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Stochastic volatility models: Conditional normality versus heavy tailed distributions
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Cited by:
- Isabel Casas & Helena Veiga, 2021.
"Exploring Option Pricing and Hedging via Volatility Asymmetry,"
Computational Economics, Springer;Society for Computational Economics, vol. 57(4), pages 1015-1039, April.
- Casas, Isabel, 2019. "Exploring option pricing and hedging via volatility asymmetry," DES - Working Papers. Statistics and Econometrics. WS 28234, Universidad Carlos III de Madrid. Departamento de EstadÃstica.
- Jensen, Mark J. & Maheu, John M., 2010.
"Bayesian semiparametric stochastic volatility modeling,"
Journal of Econometrics, Elsevier, vol. 157(2), pages 306-316, August.
- Mark J Jensen & John M Maheu, 2008. "Bayesian semiparametric stochastic volatility modeling," Working Papers tecipa-314, University of Toronto, Department of Economics.
- Mark J. Jensen & John M. Maheu, 2009. "Bayesian Semiparametric Stochastic Volatility Modeling," Working Paper series 23_09, Rimini Centre for Economic Analysis.
- Mark J. Jensen & John M. Maheu, 2008. "Bayesian semiparametric stochastic volatility modeling," FRB Atlanta Working Paper 2008-15, Federal Reserve Bank of Atlanta.
- Robert C. Jung & Roman Liesenfeld & Jean-François Richard, 2011.
"Dynamic Factor Models for Multivariate Count Data: An Application to Stock-Market Trading Activity,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(1), pages 73-85, January.
- Jung, Robert C. & Liesenfeld, Roman & Richard, Jean-François, 2011. "Dynamic Factor Models for Multivariate Count Data: An Application to Stock-Market Trading Activity," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 73-85.
- Jung, Robert & Liesenfeld, Roman & Richard, Jean-François, 2008. "Dynamic Factor Models for Multivariate Count Data: An Application to Stock-Market Trading Activity," Economics Working Papers 2008-12, Christian-Albrechts-University of Kiel, Department of Economics.
- Carmen Broto & Esther Ruiz, 2004.
"Estimation methods for stochastic volatility models: a survey,"
Journal of Economic Surveys, Wiley Blackwell, vol. 18(5), pages 613-649, December.
- Broto, Carmen, 2002. "Estimation methods for stochastic volatility models: a survey," DES - Working Papers. Statistics and Econometrics. WS ws025414, Universidad Carlos III de Madrid. Departamento de EstadÃstica.
- Paolo Girardello & Orietta Nicolis & Giovanni Tondini, 2003. "Comparing Conditional Variance Models: Theory and Empirical Evidence," Multinational Finance Journal, Multinational Finance Journal, vol. 7(3-4), pages 177-206, September.
- C. A. Abanto-Valle & V. H. Lachos & Dipak K. Dey, 2015. "Bayesian Estimation of a Skew-Student-t Stochastic Volatility Model," Methodology and Computing in Applied Probability, Springer, vol. 17(3), pages 721-738, September.
- P. de Zea Bermudez & J. Miguel Marín & Helena Veiga, 2020.
"Data cloning estimation for asymmetric stochastic volatility models,"
Econometric Reviews, Taylor & Francis Journals, vol. 39(10), pages 1057-1074, November.
- Zea Bermudez, Patrícia de, 2019. "Data cloning estimation for asymmetric stochastic volatility models," DES - Working Papers. Statistics and Econometrics. WS 28214, Universidad Carlos III de Madrid. Departamento de EstadÃstica.
- Kawakatsu, Hiroyuki, 2007. "Specification and estimation of discrete time quadratic stochastic volatility models," Journal of Empirical Finance, Elsevier, vol. 14(3), pages 424-442, June.
- Tsyplakov, Alexander, 2010. "Revealing the arcane: an introduction to the art of stochastic volatility models," MPRA Paper 25511, University Library of Munich, Germany.
- Mendoza-Velázquez, Alfonso & Galvanovskis, Evalds, 2009. "Introducing the GED-Copula with an application to Financial Contagion in Latin America," MPRA Paper 46669, University Library of Munich, Germany, revised 01 Feb 2010.
- Adam Clements & Scott White, 2005. "Nonlinear Filtering for Stochastic Volatility Models with Heavy Tails and Leverage," School of Economics and Finance Discussion Papers and Working Papers Series 192, School of Economics and Finance, Queensland University of Technology.
