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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. Szabolcs Blazsek & Alvaro Escribano, 2010. "Knowledge spillovers in U.S. patents: A dynamic patent intensity model with secret common innovation factors," Post-Print hal-00732533, HAL.
  2. Carles Bret\'o, 2013. "On idiosyncratic stochasticity of financial leverage effects," Papers 1312.5496, arXiv.org.
  3. 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.
  4. 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.
  5. 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.
  6. Siem Jan Koopman & André Lucas & André Monteiro, 2005. "The Multi-State Latent Factor Intensity Model for Credit Rating Transitions," Tinbergen Institute Discussion Papers 05-071/4, Tinbergen Institute, revised 04 Jul 2005.
  7. Bretó, Carles, 2014. "On idiosyncratic stochasticity of financial leverage effects," Statistics & Probability Letters, Elsevier, vol. 91(C), pages 20-26.
  8. 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.
  9. Steffen Henzel & Malte Rengel, 2013. "Dimensions of macroeconomic uncertainty: A common factor analysis," Ifo Working Paper Series Ifo Working Paper No. 167, Ifo Institute for Economic Research at the University of Munich.
  10. 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.
  11. Hans J. Skaug & Jun Yu, 2007. "Automated Likelihood Based Inference for Stochastic Volatility Models," Working Papers CoFie-01-2007, Sim Kee Boon Institute for Financial Economics.
  12. Mustafa Hakan Eratalay, 2012. "Estimation of Multivariate Stochastic Volatility Models: A Comparative Monte Carlo Study," EUSP Deparment of Economics Working Paper Series Ec-04/12, European University at St. Petersburg, Department of Economics.
  13. 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".
  14. 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.
  15. Perry Sadorsky, 2005. "Stochastic volatility forecasting and risk management," Applied Financial Economics, Taylor & Francis Journals, vol. 15(2), pages 121-135.
  16. 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.
  17. 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.
  18. Tore Selland Kleppe & Jun Yu & Hans J. skaug, 2011. "Simulated Maximum Likelihood Estimation for Latent Diffusion Models," Working Papers 10-2011, Singapore Management University, School of Economics.
  19. 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.
  20. 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.
  21. 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).
  22. 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.
  23. 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.
  24. 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.
  25. 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.
  26. Alvaro Escribano & Szabolcs Blazsek, 2012. "Patents, secret innovations and firm's rate of return : differential effects of the innovation leader," Economics Working Papers we1202, Universidad Carlos III, Departamento de Economía.
  27. K. Triantafyllopoulos, 2012. "Multi‐variate stochastic volatility modelling using Wishart autoregressive processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 33(1), pages 48-60, 01.
  28. Tore Selland Kleppe & Hans J. Skaug & Jun Yu, 2009. "Simulated Maximum Likelihood Estimation of Continuous Time Stochastic Volatility Models," Working Papers CoFie-09-2009, Sim Kee Boon Institute for Financial Economics.
  29. Manabu Asai & Michael McAleer, 2014. "Forecasting Co-Volatilities via Factor Models with Asymmetry and Long Memory in Realized Covariance," Tinbergen Institute Discussion Papers 14-037/III, Tinbergen Institute.
  30. Manabu Asai & Michael McAleer & Marcelo C. Medeiros, 2010. "Asymmetry and Long Memory in Volatility Modelling," Working Papers in Economics 10/60, University of Canterbury, Department of Economics and Finance.
  31. Vasyl Golosnoy, 2007. "Sequential monitoring of minimum variance portfolio," AStA Advances in Statistical Analysis, Springer, vol. 91(1), pages 39-55, March.
  32. Manabu Asai & Michael McAleer & Jun Yu, 2006. "Multivariate Stochastic Volatility," Microeconomics Working Papers 22058, East Asian Bureau of Economic Research.
  33. Hautsch, Nikolaus, 2008. "Capturing common components in high-frequency financial time series: A multivariate stochastic multiplicative error model," Journal of Economic Dynamics and Control, Elsevier, vol. 32(12), pages 3978-4015, December.
  34. 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).
  35. 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.
  36. 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.
  37. 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.
  38. Tsunehiro Ishihara & Yasuhiro Omori, 2010. "Efficient Bayesian Estimation of a Multivariate Stochastic Volatility Model with Cross Leverage and Heavy-Tailed Errors," CARF F-Series CARF-F-221, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
  39. Galli, Fausto, 2014. "Stochastic conditonal range, a latent variable model for financial volatility," MPRA Paper 54030, University Library of Munich, Germany.
