective," Working Papers 2010-12, Banco de México.
    10. Pramod Kumar Naik & Puja Padhi, 2015. "Stock Market Volatility and Equity Trading Volume: Empirical Examination from Brazil, Russia, India and China (BRIC)," Global Business Review, International Management Institute, vol. 16(5_suppl), pages 28-45, October.
    11. Farag, Hisham & Cressy, Robert, 2011. "Do regulatory policies affect the flow of information in emerging markets?," Research in International Business and Finance, Elsevier, vol. 25(3), pages 238-254, September.
    12. Massimiliano Caporin & Francesco Poli, 2017. "Building News Measures from Textual Data and an Application to Volatility Forecasting," Econometrics, MDPI, vol. 5(3), pages 1-46, August.
    13. Paola Zuccolotto, 2002. "Modelling the impact of open volume on inter-trade autoregressive durations," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3-4), pages 49-63.
    14. Hasan Baklaci & Adnan Kasman, 2006. "An Empirical Analysis of Trading Volume and Return Volatility Relationship in The Turkish Stock Market," Ege Academic Review, Ege University Faculty of Economics and Administrative Sciences, vol. 6(2), pages 115-125.
    15. Cathy W. S. Chen & Mike K. P. So & Thomas C. Chiang, 2016. "Evidence of Stock Returns and Abnormal Trading Volume: A Threshold Quantile Regression Approach," The Japanese Economic Review, Springer, vol. 67(1), pages 96-124, March.
    16. Henryk Gurgul & Paweł Majdosz & Roland Mestel, 2007. "Price–volume relations of DAX companies," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 21(3), pages 353-379, September.
    17. Henryk Gurgul & Tomasz Wójtowicz, 2006. "Long-run properties of trading volume and volatility of equities listed in DJIA index," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 16(3-4), pages 29-56.
    18. Bu, Ruijun & Kim, Jihyun & Wang, Bin, 2023. "Uniform and Lp convergences for nonparametric continuous time regressions with semiparametric applications," Journal of Econometrics, Elsevier, vol. 235(2), pages 1934-1954.
    19. Zhang, Shuchang & Guo, Yaoqi & Cheng, Hui & Zhang, Hongwei, 2021. "Cross-correlations between price and volume in China's crude oil futures market: A study based on multifractal approaches," Chaos, Solitons & Fractals, Elsevier, vol. 144(C).
    20. Sarika Mahajan & Balwinder Singh, 2008. "An Empirical Analysis of Stock Price-Volume Relationship in Indian Stock Market," Vision, , vol. 12(3), pages 1-13, July.
    21. Constantinos Katrakilidis & Athanasios Koulakiotis, 2006. "The Impact of Stock Exchange Rules on Volatility and Error Transmission -- The Case of Frankfurt and Zurich Cross-Listed Equities," Annals of Economics and Finance, Society for AEF, vol. 7(2), pages 321-338, November.
    22. Kumar, Brajesh & Singh, Priyanka & Pandey, Ajay, 2009. "The Dynamic Relationship between Price and Trading Volume:Evidence from Indian Stock Market," IIMA Working Papers WP2009-12-04, Indian Institute of Management Ahmedabad, Research and Publication Department.
    23. Bohl, Martin T. & Henke, Harald, 2003. "Trading volume and stock market volatility: The Polish case," International Review of Financial Analysis, Elsevier, vol. 12(5), pages 513-525.
    24. Chen, Xiangyu & Tongurai, Jittima, 2022. "Spillovers and interdependency across base metals: Evidence from China's futures and spot markets," Resources Policy, Elsevier, vol. 75(C).
    25. Agosto, Arianna & Cavaliere, Giuseppe & Kristensen, Dennis & Rahbek, Anders, 2016. "Modeling corporate defaults: Poisson autoregressions with exogenous covariates (PARX)," Journal of Empirical Finance, Elsevier, vol. 38(PB), pages 640-663.