- Rombouts Jeroen V. K. & Bouaddi Mohammed, 2009.
"Mixed Exponential Power Asymmetric Conditional Heteroskedasticity,"
Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 13(3), pages 1-32, May.
- Mohammed Bouaddi & Jeroen V.K. Rombouts, 2007. "Mixed Exponential Power Asymmetric Conditional Heteroskedasticity," Cahiers de recherche 0749, CIRPEE.
- BOUADDI, Mohammed & ROMBOUTS, Jeroen V.K., 2007. "Mixed exponential power asymmetric conditional heteroskedasticity," LIDAM Discussion Papers CORE 2007097, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Mohammed Bouaddi & Jeroen V.K. Rombouts, 2007. "Mixed Exponential Power Asymmetric Conditional Heteroskedasticity," Cahiers de recherche 07-15, HEC Montréal, Institut d'économie appliquée.
- Bruno Feunou & Roméo Tédongap, 2012.
"A Stochastic Volatility Model With Conditional Skewness,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(4), pages 576-591, July.
- Bruno Feunou & Roméo Tedongap, 2011. "A Stochastic Volatility Model with Conditional Skewness," Staff Working Papers 11-20, Bank of Canada.
- Alexander Tsyplakov, 2010. "Revealing the arcane: an introduction to the art of stochastic volatility models (in Russian)," Quantile, Quantile, issue 8, pages 69-122, July.
- Xi, Yanhui & Peng, Hui & Qin, Yemei & Xie, Wenbiao & Chen, Xiaohong, 2015. "Bayesian analysis of heavy-tailed market microstructure model and its application in stock markets," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 117(C), pages 141-153.
- Yueh-Neng Lin & Ken Hung, 2008. "Is Volatility Priced?," Annals of Economics and Finance, Society for AEF, vol. 9(1), pages 39-75, May.
- N. Balakrishna & Bovas Abraham & Ranjini Sivakumar, 2006. "Gamma stochastic volatility models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(3), pages 153-171.
- Saralees Nadarajah, 2012. "Models for stock returns," Quantitative Finance, Taylor & Francis Journals, vol. 12(3), pages 411-424, February.
- Ruiz, Esther & Veiga, Helena, 2008.
"Modelling long-memory volatilities with leverage effect: A-LMSV versus FIEGARCH,"
Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2846-2862, February.
- Veiga, Helena, 2006. "Modelling long-memory volatilities with leverage effect: ALMSV versus FIEGARCH," DES - Working Papers. Statistics and Econometrics. WS ws066016, Universidad Carlos III de Madrid. Departamento de EstadÃstica.
- M. Hakan Eratalay, 2016.
"Estimation of Multivariate Stochastic Volatility Models: A Comparative Monte Carlo Study,"
International Econometric Review (IER), Econometric Research Association, vol. 8(2), pages 19-52, September.
- Mustafa Hakan Eratalay, 2012. "Estimation of Multivariate Stochastic Volatility Models: A Comparative Monte Carlo Study," EUSP Department of Economics Working Paper Series 2012/04, European University at St. Petersburg, Department of Economics.
- Carlos A. Abanto-Valle & Gabriel Rodríguez & Hernán B. Garrafa-Aragón, 2020. "Stochastic Volatility in Mean: Empirical Evidence from Stock Latin American Markets," Documentos de Trabajo / Working Papers 2020-481, Departamento de Economía - Pontificia Universidad Católica del Perú.
- Wang, Joanna J.J. & Chan, Jennifer S.K. & Choy, S.T. Boris, 2011. "Stochastic volatility models with leverage and heavy-tailed distributions: A Bayesian approach using scale mixtures," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 852-862, January.
- Asai, Manabu & Caporin, Massimiliano & McAleer, Michael, 2015.
"Forecasting Value-at-Risk using block structure multivariate stochastic volatility models,"
International Review of Economics & Finance, Elsevier, vol. 40(C), pages 40-50.
- Asai, M. & Caporin, M. & McAleer, M.J., 2012. "Forecasting Value-at-Risk Using Block Structure Multivariate Stochastic Volatility Models," Econometric Institute Research Papers EI 2012-02, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- Manabu Asai & Massimiliano Caporin & Michael McAleer, 2013. "Forecasting Value-at-Risk using Block Structure Multivariate Stochastic Volatility Models," Tinbergen Institute Discussion Papers 13-073/III, Tinbergen Institute.
