Markov chain Monte Carlo methods for stochastic volatility models

Citations

Cited by:

1. Sujay Mukhoti & Pritam Ranjan, 2019. "A new class of discrete-time stochastic volatility model with correlated errors," Applied Economics, Taylor & Francis Journals, vol. 51(3), pages 259-277, January.
   • Sujay Mukhoti & Pritam Ranjan, 2017. "A New Class of Discrete-time Stochastic Volatility Model with Correlated Errors," Papers 1703.06603, arXiv.org.
2. Antonio A. F. Santos, 2021. "Bayesian Estimation for High-Frequency Volatility Models in a Time Deformed Framework," Computational Economics, Springer;Society for Computational Economics, vol. 57(2), pages 455-479, February.
3. Zhongxian Men & Tony S. Wirjanto & Adam W. Kolkiewicz, 2021. "Multiscale Stochastic Volatility Model with Heavy Tails and Leverage Effects," JRFM, MDPI, vol. 14(5), pages 1-28, May.
4. Jensen Mark J., 2016. "Robust estimation of nonstationary, fractionally integrated, autoregressive, stochastic volatility," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(4), pages 455-475, September.
   • Mark J. Jensen, 2015. "Robust estimation of nonstationary, fractionally integrated, autoregressive, stochastic volatility," FRB Atlanta Working Paper 2015-12, Federal Reserve Bank of Atlanta.
5. Iseringhausen, Martin, 2020. "The time-varying asymmetry of exchange rate returns: A stochastic volatility – stochastic skewness model," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 275-292.
   • Martin Iseringhausen, 2018. "The Time-Varying Asymmetry Of Exchange Rate Returns: A Stochastic Volatility – Stochastic Skewness Model," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 18/944, Ghent University, Faculty of Economics and Business Administration.
6. Hautsch, Nikolaus & Yang, Fuyu, 2012. "Bayesian inference in a Stochastic Volatility Nelson–Siegel model," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3774-3792.
   • Hautsch, Nikolaus & Yang, Fuyu, 2010. "Bayesian inference in a stochastic volatility Nelson-Siegel Model," SFB 649 Discussion Papers 2010-004, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
7. Ahmed Belhadjayed & Grégoire Loeper & Frédéric Abergel, 2016. "Forecasting Trends With Asset Prices," Post-Print hal-01512431, HAL.
8. 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.
9. J. Beirlant & G. Claeskens & C. Croux & H. Degryse & H. Dewachter & G. Dhaene & J. Dhaene & I. Gijbels & M. Goovaerts & M. Hubert & F. Roodhooft & W. Schouten & M. Willekens, 2005. "Managing Uncertainty: Financial, Actuarial and Statistical Modeling," Review of Business and Economic Literature, KU Leuven, Faculty of Economics and Business (FEB), Review of Business and Economic Literature, vol. 0(1), pages 23-48.
10. Kenichiro McAlinn & Asahi Ushio & Teruo Nakatsuma, 2020. "Volatility forecasts using stochastic volatility models with nonlinear leverage effects," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 143-154, March.
11. Nonejad, Nima, 2014. "Particle Gibbs with Ancestor Sampling Methods for Unobserved Component Time Series Models with Heavy Tails, Serial Dependence and Structural Breaks," MPRA Paper 55664, University Library of Munich, Germany.
12. Arnaud Dufays, 2014. "On the conjugacy of off-line and on-line Sequential Monte Carlo Samplers," Working Paper Research 263, National Bank of Belgium.
13. Timmermann, Allan & Pettenuzzo, Davide & Valkanov, Rossen, 2014. "A Bayesian MIDAS Approach to Modeling First and Second Moment Dynamics," CEPR Discussion Papers 10160, C.E.P.R. Discussion Papers.
    • Davide Pettenuzzo & Rossen Valkanov & Allan Timmermann, 2014. "A Bayesian MIDAS Approach to Modeling First and Second Moment Dynamics," Working Papers 76, Brandeis University, Department of Economics and International Business School.
14. 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 Estadística.
15. Faruk Selcuk, 2005. "Asymmetric stochastic volatility in emerging stock markets," Applied Financial Economics, Taylor & Francis Journals, vol. 15(12), pages 867-874.
16. Robert Barro & Tao Jin, 2021. "Rare Events and Long-Run Risks," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 39, pages 1-25, January.
    • Robert J. Barro & Tao Jin, 2016. "Rare Events and Long-Run Risks," NBER Working Papers 21871, National Bureau of Economic Research, Inc.
    • Robert Barro & Tao Jin, 2020. "Online Appendix to "Rare Events and Long-Run Risks"," Online Appendices 18-485, Review of Economic Dynamics.
    • Robert J. Barro & Tao Jin, 2016. "Rare events and long-run risks," AEI Economics Working Papers 905253, American Enterprise Institute.
    • Robert J. Barro & Tao Jin, 2016. "Rare Events and Long-Run Risks," Working Paper 115371, Harvard University OpenScholar.
    • Robert Barro & Tao Jin, 2020. "Code and data files for "Rare Events and Long-Run Risks"," Computer Codes 18-485, Review of Economic Dynamics.
17. Li, Yong & Yu, Jun, 2012. "Bayesian hypothesis testing in latent variable models," Journal of Econometrics, Elsevier, vol. 166(2), pages 237-246.
    • Yong Li & Jun Yu, 2011. "Bayesian Hypothesis Testing in Latent Variable Models," Working Papers 11-2011, Singapore Management University, School of Economics.
18. Georgios Tsiotas, 2009. "On the use of non-linear transformations in Stochastic Volatility models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 18(4), pages 555-583, November.
19. Aït-Sahalia, Yacine & Li, Chenxu & Li, Chen Xu, 2024. "Maximum likelihood estimation of latent Markov models using closed-form approximations," Journal of Econometrics, Elsevier, vol. 240(2).
20. Audronė Virbickaitė & Hedibert F. Lopes & M. Concepción Ausín & Pedro Galeano, 2019. "Particle learning for Bayesian semi-parametric stochastic volatility model," Econometric Reviews, Taylor & Francis Journals, vol. 38(9), pages 1007-1023, October.
    • Audrone Virbickaite & Hedibert F. Lopes & Maria Concepción Ausín & Pedro Galeano, 2018. "Particle Learning for Bayesian Semi-Parametric Stochastic Volatility Model," DEA Working Papers 88, Universitat de les Illes Balears, Departament d'Economía Aplicada.
21. Loddo, Antonello & Ni, Shawn & Sun, Dongchu, 2011. "Selection of Multivariate Stochastic Volatility Models via Bayesian Stochastic Search," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(3), pages 342-355.
    • Antonello Loddo & Shawn Ni & Dongchu Sun, 2011. "Selection of Multivariate Stochastic Volatility Models via Bayesian Stochastic Search," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(3), pages 342-355, July.
    • Shawn Ni & Antonello Loddo & Dongchu Sun, 2009. "Selection of Multivariate Stochastic Volatility Models via Bayesian Stochastic Search," Working Papers 0911, Department of Economics, University of Missouri.
22. 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.
23. Pettenuzzo, Davide & Timmermann, Allan & Valkanov, Rossen, 2016. "A MIDAS approach to modeling first and second moment dynamics," Journal of Econometrics, Elsevier, vol. 193(2), pages 315-334.
24. Yuta Yamauchi & Yasuhiro Omori, 2020. "Dynamic factor, leverage and realized covariances in multivariate stochastic volatility," Papers 2011.06909, arXiv.org, revised Sep 2021.
25. Philipp Otto & Osman Dou{g}an & Suleyman Tac{s}p{i}nar & Wolfgang Schmid & Anil K. Bera, 2023. "Spatial and Spatiotemporal Volatility Models: A Review," Papers 2308.13061, arXiv.org.
