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Citations for "Univariate and multivariate stochastic volatility models: estimation and diagnostics"

by Liesenfeld, Roman & Richard, Jean-Francois

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  1. Dao, Chi-Mai & Wolters, Jürgen, 2008. "Common stochastic volatility trends in international stock returns," International Review of Financial Analysis, Elsevier, vol. 17(3), pages 431-445, June.
  2. 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.
  3. Manabu Asai & Michael McAleer & Marcelo C. Medeiros, 2011. "Asymmetry and Long Memory in Volatility Modelling," Documentos de Trabajo del ICAE 2011-29, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
  4. Maria Pacurar, 2008. "Autoregressive Conditional Duration Models In Finance: A Survey Of The Theoretical And Empirical Literature," Journal of Economic Surveys, Wiley Blackwell, vol. 22(4), pages 711-751, 09.
  5. Jean-François Richard, 2015. "Likelihood Evaluation of High-Dimensional Spatial Latent Gaussian Models with Non-Gaussian Response Variables," Working Paper 5778, Department of Economics, University of Pittsburgh.
  6. Jun Yu & Renate Meyer, 2006. "Multivariate Stochastic Volatility Models: Bayesian Estimation and Model Comparison," Econometric Reviews, Taylor & Francis Journals, vol. 25(2-3), pages 361-384.
  7. 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.
  8. Manabu Asai & Michael McAleer, 2009. "Alternative Asymmetric Stochastic Volatility Models," CIRJE F-Series CIRJE-F-655, CIRJE, Faculty of Economics, University of Tokyo.
  9. Ozturk, Serda Selin & Richard, Jean-Francois, 2015. "Stochastic volatility and leverage: Application to a panel of S&P500 stocks," Finance Research Letters, Elsevier, vol. 12(C), pages 67-76.
  10. McCausland, William J., 2012. "The HESSIAN method: Highly efficient simulation smoothing, in a nutshell," Journal of Econometrics, Elsevier, vol. 168(2), pages 189-206.
  11. Nikolaus Hautsch, 2007. "Capturing Common Components in High-Frequency Financial Time Series: A Multivariate Stochastic Multiplicative Error Model," SFB 649 Discussion Papers SFB649DP2007-052, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  12. 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.
  13. Kleppe, Tore Selland & Skaug, Hans Julius, 2012. "Fitting general stochastic volatility models using Laplace accelerated sequential importance sampling," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3105-3119.
  14. Liesenfeld, Roman & Richard, Jean-François, 2008. "Improving MCMC, using efficient importance sampling," Computational Statistics & Data Analysis, Elsevier, vol. 53(2), pages 272-288, December.
  15. Steffen Henzel & Malte Rengel, 2014. "Dimensions of Macroeconomic Uncertainty: A Common Factor Analysis," CESifo Working Paper Series 4991, CESifo Group Munich.
  16. Kleppe, Tore Selland & Skaug, Hans J., 2008. "Simulated maximum likelihood for general stochastic volatility models: a change of variable approach," MPRA Paper 12022, University Library of Munich, Germany.
  17. Escribano, Álvaro & Blazsek, Szabolcs, 2012. "Patents, secret innovations and firm's rate of return : differential effects of the innovation leader," UC3M Working papers. Economics we1202, Universidad Carlos III de Madrid. Departamento de Economía.
  18. Liesenfeld, Roman & Richard, Jean-François, 2004. "Classical and Bayesian Analysis of Univariate and Multivariate Stochastic Volatility Models," Economics Working Papers 2004,12, Christian-Albrechts-University of Kiel, Department of Economics.
  19. Tore Selland KLEPPE & Jun YU & Hans J. SKAUG, 2009. "Stimulated Maximum Likelihood Estimation of Continuous Time Stochastic Volatility Models," Working Papers 20-2009, Singapore Management University, School of Economics.
  20. Kleppe, Tore Selland & Yu, Jun & Skaug, Hans J., 2014. "Maximum likelihood estimation of partially observed diffusion models," Journal of Econometrics, Elsevier, vol. 180(1), pages 73-80.