- Manabu Asai & Massimiliano Caporin & Michael McAleer, 2012. "Forecasting Value-at-Risk Using Block Structure Multivariate Stochastic Volatility Models," Documentos de Trabajo del ICAE 2012-03, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
- Michael McAleer & Manabu Asai & Massimiliano Caporin, 2012. "Forecasting Value-at-Risk Using Block Structure Multivariate Stochastic Volatility Models," KIER Working Papers 812, Kyoto University, Institute of Economic Research.
- Manabu Asai & Massimiliano Caporin & Michael McAleer, 2012. "Forecasting Value-at-Risk Using Block Structure Multivariate Stochastic Volatility Models," Working Papers in Economics 12/04, University of Canterbury, Department of Economics and Finance.
- M. Angeles Carnero, 2004. "Persistence and Kurtosis in GARCH and Stochastic Volatility Models," Journal of Financial Econometrics, Oxford University Press, vol. 2(2), pages 319-342.
- Timo Terasvirta & Zhenfang Zhao, 2011.
"Stylized facts of return series, robust estimates and three popular models of volatility,"
Applied Financial Economics, Taylor & Francis Journals, vol. 21(1-2), pages 67-94.
- Teräsvirta, Timo & Zhao, Zhenfang, 2007. "Stylized Facts of Return Series, Robust Estimates, and Three Popular Models of Volatility," SSE/EFI Working Paper Series in Economics and Finance 662, Stockholm School of Economics, revised 01 Aug 2007.
- PREMINGER, Arie & HAFNER, Christian, 2006.
"Deciding between GARCH and stochastic volatility via strong decision rules,"
LIDAM Discussion Papers CORE
2006042, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Hafner, C. & Preminger, A., 2010. "Deciding between GARCH and Stochastic Volatility via Strong Decision Rules," LIDAM Reprints ISBA 2010032, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
- P. Girardello & Orietta Nicolis & Giovanni Tondini, 2002. "Comparing conditional variance models: Theory and empirical evidence," Departmental Working Papers 2002-08, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
- Virbickaitė, Audronė & Nguyen, Hoang & Tran, Minh-Ngoc, 2023.
"Bayesian predictive distributions of oil returns using mixed data sampling volatility models,"
Resources Policy, Elsevier, vol. 86(PA).
- Virbickaite, Audrone & Nguyen, Hoang & Tran, Minh-Ngoc, 2023. "Bayesian Predictive Distributions of Oil Returns Using Mixed Data Sampling Volatility Models," Working Papers 2023:7, Örebro University, School of Business.
- Kastner, Gregor, 2019.
"Sparse Bayesian time-varying covariance estimation in many dimensions,"
Journal of Econometrics, Elsevier, vol. 210(1), pages 98-115.
- Gregor Kastner, 2016. "Sparse Bayesian time-varying covariance estimation in many dimensions," Papers 1608.08468, arXiv.org, revised Nov 2017.
- 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.
- Asai, Manabu & Chang, Chia-Lin & McAleer, Michael, 2017.
"Realized stochastic volatility with general asymmetry and long memory,"
Journal of Econometrics, Elsevier, vol. 199(2), pages 202-212.
- Manabu Asai & Chia-Lin Chang & Michael McAleer, 2017. "Realized Stochastic Volatility with General Asymmetry and Long Memory," Tinbergen Institute Discussion Papers 17-038/III, Tinbergen Institute.
- Asai, M. & Chang, C-L. & McAleer, M.J., 2017. "Realized Stochastic Volatility with General Asymmetry and Long Memory," Econometric Institute Research Papers TI 2017-038/III, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- Jonathan Wright, 2002.
"Log-Periodogram Estimation Of Long Memory Volatility Dependencies With Conditionally Heavy Tailed Returns,"
Econometric Reviews, Taylor & Francis Journals, vol. 21(4), pages 397-417.
- Jonathan H. Wright, 2000. "Log-periodogram estimation of long memory volatility dependencies with conditionally heavy tailed returns," International Finance Discussion Papers 685, Board of Governors of the Federal Reserve System (U.S.).
- John Randal & Peter Thomson & Martin Lally, 2004. "Non-parametric estimation of historical volatility," Quantitative Finance, Taylor & Francis Journals, vol. 4(4), pages 427-440.
