| 基于贝叶斯原理的随机波动率模型分析及其应用 |
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| 引用本文： | 蒋祥林,王春峰.基于贝叶斯原理的随机波动率模型分析及其应用[J].系统工程,2005,23(10):22-28. |
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| 作者姓名： | 蒋祥林 王春峰 |
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| 作者单位： | 1. 复旦大学,金融研究院,上海,200433
2. 天津大学,金融工程研究中心,天津,300072 |
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| 基金项目： | 国家杰出青年科学基金资助项目（70225002）;上海市哲学社会科学规划资助项目（2005BJB002） |
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| 摘 要： | 基于贝叶斯原理,对随机波动性模型进行研究,并将随机波动率模型应用股市风险价值VaR的估计与预测.针对中国股市数据进行的实证结果表明,与GARCH模型相比,随机波动率模型能更好地描述股票市场回报的异方差和波动率的序列相关性;基于随机波动率的VaR较GARCH模型的VaR具有更高的精度.
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| 关 键 词： | 随机波动率模型 GARCH模型 风险价值 贝叶斯原理 |
| 文章编号： | 1001-4098（2005）10-0022-07 |
| 收稿时间： | 2005-07-04 |
| 修稿时间： | 2005-07-04 |
Stochastic Volatility Models Based Bayesian Method and Their Application |
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| JIANGF Xiang-lin,WANG Chun-feng.Stochastic Volatility Models Based Bayesian Method and Their Application[J].Systems Engineering,2005,23(10):22-28. |
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| Authors: | JIANGF Xiang-lin WANG Chun-feng |
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| Institution: | 1. Institute for Financial Studies Fudan Unversity, Shanghai 200433, China; 2. Center of Finance Engineering Tianjin University,Tianjin 300072,China |
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| Abstract: | Stochastic volatility(SV) models here are investigated based on bayesian method,and are applied to estimate and forcast the Value at Risk(VaR) of the Chinese stock market.Empirical results on Chinese stock market indicate that stochastic volatility model outperforms the ARCH model in capturing the heteroskedasticity and serial correlation of(volatility) of the stock market.VaR based on SV models is more precision than that based on GARCH models. |
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| Keywords: | Stochastic Volatility Model GARCH Models Value at Risk Bayesian Method |
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