  21. 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.
  22. Tsyplakov, Alexander, 2010. "Revealing the arcane: an introduction to the art of stochastic volatility models," MPRA Paper 25511, University Library of Munich, Germany.
  23. Pastorello, S. & Rossi, E., 2010. "Efficient importance sampling maximum likelihood estimation of stochastic differential equations," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2753-2762, November.
  24. Tore Selland Kleppe & Jun Yu & Hans J. Skaug, 2012. "Simulated Maximum Likelihood Estimation for Latent Diffusion Models," Working Papers 12-2012, Singapore Management University, School of Economics.
  25. Thomas Lux & Leonardo Morales-Arias & Cristina Sattarhoff, 2011. "A Markov-switching Multifractal Approach to Forecasting Realized Volatility," Kiel Working Papers 1737, Kiel Institute for the World Economy.
  26. 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.
  27. Lux, Thomas & Morales-Arias, Leonardo, 2010. "Relative forecasting performance of volatility models: Monte Carlo evidence," Kiel Working Papers 1582, Kiel Institute for the World Economy (IfW).
  28. Oleg Korenok & Stanislav Radchenko, 2005. "The smooth transition autoregressive target zone model with the Gaussian stochastic volatility and TGARCH error terms with applications," Econometrics 0508015, EconWPA.
  29. Koopman, Siem Jan & Lucas, Andre & Monteiro, Andre, 2008. "The multi-state latent factor intensity model for credit rating transitions," Journal of Econometrics, Elsevier, vol. 142(1), pages 399-424, January.
  30. Kleppe, Tore Selland & Liesenfeld, Roman, 2011. "Efficient high-dimensional importance sampling in mixture frameworks," Economics Working Papers 2011,11, Christian-Albrechts-University of Kiel, Department of Economics.
  31. 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.
  32. Subbotin, Alexandre, 2009. "Volatility Models: from Conditional Heteroscedasticity to Cascades at Multiple Horizons," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 15(3), pages 94-138.
  33. repec:pit:wpaper:322 is not listed on IDEAS
  34. Luc, BAUWENS & Fausto Galli, 2007. "Efficient importance sampling for ML estimation of SCD models," Discussion Papers (ECON - Département des Sciences Economiques) 2007032, Université catholique de Louvain, Département des Sciences Economiques.
  35. Siddhartha Chib & Yasuhiro Omori & Manabu Asai, 2007. "Multivariate stochastic volatility," CIRJE F-Series CIRJE-F-488, CIRJE, Faculty of Economics, University of Tokyo.
  36. Siem Jan Koopman & André Lucas & Marcel Scharth, 2015. "Numerically Accelerated Importance Sampling for Nonlinear Non-Gaussian State-Space Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(1), pages 114-127, January.
  37. Vêlayoudom Marimoutou & Manel Soury, 2015. "Energy Markets and CO2 Emissions: Analysis by Stochastic Copula Autoregressive Model," Working Papers halshs-01148746, HAL.
  38. Galli, Fausto, 2014. "Stochastic conditonal range, a latent variable model for financial volatility," MPRA Paper 54030, University Library of Munich, Germany.
  39. Bastian Gribisch, 2016. "Multivariate Wishart stochastic volatility and changes in regime," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 100(4), pages 443-473, October.
  40. repec:hal:journl:peer-00732533 is not listed on IDEAS
  41. Marimoutou, Vêlayoudom & Soury, Manel, 2015. "Energy markets and CO2 emissions: Analysis by stochastic copula autoregressive model," Energy, Elsevier, vol. 88(C), pages 417-429.
  42. BAUWENS, Luc & HAUTSCH, Nikolaus, 2003. "Dynamic latent factor models for intensity processes," CORE Discussion Papers 2003103, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  43. Manabu Asai & Michael McAleer & Marcelo C. Medeiros, 2009. "Asymmetry and Leverage in Realized Volatility," CARF F-Series CARF-F-167, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
  44. Malik, Sheheryar & Pitt, Michael K., 2011. "Particle filters for continuous likelihood evaluation and maximisation," Journal of Econometrics, Elsevier, vol. 165(2), pages 190-209.