- Hautsch, Nikolaus & Ou, Yangguoyi, 2008. "Discrete-time stochastic volatility models and MCMC-based statistical inference," SFB 649 Discussion Papers 2008-063, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
- Meade, Nigel, 2010. "Oil prices -- Brownian motion or mean reversion? A study using a one year ahead density forecast criterion," Energy Economics, Elsevier, vol. 32(6), pages 1485-1498, November.
- Kastner, Gregor & Frühwirth-Schnatter, Sylvia, 2014.
"Ancillarity-sufficiency interweaving strategy (ASIS) for boosting MCMC estimation of stochastic volatility models,"
Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 408-423.
- Gregor Kastner & Sylvia Fruhwirth-Schnatter, 2017. "Ancillarity-Sufficiency Interweaving Strategy (ASIS) for Boosting MCMC Estimation of Stochastic Volatility Models," Papers 1706.05280, arXiv.org.
- Kirt C. Butler & Katsushi Okada, 2008. "Higher-Order Terms in Bivariate Returns to International Stock Market Indices," Multinational Finance Journal, Multinational Finance Journal, vol. 12(1-2), pages 127-155, March-Jun.
- repec:bgu:wpaper:0603 is not listed on IDEAS
- Mendoza, Alfonso. & Galvanovskis, Evalds., 2014. "La cópula GED bivariada. Una aplicación en entornos de crisis," El Trimestre Económico, Fondo de Cultura Económica, vol. 0(323), pages .721-746, julio-sep.
- repec:ebl:ecbull:v:3:y:2006:i:15:p:1-14 is not listed on IDEAS
- Malmsten, Hans & Teräsvirta, Timo, 2004. "Stylized Facts of Financial Time Series and Three Popular Models of Volatility," SSE/EFI Working Paper Series in Economics and Finance 563, Stockholm School of Economics, revised 03 Sep 2004.
- Abanto-Valle, C.A. & Bandyopadhyay, D. & Lachos, V.H. & Enriquez, I., 2010. "Robust Bayesian analysis of heavy-tailed stochastic volatility models using scale mixtures of normal distributions," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 2883-2898, December.
- repec:cte:wsrepe:ws142618 is not listed on IDEAS
- Ruili Sun & Tiefeng Ma & Shuangzhe Liu & Milind Sathye, 2019. "Improved Covariance Matrix Estimation for Portfolio Risk Measurement: A Review," JRFM, MDPI, vol. 12(1), pages 1-34, March.
- Liesenfeld, Roman & Richard, Jean-Francois, 2003. "Univariate and multivariate stochastic volatility models: estimation and diagnostics," Journal of Empirical Finance, Elsevier, vol. 10(4), pages 505-531, September.
- Li, Chenxing & Zhang, Zehua & Zhao, Ran, 2024.
"Volatility or higher moments: Which is more important in return density forecasts of stochastic volatility model?,"
Finance Research Letters, Elsevier, vol. 67(PB).
- Li, Chenxing & Zhang, Zehua & Zhao, Ran, 2023. "Volatility or higher moments: Which is more important in return density forecasts of stochastic volatility model?," MPRA Paper 118459, University Library of Munich, Germany.
- Huang, Wei & Liu, Qianqiu & Ghon Rhee, S. & Wu, Feng, 2012. "Extreme downside risk and expected stock returns," Journal of Banking & Finance, Elsevier, vol. 36(5), pages 1492-1502.
- Salvatore Ingrassia & Simona Minotti & Giorgio Vittadini, 2012.
"Local Statistical Modeling via a Cluster-Weighted Approach with Elliptical Distributions,"
Journal of Classification, Springer;The Classification Society, vol. 29(3), pages 363-401, October.
- Salvatore Ingrassia & Simona Caterina Minotti & Giorgio Vittadini, 2011. "Local Statistical Modeling via Cluster-Weighted Approach with Elliptical Distributions," Working Papers 20111001, Università degli Studi di Milano-Bicocca, Dipartimento di Statistica.
- Umberto Triacca & Fulvia Focker, 2014. "Estimating overnight volatility of asset returns by using the generalized dynamic factor model approach," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 37(2), pages 235-254, October.
- Manabu Asai & Michael McAleer, 2006.
"Asymmetric Multivariate Stochastic Volatility,"
Econometric Reviews, Taylor & Francis Journals, vol. 25(2-3), pages 453-473.
