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A threshold factor multivariate stochastic volatility model

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  • Mike K. P. So

    (Hong Kong University of Science and Technology, Hong Kong)

  • C. Y. Choi

    (Hong Kong University of Science and Technology, Hong Kong)

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    Abstract

    A new multivariate stochastic volatility model is developed in this paper. The main feature of this model is to allow threshold asymmetry in a factor covariance structure. The new model provides a parsimonious characterization of volatility and correlation asymmetry in response to market news. Statistical inferences are drawn from Markov chain Monte Carlo methods. We introduce news impact analysis to analyze volatility asymmetry with a factor structure. This analysis helps us to study different responses of volatility to historical market information in a multivariate volatility framework. Our model is successful when applied to an extensive empirical study of twenty stocks. Copyright © 2009 John Wiley & Sons, Ltd.

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    File URL: http://hdl.handle.net/10.1002/for.1123
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    Bibliographic Info

    Article provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.

    Volume (Year): 28 (2009)
    Issue (Month): 8 ()
    Pages: 712-735

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    Handle: RePEc:jof:jforec:v:28:y:2009:i:8:p:712-735

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    Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966

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    Cited by:
    1. Tsunehiro Ishihara & Yasuhiro Omori, 2009. "Efficient Bayesian Estimation of a Multivariate Stochastic Volatility Model with Cross Leverage and Heavy-Tailed Errors," CIRJE F-Series CIRJE-F-700, CIRJE, Faculty of Economics, University of Tokyo.
    2. 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.

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