26. Davide Pettenuzzo & Riccardo Sabbatucci & Allan Timmermann, 2020. "Cash Flow News and Stock Price Dynamics," Journal of Finance, American Finance Association, vol. 75(4), pages 2221-2270, August.
    • Timmermann, Allan & Pettenuzzo, Davide & Sabbatucci, Riccardo, 2019. "Cash Flow News and Stock Price Dynamics," CEPR Discussion Papers 14117, C.E.P.R. Discussion Papers.
27. Joshua C.C. Chan & Angelia L. Grant, 2014. "Issues in Comparing Stochastic Volatility Models Using the Deviance Information Criterion," CAMA Working Papers 2014-51, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
28. Lombardi, Marco J. & Calzolari, Giorgio, 2009. "Indirect estimation of [alpha]-stable stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2298-2308, April.
    • Marco Lombardi & Giorgio Calzolari, 2006. "Indirect estimation of alpha-stable stochastic volatility models," Econometrics Working Papers Archive wp2006_07, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
29. de Pinho, Frank M. & Franco, Glaura C. & Silva, Ralph S., 2016. "Modeling volatility using state space models with heavy tailed distributions," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 119(C), pages 108-127.
30. Tsyplakov, Alexander, 2010. "Revealing the arcane: an introduction to the art of stochastic volatility models," MPRA Paper 25511, University Library of Munich, Germany.
31. Sabiwalsky, Ralf, 2012. "Does Basel II pillar 3 risk exposure data help to identify risky banks?," SFB 649 Discussion Papers 2012-008, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
32. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2016. "Common Drifting Volatility in Large Bayesian VARs," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(3), pages 375-390, July.
    • Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2012. "Common Drifting Volatility in Large Bayesian VARs," CEPR Discussion Papers 8894, C.E.P.R. Discussion Papers.
    • Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2012. "Common drifting volatility in large Bayesian VARs," Working Papers (Old Series) 1206, Federal Reserve Bank of Cleveland.
    • Andrea CARRIERO & Todd E. CLARK & Massimiliano MARCELLINO, 2012. "Common Drifting Volatility in Large Bayesian VARs," Economics Working Papers ECO2012/08, European University Institute.
33. Yu, Jun & Yang, Zhenlin & Zhang, Xibin, 2006. "A class of nonlinear stochastic volatility models and its implications for pricing currency options," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2218-2231, December.
    • Jun Yu & Zhenlin Yang & Xibin Zhang, 2002. "A Class of Nonlinear Stochastic Volatility Models and Its Implications on Pricing Currency Options," Monash Econometrics and Business Statistics Working Papers 17/02, Monash University, Department of Econometrics and Business Statistics.
34. Meddahi, N., 2001. "An Eigenfunction Approach for Volatility Modeling," Cahiers de recherche 2001-29, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    • Nour Meddahi, 2001. "An Eigenfunction Approach for Volatility Modeling," CIRANO Working Papers 2001s-70, CIRANO.
    • MEDDAHI, Nour, 2001. "An Eigenfunction Approach for Volatility Modeling," Cahiers de recherche 2001-29, Universite de Montreal, Departement de sciences economiques.
35. Yijie Peng & Michael C. Fu & Jian-Qiang Hu, 2016. "Gradient-based simulated maximum likelihood estimation for stochastic volatility models using characteristic functions," Quantitative Finance, Taylor & Francis Journals, vol. 16(9), pages 1393-1411, September.
36. Joonwook Park & Wayne DeSarbo & John Liechty, 2008. "A Hierarchical Bayesian Multidimensional Scaling Methodology for Accommodating Both Structural and Preference Heterogeneity," Psychometrika, Springer;The Psychometric Society, vol. 73(3), pages 451-472, September.
37. Manabu Asai & Michael McAleer, 2011. "Alternative Asymmetric Stochastic Volatility Models," Econometric Reviews, Taylor & Francis Journals, vol. 30(5), pages 548-564, October.
    • Manabu Asai & Michael McAleer, 2009. "Alternative Asymmetric Stochastic Volatility Models," CARF F-Series CARF-F-166, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    • Manabu Asai & Michael McAleer, 2010. "Alternative Asymmetric Stochastic Volatility Models," Working Papers in Economics 10/70, University of Canterbury, Department of Economics and Finance.
    • Manabu Asai & Michael McAleer, 2010. "Alternative Asymmetric Stochastic Volatility Models," KIER Working Papers 739, Kyoto University, Institute of Economic Research.
    • Asai, M. & McAleer, M.J., 2010. "Alternative Asymmetric Stochastic Volatility Models," Econometric Institute Research Papers EI 2010-69, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    • Manabu Asai & Michael McAleer, 2009. "Alternative Asymmetric Stochastic Volatility Models," CIRJE F-Series CIRJE-F-655, CIRJE, Faculty of Economics, University of Tokyo.
38. 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.
39. repec:dau:papers:123456789/6066 is not listed on IDEAS
40. 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.
41. Hedibert F. Lopes & Nicholas G. Polson, 2016. "Particle Learning for Fat-Tailed Distributions," Econometric Reviews, Taylor & Francis Journals, vol. 35(8-10), pages 1666-1691, December.
42. Raanju R. Sundararajan & Wagner Barreto‐Souza, 2023. "Student‐t stochastic volatility model with composite likelihood EM‐algorithm," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(1), pages 125-147, January.
43. Maciej Kostrzewski & Jadwiga Kostrzewska, 2021. "The Impact of Forecasting Jumps on Forecasting Electricity Prices," Energies, MDPI, vol. 14(2), pages 1-17, January.
44. Monica Billio & Roberto Casarin & Matteo Iacopini, 2024. "Bayesian Markov-Switching Tensor Regression for Time-Varying Networks," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 119(545), pages 109-121, January.
    • Monica Billio & Roberto Casarin & Matteo Iacopini, 2018. "Bayesian Markov Switching Tensor Regression for Time-varying Networks," Working Papers 2018:14, Department of Economics, University of Venice "Ca' Foscari".
45. Kirby, Chris, 2006. "Linear filtering for asymmetric stochastic volatility models," Economics Letters, Elsevier, vol. 92(2), pages 284-292, August.
46. N. Balakrishna & Bovas Abraham & Ranjini Sivakumar, 2006. "Gamma stochastic volatility models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(3), pages 153-171.
47. Håvard Rue & Sara Martino & Nicolas Chopin, 2009. "Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(2), pages 319-392, April.
48. Olsson, Jimmy & Rydén, Tobias, 2008. "Asymptotic properties of particle filter-based maximum likelihood estimators for state space models," Stochastic Processes and their Applications, Elsevier, vol. 118(4), pages 649-680, April.
49. Creal, Drew D. & Tsay, Ruey S., 2015. "High dimensional dynamic stochastic copula models," Journal of Econometrics, Elsevier, vol. 189(2), pages 335-345.
50. Lee, King Fuei, 2023. "Effects of Monetary Policy Frameworks on Stock Market Volatilities: An Empirical Study of Global Economies," MPRA Paper 119755, University Library of Munich, Germany.
51. Arnaud Dufays, 2016. "Evolutionary Sequential Monte Carlo Samplers for Change-Point Models," Econometrics, MDPI, vol. 4(1), pages 1-33, March.
    • Arnaud Dufays, 2015. "Evolutionary Sequential Monte Carlo Samplers for Change-point Models," Cahiers de recherche 1508, Centre de recherche sur les risques, les enjeux économiques, et les politiques publiques.
    • Arnaud Dufays, 2015. "Evolutionary Sequential Monte Carlo Samplers for Change-point Models," Cahiers de recherche 1518, CIRPEE.
52. John M Maheu & Thomas H McCurdy, 2007. "Modeling foreign exchange rates with jumps," Working Papers tecipa-279, University of Toronto, Department of Economics.