- Manabu Asai & Michael McAleer, 2005. "Asymmetric Multivariate Stochastic Volatility," DEA Working Papers 12, Universitat de les Illes Balears, Departament d'Economía Aplicada.
- Asai, Manabu, 2009. "Bayesian analysis of stochastic volatility models with mixture-of-normal distributions," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(8), pages 2579-2596.
- Mao, Xiuping & Czellar, Veronika & Ruiz, Esther & Veiga, Helena, 2020. "Asymmetric stochastic volatility models: Properties and particle filter-based simulated maximum likelihood estimation," Econometrics and Statistics, Elsevier, vol. 13(C), pages 84-105.
- Carlos A. Abanto‐Valle & Helio S. Migon & Hedibert F. Lopes, 2010. "Bayesian modeling of financial returns: A relationship between volatility and trading volume," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 26(2), pages 172-193, March.
- Patricia Lengua Lafosse & Cristian Bayes & Gabriel Rodríguez, 2015. "A Stochastic Volatility Model with GH Skew Student’s t-Distribution: Application to Latin-American Stock Returns," Documentos de Trabajo / Working Papers 2015-405, Departamento de Economía - Pontificia Universidad Católica del Perú.
- António Alberto Santos & João Andrade, 2014. "Stochastic Volatility Estimation with GPU Computing," GEMF Working Papers 2014-10, GEMF, Faculty of Economics, University of Coimbra.
- Mohammed Bouaddi & Khouzeima Moutanabbir, 2022. "Systematic extreme potential gain and loss spillover across countries," Risk Management, Palgrave Macmillan, vol. 24(4), pages 327-366, December.
- Fulvia Focker & Umberto Triacca, 2006. "A new proxy of the average volatility of a basket of returns: A Monte Carlo study," Economics Bulletin, AccessEcon, vol. 3(15), pages 1-14.
- repec:hum:wpaper:sfb649dp2008-063 is not listed on IDEAS
- Kirt Butler & Katsushi Okada, 2009. "The relative contribution of conditional mean and volatility in bivariate returns to international stock market indices," Applied Financial Economics, Taylor & Francis Journals, vol. 19(1), pages 1-15.
- Asai, Manabu, 2008. "Autoregressive stochastic volatility models with heavy-tailed distributions: A comparison with multifactor volatility models," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 332-341, March.
- Wang, Joanna J.J., 2012. "On asymmetric generalised t stochastic volatility models," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 82(11), pages 2079-2095.
- Carlos A. Abanto-Valle & Gabriel Rodríguez & Luis M. Castro Cepero & Hernán B. Garrafa-Aragón, 2024. "Approximate Bayesian Estimation of Stochastic Volatility in Mean Models Using Hidden Markov Models: Empirical Evidence from Emerging and Developed Markets," Computational Economics, Springer;Society for Computational Economics, vol. 64(3), pages 1775-1801, September.
- Adam Clements & Stan Hurn & Scott White, 2006. "Estimating Stochastic Volatility Models Using a Discrete Non-linear Filter. Working paper #3," NCER Working Paper Series 3, National Centre for Econometric Research.
- Jean-Jacques Forneron, 2019. "A Sieve-SMM Estimator for Dynamic Models," Papers 1902.01456, arXiv.org, revised Jan 2023.
- Carlos A. Abanto-Valle & Hernán B. Garrafa-Aragón, 2019. "Threshold Stochastic Volatility Models with Heavy Tails:A Bayesian Approach," Revista Economía, Fondo Editorial - Pontificia Universidad Católica del Perú, vol. 42(83), pages 32-53.
- Josu Arteche & Javier García‐Enríquez, 2022. "Singular spectrum analysis for value at risk in stochastic volatility models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(1), pages 3-16, January.
- Lengua Lafosse, Patricia & Rodríguez, Gabriel, 2018. "An empirical application of a stochastic volatility model with GH skew Student's t-distribution to the volatility of Latin-American stock returns," The Quarterly Review of Economics and Finance, Elsevier, vol. 69(C), pages 155-173.
- Gordon V. Chavez, 2019. "Dynamic tail inference with log-Laplace volatility," Papers 1901.02419, arXiv.org, revised Jul 2019.
- Bruno Ebner & Bernhard Klar & Simos G. Meintanis, 2018. "Fourier inference for stochastic volatility models with heavy-tailed innovations," Statistical Papers, Springer, vol. 59(3), pages 1043-1060, September.