  45. Manabu Asai & Michael McAleer, 2014. "Forecasting Co-Volatilities via Factor Models with Asymmetry and Long Memory in Realized Covariance," Documentos de Trabajo del ICAE 2014-05, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
  46. Escribano, Álvaro & Blazsek, Szabolcs, 2009. "Knowledge spillovers in U.S. patents: a dynamic patent intensity model with secret common innovation factors," UC3M Working papers. Economics we098951, Universidad Carlos III de Madrid. Departamento de Economía.
  47. González-Rivera, Gloria & Yoldas, Emre, 2012. "Autocontour-based evaluation of multivariate predictive densities," International Journal of Forecasting, Elsevier, vol. 28(2), pages 328-342.
  48. Tsunehiro Ishihara & Yasuhiro Omori, 2009. "Efficient Bayesian estimation of a multivariate stochastic volatility model with cross leverage and heavy-tailed errors," CARF F-Series CARF-F-198, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
  49. Nalan Basturk & Stefano Grassi & Lennart Hoogerheide & Herman K. van Dijk, 2016. "Time-varying Combinations of Bayesian Dynamic Models and Equity Momentum Strategies," Tinbergen Institute Discussion Papers 16-099/III, Tinbergen Institute.
  50. K. Triantafyllopoulos, 2013. "Multivariate stochastic volatility modelling using Wishart autoregressive processes," Papers 1311.0530, arXiv.org.
  51. Venter, J.H. & de Jongh, P.J., 2014. "Extended stochastic volatility models incorporating realised measures," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 687-707.
  52. Ruiz, Esther & Veiga, Helena & Mao, Xiuping, 2014. "Score driven asymmetric stochastic volatility models," DES - Working Papers. Statistics and Econometrics. WS ws142618, Universidad Carlos III de Madrid. Departamento de Estadística.
  53. Scharth, Marcel & Kohn, Robert, 2016. "Particle efficient importance sampling," Journal of Econometrics, Elsevier, vol. 190(1), pages 133-147.
  54. Suhejla Hoti & Esfandiar Maasoumi & Michael McAleer & Daniel Slottje, 2009. "Measuring the Volatility in U.S. Treasury Benchmarks and Debt Instruments," Econometric Reviews, Taylor & Francis Journals, vol. 28(6), pages 522-554.
  55. Liu, Ruipeng & Lux, Thomas, 2010. "Flexible and robust modelling of volatility comovements: a comparison of two multifractal models," Kiel Working Papers 1594, Kiel Institute for the World Economy (IfW).
  56. Perry Sadorsky, 2005. "Stochastic volatility forecasting and risk management," Applied Financial Economics, Taylor & Francis Journals, vol. 15(2), pages 121-135.
  57. BAUWENS, Luc & HAFNER, Christian & LAURENT, Sébastien, 2011. "Volatility models," CORE Discussion Papers 2011058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  58. Siem Jan Koopman & Rutger Lit & André Lucas, 2014. "The Dynamic Skellam Model with Applications," Tinbergen Institute Discussion Papers 14-032/IV/DSF73, Tinbergen Institute, revised 06 Jul 2015.
  59. Hautsch, Nikolaus & Ou, Yangguoyi, 2009. "Analyzing interest rate risk: Stochastic volatility in the term structure of government bond yields," CFS Working Paper Series 2009/03, Center for Financial Studies (CFS).
  60. Siem Jan Koopman & Rutger Lit & Thuy Minh Nguyen, 2012. "Fast Efficient Importance Sampling by State Space Methods," Tinbergen Institute Discussion Papers 12-008/4, Tinbergen Institute, revised 16 Oct 2014.