53. Drew Creal, 2012. "A Survey of Sequential Monte Carlo Methods for Economics and Finance," Econometric Reviews, Taylor & Francis Journals, vol. 31(3), pages 245-296.
    • Creal, D., 2009. "A survey of sequential Monte Carlo methods for economics and finance," Serie Research Memoranda 0018, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
54. Martin, Gael M. & Frazier, David T. & Maneesoonthorn, Worapree & Loaiza-Maya, Rubén & Huber, Florian & Koop, Gary & Maheu, John & Nibbering, Didier & Panagiotelis, Anastasios, 2024. "Bayesian forecasting in economics and finance: A modern review," International Journal of Forecasting, Elsevier, vol. 40(2), pages 811-839.
    • Gael M. Martin & David T. Frazier & Worapree Maneesoonthorn & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2022. "Bayesian Forecasting in Economics and Finance: A Modern Review," Papers 2212.03471, arXiv.org, revised Jul 2023.
55. Beum-Jo Park, 2011. "Forecasting Volatility in Financial Markets Using a Bivariate Stochastic Volatility Model with Surprising Information," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 37-58, September.
56. Gael M. Martin & David T. Frazier & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2023. "Bayesian Forecasting in the 21st Century: A Modern Review," Monash Econometrics and Business Statistics Working Papers 1/23, Monash University, Department of Econometrics and Business Statistics.
57. Kim, Jaeho, 2015. "Bayesian Inference in a Non-linear/Non-Gaussian Switching State Space Model: Regime-dependent Leverage Effect in the U.S. Stock Market," MPRA Paper 67153, University Library of Munich, Germany.
58. 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.
59. Davide Raggi & Silvano Bordignon, 2011. "Volatility, Jumps, and Predictability of Returns: A Sequential Analysis," Econometric Reviews, Taylor & Francis Journals, vol. 30(6), pages 669-695.
    • S. Bordignon & D. Raggi, 2008. "Volatility, Jumps and Predictability of Returns: a Sequential Analysis," Working Papers 636, Dipartimento Scienze Economiche, Universita' di Bologna.
60. Motta, Anderson C. O. & Hotta, Luiz K., 2003. "Exact Maximum Likelihood and Bayesian Estimation of the Stochastic Volatility Model," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 23(2), November.
61. 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.
62. Nakajima, Jouchi & Omori, Yasuhiro, 2009. "Leverage, heavy-tails and correlated jumps in stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2335-2353, April.
    • Jouchi Nakajima & Yasuhiro Omori, 2007. "Leverage, heavy-tails and correlated jumps in stochastic volatility models," CIRJE F-Series CIRJE-F-514, CIRJE, Faculty of Economics, University of Tokyo.
63. Davide Pettenuzzo & Riccardo Sabbatucci & Allan Timmermann, 2018. "High-frequency Cash Flow Dynamics," Working Papers 120, Brandeis University, Department of Economics and International Business School.
64. Gerlach, Richard & Tuyl, Frank, 2006. "MCMC methods for comparing stochastic volatility and GARCH models," International Journal of Forecasting, Elsevier, vol. 22(1), pages 91-107.
65. Mr. Noureddine Krichene, 2003. "Modeling Stochastic Volatility with Application to Stock Returns," IMF Working Papers 2003/125, International Monetary Fund.
66. Topaloglou, Nikolas & Tsionas, Mike G., 2020. "Stochastic dominance tests," Journal of Economic Dynamics and Control, Elsevier, vol. 112(C).
67. Du, Xiaodong & Yu, Cindy L. & Hayes, Dermot J., 2011. "Speculation and volatility spillover in the crude oil and agricultural commodity markets: A Bayesian analysis," Energy Economics, Elsevier, vol. 33(3), pages 497-503, May.
    • Xiaodong Du & Cindy L. Yu & Dermot J. Hayes, 2009. "Speculation and Volatility Spillover in the Crude Oil and Agricultural Commodity Markets: A Bayesian Analysis," Food and Agricultural Policy Research Institute (FAPRI) Publications (archive only) 09-wp491, Center for Agricultural and Rural Development (CARD) at Iowa State University.
    • Du, Xiaodong & Yu, Cindy L. & Hayes, Dermot J., 2011. "Speculation and volatility spillover in the crude oil and agricultural commodity markets: A Bayesian analysis," ISU General Staff Papers 201105010700001512, Iowa State University, Department of Economics.
    • Du, Xiaodong & Yu, Cindy L. & Hayes, Dermot J., 2009. "Speculation and Volatility Spillover in the Crude Oil and Agricultural Commodity Markets: A Bayesian Analysis," 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin 49276, Agricultural and Applied Economics Association.
    • Xiaodong Du & Cindy L. Yu & Dermot J. Hayes, 2009. "Speculation and Volatility Spillover in the Crude Oil and Agricultural Commodity Markets: A Bayesian Analysis," Center for Agricultural and Rural Development (CARD) Publications 09-wp491, Center for Agricultural and Rural Development (CARD) at Iowa State University.
68. Yu, Jun, 2005. "On leverage in a stochastic volatility model," Journal of Econometrics, Elsevier, vol. 127(2), pages 165-178, August.
    • Jun Yu, 2004. "On Leverage in a Stochastic Volatility Model," Econometric Society 2004 Far Eastern Meetings 506, Econometric Society.
    • Jun Yu, 2004. "On Leverage in a Stochastic Volatility Model," Working Papers 13-2004, Singapore Management University, School of Economics.
    • Jun Yu, 2004. "On leverage in a stochastic volatility model," Econometric Society 2004 Far Eastern Meetings 497, Econometric Society.
69. Aintablian, Sebouh & Khoury, Wissam El, 2017. "A simulation on the presence of competing bidders in mergers and acquisitions," Finance Research Letters, Elsevier, vol. 22(C), pages 233-243.
70. Petra Fleischer & Ross Maller & Gernot Müller, 2011. "A Bayesian analysis of market information linkages among NAFTA countries using a multivariate stochastic volatility model," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 35(2), pages 123-148, April.
71. Tsionas, Mike G., 2017. "A non-iterative (trivial) method for posterior inference in stochastic volatility models," Statistics & Probability Letters, Elsevier, vol. 126(C), pages 83-87.
72. Liesenfeld, Roman & Richard, Jean-François, 2008. "Improving MCMC, using efficient importance sampling," Computational Statistics & Data Analysis, Elsevier, vol. 53(2), pages 272-288, December.
    • Liesenfeld, Roman & Richard, Jean-François, 2006. "Improving MCMC Using Efficient Importance Sampling," Economics Working Papers 2006-05, Christian-Albrechts-University of Kiel, Department of Economics.
73. 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.
74. António Alberto Santos, 2015. "The evolution of the Volatility in Financial Returns: Realized Volatility vs Stochastic Volatility Measures," GEMF Working Papers 2015-10, GEMF, Faculty of Economics, University of Coimbra.
75. Deschamps, Philippe J., 2011. "Bayesian estimation of an extended local scale stochastic volatility model," Journal of Econometrics, Elsevier, vol. 162(2), pages 369-382, June.
76. Kobayashi, Masahito, 2009. "Testing for jumps in the stochastic volatility models," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(8), pages 2597-2608.
77. Tsiotas, Georgios, 2012. "On generalised asymmetric stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 56(1), pages 151-172, January.
78. Yanhui Xi & Hui Peng & Yemei Qin, 2016. "Modeling Financial Time Series Based on a Market Microstructure Model with Leverage Effect," Discrete Dynamics in Nature and Society, Hindawi, vol. 2016, pages 1-15, February.
79. K. Triantafyllopoulos, 2008. "Multivariate stochastic volatility with Bayesian dynamic linear models," Papers 0802.0214, arXiv.org.
80. Bandi, F.M. & Renò, R., 2016. "Price and volatility co-jumps," Journal of Financial Economics, Elsevier, vol. 119(1), pages 107-146.
