基于小波变换的长记忆随机波动模型估计方法研究

摘要/Abstract

摘要： 根据ARFIMA过程的小波分析结果,将小波引入到长记忆随机波动(Long Memory Stochastic Volatility)LMSV模型的估计中,提出了基于小波变换的LMSV模型的参数估计和潜在波动过程的估计方法.用不同参数值和样本容量的数据进行了模拟实验,又用该方法对上海和深圳证券交易所综合指数的收益序列拟合了LMSV模型,结果表明该方法是有效且可行的.

关键词: 小波变换, LMSV模型, ARFIMA过程, 估计

Abstract: Wavelet is introduced to the estimation of the Long Memory Stochastic Volatility(LMSV)model,and the wavelet transformation based estimation method of parameters and volatility process is proposed on the bases of the wavelet analysis results of ARFIMA process.The method suggested is proved to be effective and feasible by the simulation experiments with different parameters value and different series length as well as the estimation of LMSV model of the return series of aggregate index of Shanghai and Shenzhen stock markets.

Key words: wavelet transformation, LMSV model, ARFIMA process, estimation

中图分类号:

F224

徐梅, 张世英. 基于小波变换的长记忆随机波动模型估计方法研究[J]. 中国管理科学, 2006, (1): 7-14.

XU Mei, ZHANG Shi-ying. Study on the Wavelet Transformation Based Estimation Method of LMSV Model[J]. Chinese Journal of Management Science, 2006, (1): 7-14.

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