  40. Jean-Francois Richard & Roman Liesenfeld, 2007. "Classical and Bayesian Analysis of Univariate and Multivariate Stochastic Volatility Models," Working Papers 322, University of Pittsburgh, Department of Economics, revised Jan 2004.
  41. Szabolcs Blazsek & Álvaro Escribano, 2014. "Propensity to patent, R&D and market competition : dynamic spillovers of innovation leaders and followers," Economics Working Papers we1412, Universidad Carlos III, Departamento de Economía.
  42. Bauwens, L. & Galli, F., 2009. "Efficient importance sampling for ML estimation of SCD models," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 1974-1992, April.
  43. 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.
  44. 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.
  45. Jean-Francois Richard, 2007. "Efficient High-Dimensional Importance Sampling," Working Papers 321, University of Pittsburgh, Department of Economics, revised Jan 2007.
  46. 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.
  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. 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.
  49. 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.
  50. Manner, Hans & Segers, Johan, 2011. "Tails of correlation mixtures of elliptical copulas," Insurance: Mathematics and Economics, Elsevier, vol. 48(1), pages 153-160, January.
  51. Ruipeng Liu & Thomas Lux, 2010. "Flexible and Robust Modelling of Volatility Comovements: A Comparison of Two Multifractal Models," Kiel Working Papers 1594, Kiel Institute for the World Economy.
  52. 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.
  53. 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).
  54. Siem Jan Koopman & André Lucas & André Monteiro, 2005. "The Multi-State Latent Factor Intensity Model for Credit Rating Transitions," Tinbergen Institute Discussion Papers 05-071/4, Tinbergen Institute, revised 04 Jul 2005.
  55. Liesenfeld, Roman & Richard, Jean-François, 2008. "Improving MCMC, using efficient importance sampling," Computational Statistics & Data Analysis, Elsevier, vol. 53(2), pages 272-288, December.
  56. Kleppe, Tore Selland & Liesenfeld, Roman, 2014. "Efficient importance sampling in mixture frameworks," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 449-463.
  57. Tsyplakov, Alexander, 2010. "Revealing the arcane: an introduction to the art of stochastic volatility models," MPRA Paper 25511, University Library of Munich, Germany.
  58. Galli, Fausto, 2014. "Stochastic conditonal range, a latent variable model for financial volatility," MPRA Paper 54841, University Library of Munich, Germany.
  59. 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.
  60. PREMINGER, Arie & HAFNER, Christian M., 2006. "Deciding between GARCH and stochastic volatility via strong decision rules," CORE Discussion Papers 2006042, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  61. 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.
  62. 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.
  63. 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.
  64. Xiuping Mao & Esther Ruiz & Helena Veiga, 2013. "One for all : nesting asymmetric stochastic volatility models," Statistics and Econometrics Working Papers ws131110, Universidad Carlos III, Departamento de Estadística y Econometría.
  65. Andr� A. Monteiro, 2008. "Parameter Driven Multi-state Duration Models: Simulated vs. Approximate Maximum Likelihood Estimation," Tinbergen Institute Discussion Papers 08-021/2, Tinbergen Institute.
  66. 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.
  67. 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.
  68. 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.
  69. Manabu Asai & Michael McAleer, 2005. "Asymmetric Multivariate Stochastic Volatility," DEA Working Papers 12, Universitat de les Illes Balears, Departament d'Economía Aplicada.
  70. 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.
  71. BAUWENS, Luc & HAFNER, Christian & LAURENT, Sébastien, 2011. "Volatility models," CORE Discussion Papers 2011058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  72. 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.
  73. McCausland, William J., 2012. "The HESSIAN method: Highly efficient simulation smoothing, in a nutshell," Journal of Econometrics, Elsevier, vol. 168(2), pages 189-206.
  74. Siem Jan Koopman & Rutger Lit & André Lucas, 2014. "The Dynamic Skellam Model with Applications," Tinbergen Institute Discussion Papers 14-032/IV/DSF73, Tinbergen Institute.
  75. 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.
  76. Siem Jan Koopman & Andre Lucas & Marcel Scharth, 2011. "Numerically Accelerated Importance Sampling for Nonlinear Non-Gaussian State Space Models," Tinbergen Institute Discussion Papers 11-057/4, Tinbergen Institute, revised 27 Jan 2012.
  77. 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.
  78. 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.
  79. 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.
  80. 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.
  81. 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.
  82. 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.
  83. 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.
  84. 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.
  85. 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.