81. Ilias Tsiakas, 2010. "The Economic Gains Of Trading Stocks Around Holidays," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 33(1), pages 1-26, March.
82. Han, Chuan-Hsiang & Molina, German & Fouque, Jean-Pierre, 2014. "McMC estimation of multiscale stochastic volatility models with applications," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 103(C), pages 1-11.
83. Koop, Gary & Korobilis, Dimitris, 2010. "Bayesian Multivariate Time Series Methods for Empirical Macroeconomics," Foundations and Trends(R) in Econometrics, now publishers, vol. 3(4), pages 267-358, July.
    • Gary Koop & Dimitris Korobilis, 2009. "Bayesian Multivariate Time Series Methods for Empirical Macroeconomics," Working Paper series 47_09, Rimini Centre for Economic Analysis.
    • Koop, Gary & Korobilis, Dimitris, 2009. "Bayesian Multivariate Time Series Methods for Empirical Macroeconomics," MPRA Paper 20125, University Library of Munich, Germany.
84. Angelos Alexopoulos & Petros Dellaportas & Omiros Papaspiliopoulos, 2019. "Bayesian prediction of jumps in large panels of time series data," Papers 1904.05312, arXiv.org, revised Apr 2021.
85. Chiranjit Dutta & Kara Karpman & Sumanta Basu & Nalini Ravishanker, 2023. "Review of Statistical Approaches for Modeling High-Frequency Trading Data," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 1-48, May.
86. Roberto León-González, 2019. "Efficient Bayesian inference in generalized inverse gamma processes for stochastic volatility," Econometric Reviews, Taylor & Francis Journals, vol. 38(8), pages 899-920, September.
    • Roberto Leon-Gonzalez, 2014. "Efficient Bayesian Inference in Generalized Inverse Gamma Processes for Stochastic Volatility," Working Paper series 19_14, Rimini Centre for Economic Analysis.
    • Roberto Leon-Gonzalez, 2018. "Efficient Bayesian Inference in Generalized Inverse Gamma Processes for Stochastic Volatility," GRIPS Discussion Papers 17-16, National Graduate Institute for Policy Studies.
    • Roberto Leon-Gonzalez, 2015. "Efficient Bayesian Inference in Generalized Inverse Gamma Processes for Stochastic Volatility," GRIPS Discussion Papers 15-17, National Graduate Institute for Policy Studies.
    • Roberto Leon-Gonzalez, 2014. "Efficient Bayesian Inference in Generalized Inverse Gamma Processes for Stochastic Volatility," GRIPS Discussion Papers 14-12, National Graduate Institute for Policy Studies.
87. Mark J. Jensen, 2004. "Semiparametric Bayesian Inference of Long‐Memory Stochastic Volatility Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(6), pages 895-922, November.
88. Xu, Wan & Khachatryan, Hayk, 2015. "The Role of Integrated Pest Management Practices in the U.S. Nursery Industry: A Bayesian Hierarchical Poisson Approach," 2015 Annual Meeting, January 31-February 3, 2015, Atlanta, Georgia 196808, Southern Agricultural Economics Association.
89. Phillip, Andrew & Chan, Jennifer & Peiris, Shelton, 2020. "On generalized bivariate student-t Gegenbauer long memory stochastic volatility models with leverage: Bayesian forecasting of cryptocurrencies with a focus on Bitcoin," Econometrics and Statistics, Elsevier, vol. 16(C), pages 69-90.
90. Chan, Joshua C.C., 2013. "Moving average stochastic volatility models with application to inflation forecast," Journal of Econometrics, Elsevier, vol. 176(2), pages 162-172.
    • Joshua C C Chan, 2012. "Moving Average Stochastic Volatility Models with Application to Inflation Forecast," ANU Working Papers in Economics and Econometrics 2012-591, Australian National University, College of Business and Economics, School of Economics.
    • Joshua C.C. Chan, 2013. "Moving Average Stochastic Volatility Models with Application to Inflation Forecast," CAMA Working Papers 2013-31, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
91. Yuta Yamauchi & Yasuhiro Omori, 2021. "Dynamic Factor, Leverage and Realized Covariances in Multivariate Stochastic Volatility," CIRJE F-Series CIRJE-F-1176, CIRJE, Faculty of Economics, University of Tokyo.
92. 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.
93. Jouchi Nakajima & Yasuhiro Omori, 2007. "Leverage, Heavy-Tails and Correlated Jumps in Stochastic Volatility Models (Revised in January 2008; Published in "Computational Statistics and Data Analysis", 53-6, 2335-2353. April 2009. )," CARF F-Series CARF-F-107, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
94. repec:hum:wpaper:sfb649dp2012-008 is not listed on IDEAS
95. 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.
96. Tingguo Zheng & Tao Song, 2014. "A Realized Stochastic Volatility Model With Box-Cox Transformation," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(4), pages 593-605, October.
97. Jeff Fleming & Chris Kirby & Barbara Ostdiek, 2006. "Stochastic Volatility, Trading Volume, and the Daily Flow of Information," The Journal of Business, University of Chicago Press, vol. 79(3), pages 1551-1590, May.
98. Tsionas, Mike G. & Philippas, Dionisis & Philippas, Nikolaos, 2022. "Multivariate stochastic volatility for herding detection: Evidence from the energy sector," Energy Economics, Elsevier, vol. 109(C).
99. Chen, Liyuan & Zerilli, Paola & Baum, Christopher F., 2019. "Leverage effects and stochastic volatility in spot oil returns: A Bayesian approach with VaR and CVaR applications," Energy Economics, Elsevier, vol. 79(C), pages 111-129.
    • Liyuan Chen & Paola Zerilli & Christopher F Baum, 2018. "Leverage effects and stochastic volatility in spot oil returns: A Bayesian approach with VaR and CVaR applications," Boston College Working Papers in Economics 953, Boston College Department of Economics.
100. Ilias Tsiakas, 2004. "Analysis of the predictive ability of information accumulated over nights, weekends and holidays," Econometric Society 2004 Australasian Meetings 208, Econometric Society.
101. António A. F. Santos, 2015. "On the Forecasting of Financial Volatility Using Ultra-High Frequency Data," GEMF Working Papers 2015-17, GEMF, Faculty of Economics, University of Coimbra.
102. Zu, Yang & Boswijk, H. Peter, 2017. "Consistent nonparametric specification tests for stochastic volatility models based on the return distribution," Journal of Empirical Finance, Elsevier, vol. 41(C), pages 53-75.
103. Omori, Yasuhiro & Chib, Siddhartha & Shephard, Neil & Nakajima, Jouchi, 2007. "Stochastic volatility with leverage: Fast and efficient likelihood inference," Journal of Econometrics, Elsevier, vol. 140(2), pages 425-449, October.
104. Jensen, Mark J. & Maheu, John M., 2014. "Estimating a semiparametric asymmetric stochastic volatility model with a Dirichlet process mixture," Journal of Econometrics, Elsevier, vol. 178(P3), pages 523-538.
     • Mark J. Jensen & John M. Maheu, 2012. "Estimating a Semiparametric Asymmetric Stochastic Volatility Model with a Dirichlet Process Mixture," Working Paper series 45_12, Rimini Centre for Economic Analysis.
     • Mark J Jensen & John M Maheu, 2012. "Estimating a Semiparametric Asymmetric Stochastic Volatility Model with a Dirichlet Process Mixture," Working Papers tecipa-453, University of Toronto, Department of Economics.
     • Mark J. Jensen & John M. Maheu, 2012. "Estimating a semiparametric asymmetric stochastic volatility model with a Dirichlet process mixture," FRB Atlanta Working Paper 2012-06, Federal Reserve Bank of Atlanta.
105. Mukhoti, Sujay, 2014. "Non-Stationary Stochastic Volatility Model for Dynamic Feedback and Skewness," MPRA Paper 62532, University Library of Munich, Germany.
