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Matrix Exponential Stochastic Volatility with Cross Leverage

Listed author(s):
  • Tsunehiro Ishihara

    (Department of Economics, Hitotsubashi University,)

  • Yasuhiro Omori

    (Faculty of Economics, The University of Tokyo)

  • Manabu Asai

    (Faculty of Economics, Soka University)

   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 conditional posterior distribution, where we construct the proposal density based on an approximating linear Gaussian state space model. The proposed model and its extended 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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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
Handle: RePEc:tky:fseres:2013cf904
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