Graduate School of Economics, University of Tokyo
University of Tokyo
抄録
An efficient Bayesian estimation using a Markov chain Monte Carlo methodis proposed in the case of a multivariate stochastic volatility model as anatural extension of the univariate stochastic volatility model with leverageand heavy-tailed errors. Note that we further incorporate cross-leverageeffects among stock returns. Our method is based on a multi-move samplerthat samples a block of latent volatility vectors. The method is presentedas a multivariate stochastic volatility model with cross leverage and heavytailederrors. Its high sampling efficiency is shown using numerical examplesin comparison with a single-move sampler that samples one latent volatilityvector at a time, given other latent vectors and parameters. To illustrate themethod, empirical analyses are provided based on five-dimensional S&P500sector indices returns.
内容記述
Revised version of CIRJE-F-690 (2009) and CIRJE-F-700 (2009), forthcoming in Computational Statistics and Data Analysis.
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雑誌名
Discussion paper series. CIRJE-F
巻
CIRJE-F-746
発行年
2010-05
書誌レコードID
AA11450569
フォーマット
application/pdf
日本十進分類法
335
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
Efficient Bayesian Estimation of a Multivariate Stochastic Volatility Model with Cross Leverage and Heavy-Tailed Errors