    26. Kao, Yu-Sheng & Zhao, Kai & Chuang, Hwei-Lin & Ku, Yu-Cheng, 2024. "The asymmetric relationships between the Bitcoin futures’ return, volatility, and trading volume," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 524-542.
    27. Eric Girard & Mohammed Omran, 2009. "On the relationship between trading volume and stock price volatility in CASE," International Journal of Managerial Finance, Emerald Group Publishing Limited, vol. 5(1), pages 110-134, February.
    28. Alsubaie, Abdullah & Najand, Mohammad, 2009. "Trading volume, time-varying conditional volatility, and asymmetric volatility spillover in the Saudi stock market," Journal of Multinational Financial Management, Elsevier, vol. 19(2), pages 139-159, April.
    29. Carroll, Rachael & Kearney, Colm, 2015. "Testing the mixture of distributions hypothesis on target stocks," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 39(C), pages 1-14.
    30. Müller, Christian, 2012. "A new interpretation of known facts: The case of two-way causality between trading and volatility," Economic Modelling, Elsevier, vol. 29(3), pages 664-670.
    31. Tseng-Chan Tseng & Hung-Cheng Lai & Cha-Fei Lin, 2012. "The impact of overnight returns on realized volatility," Applied Financial Economics, Taylor & Francis Journals, vol. 22(5), pages 357-364, March.
    32. Brajesh Kumar, 2010. "The Dynamic Relationship between Price and Trading Volume: Evidence from Indian Stock Market," Working Papers id:2379, eSocialSciences.
    33. Ping, Yuan & Li, Rui, 2018. "Forecasting realized volatility based on the truncated two-scales realized volatility estimator (TTSRV): Evidence from China's stock market," Finance Research Letters, Elsevier, vol. 25(C), pages 222-229.
    34. Brooks, C. & Clare, A. D. & Persand, G., 2000. "A word of caution on calculating market-based minimum capital risk requirements," Journal of Banking & Finance, Elsevier, vol. 24(10), pages 1557-1574, October.
    35. Pramod Kumar Naik & Rangan Gupta & Puja Padhi, 2016. "The Relationship between Stock Market Volatility and Trading Volume: Evidence from South Africa," Working Papers 201689, University of Pretoria, Department of Economics.
    36. Kao, Yu-Sheng & Chuang, Hwei-Lin & Ku, Yu-Cheng, 2020. "The empirical linkages among market returns, return volatility, and trading volume: Evidence from the S&P 500 VIX Futures," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    37. Bruce Burton & Satish Kumar & Nitesh Pandey, 2020. "Twenty-five years of The European Journal of Finance (EJF): a retrospective analysis," The European Journal of Finance, Taylor & Francis Journals, vol. 26(18), pages 1817-1841, December.
    38. Yi-Hao Lai & Yi-Chiuan Wang & Yu-Ching Chang, 2024. "Forecasting Trading-Session Return Volatility in Taiwan Futures Market: A Periodic Regime Switching with Jump Approach," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 31(2), pages 285-305, June.
    39. 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.
    40. Todorova, Neda & Souček, Michael, 2014. "The impact of trading volume, number of trades and overnight returns on forecasting the daily realized range," Economic Modelling, Elsevier, vol. 36(C), pages 332-340.
    41. Pankaj Sinha & Shalini Agnihotri, 2016. "Investigating Impact of Volatility Persistence and Information Inflow on Volatility of Stock Indices Using Bivarite GJR-GARCH," Global Business Review, International Management Institute, vol. 17(5), pages 1145-1161, October.

  39. Gallo Giampiero M. & Pacini Barbara, 1998. "Early News is Good News: The Effects of Market Opening on Market Volatility," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 2(4), pages 1-19, January.
    See citations under working paper version above.
  40. Fabrizio Cipollini & Giampiero M Gallo & Alessandro Palandri, 0. "Realized Variance Modeling: Decoupling Forecasting from Estimation," Journal of Financial Econometrics, Oxford University Press, vol. 18(3), pages 532-555.
    See citations under working paper version above.

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