Matrix Exponential Stochastic Volatility with Cross Leverage

Tsunehiro Ishihara, Yasuhiro Omori () and Manabu Asai

No CIRJE-F-932, CIRJE F-Series from CIRJE, Faculty of Economics, University of Tokyo

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 definite 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 and diagonal multivariate GARCH models.

Pages: 42 pages
Date: 2014-05
New Economics Papers: this item is included in nep-ets and nep-ore
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Citations: View citations in EconPapers (13)

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Related works:
Journal Article: Matrix exponential stochastic volatility with cross leverage (2016)
Working Paper: Matrix Exponential Stochastic Volatility with Cross Leverage (2013)
Working Paper: Matrix Exponential Stochastic Volatility with Cross Leverage (2011)
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