106. David Chan & Robert Kohn & Chris Kirby, 2006. "Multivariate Stochastic Volatility Models with Correlated Errors," Econometric Reviews, Taylor & Francis Journals, vol. 25(2-3), pages 245-274.
107. Chan, Joshua & Strachan, Rodney, 2012. "Estimation in Non-Linear Non-Gaussian State Space Models with Precision-Based Methods," MPRA Paper 39360, University Library of Munich, Germany.
     • Joshua Chan & Rodney Strachan, 2012. "Estimation in Non-Linear Non-Gaussian State Space Models with Precision-Based Methods," CAMA Working Papers 2012-13, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
108. Maddalena Cavicchioli, 2017. "Estimation and asymptotic covariance matrix for stochastic volatility models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 26(3), pages 437-452, August.
109. Lopes, Hedibert F., 2014. "Particle learning for Bayesian non-parametric Markov Switching Stochastic Volatility model," DES - Working Papers. Statistics and Econometrics. WS ws142819, Universidad Carlos III de Madrid. Departamento de Estadística.
110. Isaiah Hull & Or Sattath & Eleni Diamanti & Göran Wendin, 2024. "Quantum Technology for Economists," Contributions to Economics, Springer, number 978-3-031-50780-9, May.
     • Hull, Isaiah & Sattath, Or & Diamanti, Eleni & Wendin, Göran, 2020. "Quantum Technology for Economists," Working Paper Series 398, Sveriges Riksbank (Central Bank of Sweden).
     • Isaiah Hull & Or Sattath & Eleni Diamanti & Goran Wendin, 2020. "Quantum Technology for Economists," Papers 2012.04473, arXiv.org, revised Oct 2021.
111. Jian Chen & Michael P Clements & Andrew Urquhart, 2024. "Modeling Price and Variance Jump Clustering Using the Marked Hawkes Process," Journal of Financial Econometrics, Oxford University Press, vol. 22(3), pages 743-772.
112. Emese Lazar & Shuyuan Qi & Radu Tunaru, 2020. "Measures of Model Risk in Continuous-time Finance Models," Papers 2010.08113, arXiv.org, revised Oct 2020.
113. Yufeng Han, 2011. "On the relation between the market risk premium and market volatility," Applied Financial Economics, Taylor & Francis Journals, vol. 21(22), pages 1711-1723.
114. Kristensen, Dennis, 2010. "Nonparametric Filtering Of The Realized Spot Volatility: A Kernel-Based Approach," Econometric Theory, Cambridge University Press, vol. 26(1), pages 60-93, February.
     • Dennis Kristensen, 2007. "Nonparametric Filtering of the Realised Spot Volatility: A Kernel-based Approach," CREATES Research Papers 2007-02, Department of Economics and Business Economics, Aarhus University.
115. Siddhartha Chib & Minchul Shin & Fei Tan, 2023. "DSGE-SVt: An Econometric Toolkit for High-Dimensional DSGE Models with SV and t Errors," Computational Economics, Springer;Society for Computational Economics, vol. 61(1), pages 69-111, January.
     • Siddhartha Chib & Minchul Shin & Fei Tan, 2021. "DSGE-SVt: An Econometric Toolkit for High-Dimensional DSGE Models with SV and t Errors," Working Papers 21-02, Federal Reserve Bank of Philadelphia.
116. Eunhee Lee & Doo Bong Han & Rodolfo M. Nayga, 2017. "A common factor of stochastic volatilities between oil and commodity prices," Applied Economics, Taylor & Francis Journals, vol. 49(22), pages 2203-2215, May.
     • Lee, Eunhee & Han, Doo Bong & Ito, Shoichi & Rodolfo M. Nayga, Jr, 2015. "A common factor of stochastic volatilities between oil and commodity prices," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205771, Agricultural and Applied Economics Association.
117. Byrne, Joseph P. & Cao, Shuo & Korobilis, Dimitris, 2019. "Decomposing global yield curve co-movement," Journal of Banking & Finance, Elsevier, vol. 106(C), pages 500-513.
     • Byrne, JP & Cao, S & Korobilis, D, 2016. "Decomposing Global Yield Curve Co-Movement," Essex Finance Centre Working Papers 18194, University of Essex, Essex Business School.
118. 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.
119. Charles S. Bos, 2008. "Model-based Estimation of High Frequency Jump Diffusions with Microstructure Noise and Stochastic Volatility," Tinbergen Institute Discussion Papers 08-011/4, Tinbergen Institute.
120. Kenichiro McAlinn & Asahi Ushio & Teruo Nakatsuma, 2016. "Volatility Forecasts Using Nonlinear Leverage Effects," Papers 1605.06482, arXiv.org, revised Dec 2017.
121. 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.
122. Junli Cheng & Feng Lin, 2022. "The Dynamic Effects of Urban–Rural Income Inequality on Sustainable Economic Growth under Urbanization and Monetary Policy in China," Sustainability, MDPI, vol. 14(11), pages 1-23, June.
123. Gorgi, Paolo & Koopman, Siem Jan & Li, Mengheng, 2019. "Forecasting economic time series using score-driven dynamic models with mixed-data sampling," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1735-1747.
     • Paolo Gorgi & Siem Jan (S.J.) Koopman & Mengheng Li, 2018. "Forecasting economic time series using score-driven dynamic models with mixed-data sampling," Tinbergen Institute Discussion Papers 18-026/III, Tinbergen Institute.
124. Huang, Jing-Zhi & Ni, Jun & Xu, Li, 2022. "Leverage effect in cryptocurrency markets," Pacific-Basin Finance Journal, Elsevier, vol. 73(C).
125. 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.
126. Avouyi-Dovi, S. & Horny, G. & Sevestre, P., 2013. "The dynamics of bank loans short-term interest rates in the Euro area: what lessons can we draw from the current crisis?," Working papers 462, Banque de France.
127. Jouchi Nakajima & Yasuhiro Omori, 2010. "Stochastic Volatility Model with Leverage and Asymmetrically Heavy-Tailed Error Using GH Skew Student's t-Distribution Models," CIRJE F-Series CIRJE-F-738, CIRJE, Faculty of Economics, University of Tokyo.
128. Richard Anton Braun & Huiyu Li & John Stachurski, 2009. "Computing Densities: A Conditional Monte Carlo Estimator," CIRJE F-Series CIRJE-F-678, CIRJE, Faculty of Economics, University of Tokyo.
     • Richard Anton Braun & Huiyu Li & John Stachurski, 2009. "Computing Densities: A Conditional Monte Carlo Estimator," CARF F-Series CARF-F-181, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
129. 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.
130. Siddhartha Chib & Srikanth Ramamurthy, 2014. "DSGE Models with Student- t Errors," Econometric Reviews, Taylor & Francis Journals, vol. 33(1-4), pages 152-171, June.
131. Tomohiro Ando, 2008. "Measuring the baseline sales and the promotion effect for incense products: a Bayesian state-space modeling approach," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 60(4), pages 763-780, December.
132. McCausland, William J., 2012. "The HESSIAN method: Highly efficient simulation smoothing, in a nutshell," Journal of Econometrics, Elsevier, vol. 168(2), pages 189-206.
133. Daichi Hiraki & Siddhartha Chib & Yasuhiro Omori, 2024. "Stochastic Volatility in Mean: Efficient Analysis by a Generalized Mixture Sampler," Papers 2404.13986, arXiv.org, revised Nov 2024.
134. Shiyi Chen & Wolfgang K. Härdle & Kiho Jeong, 2010. "Forecasting volatility with support vector machine-based GARCH model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(4), pages 406-433.
135. Manabu Asai & Michael McAleer & Jun Yu, 2006. "Multivariate Stochastic Volatility," Microeconomics Working Papers 22058, East Asian Bureau of Economic Research.
