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Matrix Exponential Stochastic Volatility with Cross Leverage

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  • Tsunehiro Ishihara

    (Department of Economics, Hitotsubashi University,)

  • Yasuhiro Omori

    (Faculty of Economics, The University of Tokyo)

  • Manabu Asai

    (Faculty of Economics, Soka University)

Abstract

   A multivariate stochastic volatility model with the dynamic correlation and the cross leverage effect is described and its efficient estimation method using Markov chain Monte Carlo is proposed. The time-varying covariance matrices are guaranteed to be positive de nite by using a matrix exponential transformation. Of particular interest is our approach for sampling a set of latent matrix logarithm variables from their con- ditional posterior distribution, where we construct the proposal density based on an approximating linear Gaussian state space model. The proposed model and its extend- ed models with fat-tailed error distribution are applied to trivariate returns data (daily stocks, bonds, and exchange rates) of Japan. Further, a model comparison is conducted including constant correlation multivariate stochastic volatility models with leverage.

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Bibliographic Info

Paper provided by CIRJE, Faculty of Economics, University of Tokyo in its series CIRJE F-Series with number CIRJE-F-904.

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Length: 41 pages
Date of creation: Sep 2013
Date of revision:
Handle: RePEc:tky:fseres:2013cf904

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  1. Jun Yu, 2004. "On Leverage in a Stochastic Volatility Model," Econometric Society 2004 Far Eastern Meetings 506, Econometric Society.
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Cited by:
  1. Yuta Kurose & Yasuhiro Omori, 2013. "Dynamic Equicorrelation Stochastic Volatility," CIRJE F-Series CIRJE-F-907, CIRJE, Faculty of Economics, University of Tokyo.

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