Center for the Study of Finance and Insurance, Osaka University
Faculty of Economics, University of Tokyo
抄録
A multivariate stochastic volatility model with dynamic equicorrelation and cross leverage effect is proposed and estimated. Using a Bayesian approach, an efficient Markov chain Monte Carlo algorithm is described where we use the multi-move sampler, which generates multiple latent variables simultaneously. Numerical examples are provided to show its sampling efficiency in comparison with the simple algorithm that generates one latent variable at a time given other latent variables. Furthermore, the proposed model is applied to the multivariate daily stock price index data. The empirical study shows that our novel model provides a substantial improvement in forecasting with respect to out-of-sample hedging performances.
内容記述
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雑誌名
Discussion paper series. CIRJE-F
巻
CIRJE-F-907
発行年
2013-11
書誌レコードID
AA11450569
フォーマット
application/pdf
出版者
日本経済国際共同センター
出版者別名
Center for International Research on the Japanese Economy
Dynamic Equicorrelation Stochastic Volatility