  61. Vêlayoudom Marimoutou & Manel Soury, 2015. "Energy Markets and CO2 Emissions: Analysis by Stochastic Copula Autoregressive Model," AMSE Working Papers 1520, Aix-Marseille School of Economics, Marseille, France.
  62. Blazsek, Szabolcs & Escribano, Alvaro, 2016. "Patent propensity, R&D and market competition: Dynamic spillovers of innovation leaders and followers," Journal of Econometrics, Elsevier, vol. 191(1), pages 145-163.
  63. Chris M. Strickland & Catherine S. Forbes & Gael M. Martin, 2003. "Bayesian Analysis of the Stochastic Conditional Duration Model," Monash Econometrics and Business Statistics Working Papers 14/03, Monash University, Department of Econometrics and Business Statistics.
  64. 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.
  65. Roberto Casarin & Marco Tronzano & Domenico Sartore, 2013. "Bayesian Markov Switching Stochastic Correlation Models," Working Papers 2013:11, Department of Economics, University of Venice "Ca' Foscari".
  66. 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.
  67. Nikolaus Hautsch & Yangguoyi Ou, 2008. "Discrete-Time Stochastic Volatility Models and MCMC-Based Statistical Inference," SFB 649 Discussion Papers SFB649DP2008-063, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  68. Siem Jan Koopman & Andre Lucas & Marcel Scharth, 2012. "Predicting Time-Varying Parameters with Parameter-Driven and Observation-Driven Models," Tinbergen Institute Discussion Papers 12-020/4, Tinbergen Institute.
  69. Lee, Woojoo & Lim, Johan & Lee, Youngjo & del Castillo, Joan, 2011. "The hierarchical-likelihood approach to autoregressive stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 248-260, January.
  70. Skaug, Hans J. & Yu, Jun, 2014. "A flexible and automated likelihood based framework for inference in stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 642-654.
  71. McCAUSLAND, William, 2008. "The Hessian Method (Highly Efficient State Smoothing, In a Nutshell)," Cahiers de recherche 2008-03, Universite de Montreal, Departement de sciences economiques.
  72. Jung, Robert & Kukuk, Martin & Liesenfeld, Roman, 2005. "Time Series of Count Data : Modelling and Estimation," Economics Working Papers 2005,08, Christian-Albrechts-University of Kiel, Department of Economics.
  73. 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.
  74. Jun Yu, 2004. "Asymmetric Response of Volatility: Evidence from Stochastic Volatility Models and Realized Volatility," Working Papers 24-2004, Singapore Management University, School of Economics.
  75. Manabu Asai & Michael McAleer, 2005. "Asymmetric Multivariate Stochastic Volatility," DEA Working Papers 12, Universitat de les Illes Balears, Departament d'Economía Aplicada.
  76. Manner, Hans & Segers, Johan, 2011. "Tails of correlation mixtures of elliptical copulas," Insurance: Mathematics and Economics, Elsevier, vol. 48(1), pages 153-160, January.
  77. Bretó, Carles, 2014. "On idiosyncratic stochasticity of financial leverage effects," Statistics & Probability Letters, Elsevier, vol. 91(C), pages 20-26.
  78. Deschamps, P., 2015. "Alternative Formulation of the Leverage Effect in a Stochastic Volatility Model with Asymmetric Heavy-Tailed Errors," CORE Discussion Papers 2015020, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  79. Ingmar Nolte & Valeri Voev, 2007. "Panel Intensity Models with Latent Factors: An Application to the Trading Dynamics on the Foreign Exchange Market¤," CoFE Discussion Paper 07-02, Center of Finance and Econometrics, University of Konstanz.
  80. Kleppe, Tore Selland & Liesenfeld, Roman, 2014. "Efficient importance sampling in mixture frameworks," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 449-463.
  81. M. Shelton Peiris & Manabu Asai, 2016. "Generalized Fractional Processes with Long Memory and Time Dependent Volatility Revisited," Econometrics, MDPI, Open Access Journal, vol. 4(3), pages 37-37, September.