     • Siddhartha Chib & Yasuhiro Omori & Manabu Asai, 2007. "Multivariate stochastic volatility," CIRJE F-Series CIRJE-F-488, CIRJE, Faculty of Economics, University of Tokyo.
136. Calvet, Laurent E. & Fisher, Adlai J. & Thompson, Samuel B., 2006. "Volatility comovement: a multifrequency approach," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 179-215.
     • Laurent E. Calvet & Adlai J. Fisher & Samuel B. Thompson, 2004. "Volatility Comovement: A Multifrequency Approach," NBER Technical Working Papers 0300, National Bureau of Economic Research, Inc.
     • Laurent-Emmanuel Calvet & Adlai J. Fisher & Samuel B. Thompson, 2006. "Volatility Comovement: a multifrequency approach," Post-Print hal-00459667, HAL.
137. Frühwirth-Schnatter, Sylvia & Wagner, Helga, 2008. "Marginal likelihoods for non-Gaussian models using auxiliary mixture sampling," Computational Statistics & Data Analysis, Elsevier, vol. 52(10), pages 4608-4624, June.
138. Delis, Manthos & Iosifidi, Maria & Tsionas, Mike G, 2017. "Endogenous bank risk and efficiency," European Journal of Operational Research, Elsevier, vol. 260(1), pages 376-387.
139. Maciej Kostrzewski, 2016. "Bayesian SVLEDEJ Model for Detecting Jumps in Logarithmic Growth Rates of One Month Forward Gas Contract Prices," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 8(3), pages 161-179, September.
140. Siddhartha Chib & Yasuhiro Omori & Manabu Asai, 2007. "Multivariate stochastic volatility (Revised in May 2007, Handbook of Financial Time Series (Published in "Handbook of Financial Time Series" (eds T.G. Andersen, R.A. Davis, Jens-Peter Kreiss," CARF F-Series CARF-F-094, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
141. Arthur T. Rego & Thiago R. dos Santos, 2018. "Non-Gaussian Stochastic Volatility Model with Jumps via Gibbs Sampler," Papers 1809.01501, arXiv.org, revised Oct 2018.
142. Samar K. Guharay & Gaurav S. Thakur & Fred J. Goodman & Scott L. Rosen & Daniel Houser, 2016. "Integrated data-driven analytics to identify instability signatures in nonstationary financial time series," Applied Economics, Taylor & Francis Journals, vol. 48(18), pages 1678-1694, April.
143. Siem Jan Koopman & Marcel Scharth, 2012. "The Analysis of Stochastic Volatility in the Presence of Daily Realized Measures," Journal of Financial Econometrics, Oxford University Press, vol. 11(1), pages 76-115, December.
     • Siem Jan Koopman & Marcel Scharth, 2011. "The Analysis of Stochastic Volatility in the Presence of Daily Realised Measures," Tinbergen Institute Discussion Papers 11-132/4, Tinbergen Institute.
144. Celeux, Gilles & Marin, Jean-Michel & Robert, Christian P., 2006. "Iterated importance sampling in missing data problems," Computational Statistics & Data Analysis, Elsevier, vol. 50(12), pages 3386-3404, August.
145. Lupu, Radu, 2011. "Shock transmission among the European Stock markets - Conferinta CRESTERE ECONOMICA SI SUSTENABILITATE SOCIALA. PROVOCARI SI PERSPECTIVE EUROPENE>," Institute for Economic Forecasting Conference Proceedings 101101, Institute for Economic Forecasting.
146. Nonejad Nima, 2015. "Particle Gibbs with ancestor sampling for stochastic volatility models with: heavy tails, in mean effects, leverage, serial dependence and structural breaks," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(5), pages 561-584, December.
147. Deschamps, P., 2015. "Alternative Formulation of the Leverage Effect in a Stochastic Volatility Model with Asymmetric Heavy-Tailed Errors," LIDAM Discussion Papers CORE 2015020, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
148. Abdelhakim Aknouche, 2017. "Periodic autoregressive stochastic volatility," Statistical Inference for Stochastic Processes, Springer, vol. 20(2), pages 139-177, July.
149. 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.
150. Fruhwirth-Schnatter, Sylvia & Fruhwirth, Rudolf, 2007. "Auxiliary mixture sampling with applications to logistic models," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3509-3528, April.
151. Chib, Siddhartha & Nardari, Federico & Shephard, Neil, 2006. "Analysis of high dimensional multivariate stochastic volatility models," Journal of Econometrics, Elsevier, vol. 134(2), pages 341-371, October.
152. David Neto & Sylvain Sardy, 2012. "Moments structure of ℓ 1 -stochastic volatility models," Quality & Quantity: International Journal of Methodology, Springer, vol. 46(6), pages 1947-1952, October.
153. Yasuhiro Omori & Siddhartha Chib & Neil Shephard & Jouchi Nakajima, 2004. "Stochastic volatility with leverage: fast likelihood inference," Economics Papers 2004-W19, Economics Group, Nuffield College, University of Oxford.
     • Yasuhiro Omori & Siddhartha Chib & Neil Shephard & Jouchi Nakajima, 2004. "Stochastic Volatility with Leverage: Fast Likelihood Inference," CIRJE F-Series CIRJE-F-297, CIRJE, Faculty of Economics, University of Tokyo.
     • Neil Shephard & Yashurio Omori & Faculty of Economics & University of Tokyo & Siddhartha Chib & Olin School of Business & Washington University & Jouchi Nakajima & Faculty of Economics & University of, 2004. "Stochastic volatility with leverage: fast likelihood inference," Economics Series Working Papers 2004-FE-16, University of Oxford, Department of Economics.
154. 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.
155. Garland Durham, 2004. "Likelihood-based estimation and specification analysis of one- and two-factor SV models with leverage effects," Econometric Society 2004 North American Summer Meetings 294, Econometric Society.
156. Yanlin Shi, 2023. "Long memory and regime switching in the stochastic volatility modelling," Annals of Operations Research, Springer, vol. 320(2), pages 999-1020, January.
157. Dufour, Jean-Marie & Valéry, Pascale, 2009. "Exact and asymptotic tests for possibly non-regular hypotheses on stochastic volatility models," Journal of Econometrics, Elsevier, vol. 150(2), pages 193-206, June.
158. Radu Lupu, 2014. "Simultaneity of Tail Events for Dynamic Conditional Distributions of Stock Market Index Returns," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 49-64, December.
159. Ole E. Barndorff-Nielsen, 2004. "Power and Bipower Variation with Stochastic Volatility and Jumps," Journal of Financial Econometrics, Oxford University Press, vol. 2(1), pages 1-37.
     • Ole E. Barndorff-Nielsen & Neil Shephard, 2003. "Power and bipower variation with stochastic volatility and jumps," Economics Papers 2003-W17, Economics Group, Nuffield College, University of Oxford.
160. Heejoon Han & Eunhee Lee, 2020. "Triple Regime Stochastic Volatility Model with Threshold and Leverage Effects," Korean Economic Review, Korean Economic Association, vol. 36, pages 481-509.
161. Ren-Her Wang & John Aston & Cheng-Der Fuh, 2010. "The Role of Additional Information in Option Pricing: Estimation Issues for the State Space Model," Computational Economics, Springer;Society for Computational Economics, vol. 36(4), pages 283-307, December.
162. Tsiakas, Ilias, 2008. "Overnight information and stochastic volatility: A study of European and US stock exchanges," Journal of Banking & Finance, Elsevier, vol. 32(2), pages 251-268, February.
163. Nakajima, Jouchi & Omori, Yasuhiro, 2012. "Stochastic volatility model with leverage and asymmetrically heavy-tailed error using GH skew Student’s t-distribution," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3690-3704.
