Leverage, heavy-tails and correlated jumps in stochastic volatility models

被引：60

作者：

Nakajima, Jouchi ^{[2
]}

Omori, Yasuhiro ^{[1
]}

机构：

[1] Univ Tokyo, Fac Econ, Tokyo 1130033, Japan

[2] Bank Japan, Tokyo 1038660, Japan

来源：

COMPUTATIONAL STATISTICS & DATA ANALYSIS | 2009年 / 53卷 / 06期

关键词：

MARGINAL LIKELIHOOD; SIMULATION SMOOTHER; DYNAMICS;

D O I：

10.1016/j.csda.2008.03.015

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Efficient and fast Markov chain Monte Carlo estimation methods for the stochastic volatility model with leverage effects, heavy-tailed errors and jump components, and for the stochastic volatility model with correlated jumps are proposed. The methods are illustrated using simulated data and are applied to analyze daily stock returns data on S&P500 index and TOPIX. Model comparisons are conducted based on the marginal likelihood for various SV models including the superposition model. (c) 2008 Elsevier B.V. All rights reserved.

引用

页码：2335 / 2353

页数：19

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