  82. Mustafa Hakan Eratalay, 2012. "Estimation of Multivariate Stochastic Volatility Models: A Comparative Monte Carlo Study," EUSP Department of Economics Working Paper Series Ec-04/12, European University at St. Petersburg, Department of Economics.
  83. Carles Bret\'o, 2013. "On idiosyncratic stochasticity of financial leverage effects," Papers 1312.5496, arXiv.org.
  84. Hafner Christian M. & Manner Hans, 2008. "Dynamic stochastic copula models: Estimation, inference and applications," Research Memorandum 043, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
  85. 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.
  86. Pierre Collin-Dufresne & Christopher S. Jones & Robert S. Goldstein, 2004. "Can Interest Rate Volatility be Extracted from the Cross Section of Bond Yields? An Investigation of Unspanned Stochastic Volatility," NBER Working Papers 10756, National Bureau of Economic Research, Inc.
  87. 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).
  88. Koopman, Siem Jan & Shephard, Neil & Creal, Drew, 2009. "Testing the assumptions behind importance sampling," Journal of Econometrics, Elsevier, vol. 149(1), pages 2-11, April.
  89. Blazsek, Szabolcs & Escribano, Álvaro, 2014. "Propensity to patent, R&D and market competition : dynamic spillovers of innovation leaders and followers," UC3M Working papers. Economics we1412, Universidad Carlos III de Madrid. Departamento de Economía.
  90. BAUWENS, Luc & HAUTSCH, Nikolaus, "undated". "Stochastic conditional intensity processes," CORE Discussion Papers RP 1937, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  91. Galli, Fausto, 2014. "Stochastic conditonal range, a latent variable model for financial volatility," MPRA Paper 54841, University Library of Munich, Germany.
  92. Veiga, Helena & Ruiz, Esther & Mao, Xiuping, 2013. "One for all : nesting asymmetric stochastic volatility models," DES - Working Papers. Statistics and Econometrics. WS ws131110, Universidad Carlos III de Madrid. Departamento de Estadística.
  93. Wu, Xin-Yu & Ma, Chao-Qun & Wang, Shou-Yang, 2012. "Warrant pricing under GARCH diffusion model," Economic Modelling, Elsevier, vol. 29(6), pages 2237-2244.
  94. Chris M Strickland & Gael Martin & Catherine S Forbes, 2006. "Parameterisation and Efficient MCMC Estimation of Non-Gaussian State Space Models," Monash Econometrics and Business Statistics Working Papers 22/06, Monash University, Department of Econometrics and Business Statistics.
  95. Alexander Subbotin & Thierry Chauveau & Kateryna Shapovalova, 2009. "Volatility Models : from GARCH to Multi-Horizon Cascades," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00390636, HAL.
  96. Richard, Jean-Francois & Zhang, Wei, 2007. "Efficient high-dimensional importance sampling," Journal of Econometrics, Elsevier, vol. 141(2), pages 1385-1411, December.
  97. Arie Preminger & Christian M. Hafner, 2006. "Deciding Between Garch And Stochastic Volatility Via Strong Decision Rules," Working Papers 0603, Ben-Gurion University of the Negev, Department of Economics.
  98. Jung, Robert C. & Kukuk, Martin & Liesenfeld, Roman, 2006. "Time series of count data: modeling, estimation and diagnostics," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2350-2364, December.
  99. Ahmed Hachicha & Fatma Hachicha & Afif Masmoudi, 2013. "SV Mixture, Classification Using EM Algorithm," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 3(4), pages 553-559, April.
  100. Vasyl Golosnoy, 2007. "Sequential monitoring of minimum variance portfolio," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 91(1), pages 39-55, March.
  101. Durham, Garland B., 2007. "SV mixture models with application to S&P 500 index returns," Journal of Financial Economics, Elsevier, vol. 85(3), pages 822-856, September.
  102. Richard, Oliver & Van Horn, Larry, 2004. "Persistence in prescriptions of branded drugs," International Journal of Industrial Organization, Elsevier, vol. 22(4), pages 523-540, April.
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