     • Jouchi Nakajima & Yasuhiro Omori, 2009. "Stochastic Volatility Model with Leverage and Asymmetrically Heavy-Tailed Error Using GH Skew Student's t-Distribution," CIRJE F-Series CIRJE-F-701, CIRJE, Faculty of Economics, University of Tokyo.
     • Jouchi Nakajima & Yasuhiro Omori, 2010. "Stochastic Volatility Model with Leverage and Asymmetrically Heavy-tailed Error Using GH Skew Student's t-distribution," Global COE Hi-Stat Discussion Paper Series gd09-124, Institute of Economic Research, Hitotsubashi University.
     • Jouchi Nakajima & Yasuhiro Omori, 2010. "Stochastic Volatility Model with Leverage and Asymmetrically Heavy-Tailed Error Using GH Skew Student?s t-Distribution," CARF F-Series CARF-F-215, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
     • Jouchi Nakajima & Yasuhiro Omori, 2009. "Stochastic volatility model with leverage and asymmetrically heavy-tailed error using GH skew Student's t-distribution," CARF F-Series CARF-F-199, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
164. Karamé, Frédéric, 2018. "A new particle filtering approach to estimate stochastic volatility models with Markov-switching," Econometrics and Statistics, Elsevier, vol. 8(C), pages 204-230.
     • Frédéric Karamé, 2018. "A new particle filtering approach to estimate stochastic volatility models with Markov-switching," Post-Print hal-02296093, HAL.
165. Durham, Garland B., 2006. "Monte Carlo methods for estimating, smoothing, and filtering one- and two-factor stochastic volatility models," Journal of Econometrics, Elsevier, vol. 133(1), pages 273-305, July.
166. Audrone Virbickaite & Hedibert F. Lopes, 2018. "Bayesian Semi-Parametric Markov Switching Stochastic Volatility Model," DEA Working Papers 89, Universitat de les Illes Balears, Departament d'Economía Aplicada.
167. Tian, Ping & Zhou, Hang & Zhou, Duotai, 2023. "Analysis about the Black-Scholes asset price under the regime-switching framework," International Review of Financial Analysis, Elsevier, vol. 88(C).
168. 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.
169. A. Hachicha & F. Hachicha, 2021. "Analysis of the bitcoin stock market indexes using comparative study of two models SV with MCMC algorithm," Review of Quantitative Finance and Accounting, Springer, vol. 56(2), pages 647-673, February.
170. Legrand, Romain, 2018. "Time-Varying Vector Autoregressions: Efficient Estimation, Random Inertia and Random Mean," MPRA Paper 88925, University Library of Munich, Germany.
171. Jacquier, Eric & Polson, Nicholas G. & Rossi, P.E.Peter E., 2004. "Bayesian analysis of stochastic volatility models with fat-tails and correlated errors," Journal of Econometrics, Elsevier, vol. 122(1), pages 185-212, September.
172. T. R. Santos, 2018. "A Bayesian GED-Gamma stochastic volatility model for return data: a marginal likelihood approach," Papers 1809.01489, arXiv.org.
173. Nonejad, Nima, 2014. "Particle Markov Chain Monte Carlo Techniques of Unobserved Component Time Series Models Using Ox," MPRA Paper 55662, University Library of Munich, Germany.
174. Trojan, Sebastian, 2013. "Regime Switching Stochastic Volatility with Skew, Fat Tails and Leverage using Returns and Realized Volatility Contemporaneously," Economics Working Paper Series 1341, University of St. Gallen, School of Economics and Political Science, revised Aug 2014.
175. Yuta Yamauchi & Yasuhiro Omori, 2020. "Dynamic Factor, Leverage and Realized Covariances in Multivariate Stochastic Volatility," CIRJE F-Series CIRJE-F-1158, CIRJE, Faculty of Economics, University of Tokyo.
176. Michael Smith & Andrew Pitts, 2006. "Foreign Exchange Intervention by the Bank of Japan: Bayesian Analysis Using a Bivariate Stochastic Volatility Model," Econometric Reviews, Taylor & Francis Journals, vol. 25(2-3), pages 425-451.
177. Xiaodong Du & Fengxia Dong, 2016. "Responses to market information and the impact on price volatility and trading volume: the case of Class III milk futures," Empirical Economics, Springer, vol. 50(2), pages 661-678, March.
178. Praveen Kumar Tripathi & Manika Agarwal, 2024. "A Bayes Analysis of Random Walk Model Under Different Error Assumptions," Annals of Data Science, Springer, vol. 11(5), pages 1635-1652, October.
179. Wei Wei & Denis Pelletier, 2015. "A Jump-Diffusion Model with Stochastic Volatility and Durations," CREATES Research Papers 2015-34, Department of Economics and Business Economics, Aarhus University.
180. 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.
181. Cheng, Ai-ru (Meg) & Gallant, A. Ronald & Ji, Chuanshu & Lee, Beom S., 2008. "A Gaussian approximation scheme for computation of option prices in stochastic volatility models," Journal of Econometrics, Elsevier, vol. 146(1), pages 44-58, September.
182. Jeongeun Kim & David S. Stoffer, 2008. "Fitting Stochastic Volatility Models in the Presence of Irregular Sampling via Particle Methods and the EM Algorithm," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(5), pages 811-833, September.
183. Yong Li & Jun Yu, 2010. "A New Bayesian Unit Root Test in Stochastic Volatility Models," Working Papers 21-2010, Singapore Management University, School of Economics, revised Oct 2010.
     • Yong Li & Jun Yu, 2012. "A New Bayesian Unit Root Test in Stochastic Volatility Models," Working Papers 14-2012, Singapore Management University, School of Economics.
184. Watanabe, Toshiaki & Nakajima, Jouchi, 2023. "High-frequency realized stochastic volatility model," Discussion paper series HIAS-E-127, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
185. 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.
     • Gilles Dufrénot & Benjamin Keddad, 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," Post-Print hal-01474429, HAL.
186. Nakajima Jouchi, 2013. "Stochastic volatility model with regime-switching skewness in heavy-tailed errors for exchange rate returns," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(5), pages 499-520, December.
187. Nonejad, Nima, 2017. "Parameter instability, stochastic volatility and estimation based on simulated likelihood: Evidence from the crude oil market," Economic Modelling, Elsevier, vol. 61(C), pages 388-408.
188. Tsionas, Mike G., 2021. "Bayesian analysis of static and dynamic Hurst parameters under stochastic volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 567(C).
189. Yasuhiro Omori & Siddhartha Chib & Neil Shephard & Jouchi Nakajima, 2004. "Stochastic Volatility with Leverage: Fast Likelihood Inference (Revised in April 2006, subsequently published in "Journal of Econometrics", 140, 425-449, 2007. )," CARF F-Series CARF-F-011, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
190. Manabu Asai, 2005. "Comparison of MCMC Methods for Estimating Stochastic Volatility Models," Computational Economics, Springer;Society for Computational Economics, vol. 25(3), pages 281-301, June.
191. McCausland, William & Miller, Shirley & Pelletier, Denis, 2021. "Multivariate stochastic volatility using the HESSIAN method," Econometrics and Statistics, Elsevier, vol. 17(C), pages 76-94.
192. Chew Lian Chua & G. C. Lim & Penelope Smith, 2008. "A Bayesian Simulation Approach to Inference on a Multi-State Latent Factor Intensity Model," Melbourne Institute Working Paper Series wp2008n16, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
193. Man Chung Fung & Gareth W. Peters & Pavel V. Shevchenko, 2016. "A unified approach to mortality modelling using state-space framework: characterisation, identification, estimation and forecasting," Papers 1605.09484, arXiv.org.
194. G. Dhaene, 2004. "Indirect Inference for Stochastic Volatility Models via the Log-Squared Observations," Review of Business and Economic Literature, KU Leuven, Faculty of Economics and Business (FEB), Review of Business and Economic Literature, vol. 0(3), pages 421-440.
195. Jonathan R. Stroud & Michael S. Johannes, 2014. "Bayesian Modeling and Forecasting of 24-Hour High-Frequency Volatility," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(508), pages 1368-1384, December.
196. António Alberto Santos & João Andrade, 2014. "Stochastic Volatility Estimation with GPU Computing," GEMF Working Papers 2014-10, GEMF, Faculty of Economics, University of Coimbra.
197. Andersen, Torben G. & Bollerslev, Tim & Dobrev, Dobrislav, 2007. "No-arbitrage semi-martingale restrictions for continuous-time volatility models subject to leverage effects, jumps and i.i.d. noise: Theory and testable distributional implications," Journal of Econometrics, Elsevier, vol. 138(1), pages 125-180, May.
     • Torben G. Andersen & Tim Bollerslev & Dobrislav Dobrev, 2007. "No-Arbitrage Semi-Martingale Restrictions for Continuous-Time Volatility Models subject to Leverage Effects, Jumps and i.i.d. Noise: Theory and Testable Distributional Implications," NBER Working Papers 12963, National Bureau of Economic Research, Inc.
198. Zellner, Arnold & Ando, Tomohiro, 2010. "Bayesian and non-Bayesian analysis of the seemingly unrelated regression model with Student-t errors, and its application for forecasting," International Journal of Forecasting, Elsevier, vol. 26(2), pages 413-434, April.
199. Sergey Egiev, 2016. "On Persistence of Uncertainty Shocks," HSE Working papers WP BRP 144/EC/2016, National Research University Higher School of Economics.
200. Liu, Qingfu & Wong, Ieokhou & An, Yunbi & Zhang, Jinqing, 2014. "Asymmetric Information and Volatility Forecasting in Commodity Futures Markets," Pacific-Basin Finance Journal, Elsevier, vol. 26(C), pages 79-97.
201. Xu, Bing & Ouenniche, Jamal, 2012. "A data envelopment analysis-based framework for the relative performance evaluation of competing crude oil prices' volatility forecasting models," Energy Economics, Elsevier, vol. 34(2), pages 576-583.
202. repec:hum:wpaper:sfb649dp2008-063 is not listed on IDEAS
203. repec:dau:papers:123456789/6215 is not listed on IDEAS
204. Pawel J. Szerszen, 2009. "Bayesian analysis of stochastic volatility models with Lévy jumps: application to risk analysis," Finance and Economics Discussion Series 2009-40, Board of Governors of the Federal Reserve System (U.S.).
205. 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.
206. Juan Hoyo & Guillermo Llorente & Carlos Rivero, 2020. "A Testing Procedure for Constant Parameters in Stochastic Volatility Models," Computational Economics, Springer;Society for Computational Economics, vol. 56(1), pages 163-186, June.
207. 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.
208. István Barra & Agnieszka Borowska & Siem Jan Koopman, 2018. "Bayesian Dynamic Modeling of High-Frequency Integer Price Changes," Journal of Financial Econometrics, Oxford University Press, vol. 16(3), pages 384-424.
     • Istvan Barra & Siem Jan Koopman & Agnieszka Borowska, 2016. "Bayesian Dynamic Modeling of High-Frequency Integer Price Changes," Tinbergen Institute Discussion Papers 16-028/III, Tinbergen Institute, revised 16 Feb 2018.
209. Aknouche, Abdelhakim, 2013. "Periodic autoregressive stochastic volatility," MPRA Paper 69571, University Library of Munich, Germany, revised 2015.
210. Roland Langrock & Théo Michelot & Alexander Sohn & Thomas Kneib, 2015. "Semiparametric stochastic volatility modelling using penalized splines," Computational Statistics, Springer, vol. 30(2), pages 517-537, June.
211. Guharay, Samar K. & Thakur, Gaurav S. & Goodman, Fred J. & Rosen, Scott L. & Houser, Daniel, 2013. "Analysis of non-stationary dynamics in the financial system," Economics Letters, Elsevier, vol. 121(3), pages 454-457.
212. Gloria Gonzalez-Rivera & Yun Luo, 2020. "A Truncated Mixture Transition Model for Interval-valued Time Series," Working Papers 202005, University of California at Riverside, Department of Economics.
     • Gloria Gonzalez-Rivera & Yun Luo, 2023. "A Truncated Mixture Transition Model for Interval-valued Time Series," Working Papers 202315, University of California at Riverside, Department of Economics.
213. Nima Nonejad, 2013. "Particle Markov Chain Monte Carlo Techniques of Unobserved Component Time Series Models Using Ox," CREATES Research Papers 2013-27, Department of Economics and Business Economics, Aarhus University.
214. Ahmed Bel Hadj Ayed & Gr'egoire Loeper & Fr'ed'eric Abergel, 2015. "Forecasting trends with asset prices," Papers 1504.03934, arXiv.org, revised Apr 2015.
215. Deschamps, Philippe J., 2011. "Bayesian estimation of an extended local scale stochastic volatility model," Journal of Econometrics, Elsevier, vol. 162(2), pages 369-382, June.
     • Deschamps, Philippe J., 2009. "Bayesian estimation of an extended local scale stochastic volatility model," DQE Working Papers 15, Department of Quantitative Economics, University of Freiburg/Fribourg Switzerland, revised 12 Nov 2011.
216. Kim C. Raath & Katherine B. Ensor, 2023. "Wavelet-L2E Stochastic Volatility Models: an Application to the Water-Energy Nexus," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 150-176, May.
217. Michael S. Johannes & Nicholas G. Polson & Jonathan R. Stroud, 2009. "Optimal Filtering of Jump Diffusions: Extracting Latent States from Asset Prices," The Review of Financial Studies, Society for Financial Studies, vol. 22(7), pages 2559-2599, July.
218. Osman Doğan & Süleyman Taşpınar & Anil K. Bera, 2021. "Bayesian estimation of stochastic tail index from high-frequency financial data," Empirical Economics, Springer, vol. 61(5), pages 2685-2711, November.
219. 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.
220. 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.
221. Sakaria, D.K. & Griffin, J.E., 2017. "On efficient Bayesian inference for models with stochastic volatility," Econometrics and Statistics, Elsevier, vol. 3(C), pages 23-33.
222. Jouchi Nakajima, 2008. "EGARCH and Stochastic Volatility: Modeling Jumps and Heavy-tails for Stock Returns," IMES Discussion Paper Series 08-E-23, Institute for Monetary and Economic Studies, Bank of Japan.
223. Raggi, Davide & Bordignon, Silvano, 2006. "Comparing stochastic volatility models through Monte Carlo simulations," Computational Statistics & Data Analysis, Elsevier, vol. 50(7), pages 1678-1699, April.
224. Smith Daniel R, 2009. "Asymmetry in Stochastic Volatility Models: Threshold or Correlation?," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 13(3), pages 1-36, May.
225. Ahmed Hachicha & Fatma Hachicha & Afif Masmoudi, 2012. "A comparative study of two models SV with MCMC algorithm," Review of Quantitative Finance and Accounting, Springer, vol. 38(4), pages 479-493, May.
226. Chon, Sora & Kim, Jaeho, 2021. "Does the Financial Leverage Effect Depend on Volatility Regimes?," Finance Research Letters, Elsevier, vol. 39(C).
227. Yong Li & Jun Yu, 2019. "An Improved Bayesian Unit Root Test in Stochastic Volatility Models," Annals of Economics and Finance, Society for AEF, vol. 20(1), pages 103-122, May.
228. Gordon V. Chavez, 2019. "Dynamic tail inference with log-Laplace volatility," Papers 1901.02419, arXiv.org, revised Jul 2019.
229. Phillip, Andrew & Chan, Jennifer S.K. & Peiris, Shelton, 2018. "A new look at Cryptocurrencies," Economics Letters, Elsevier, vol. 163(C), pages 6-9.