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中文摘要：
研究了基于小波变换的时变长记忆SV模型参数的估计方法．根据小波变换可将过程分解到不同的尺度上以及长记忆SV过程同一尺度下和不同尺度下DWT系数的近似不相关性，提出了建立局部似然函数的方法．又根据DWT系数和MODWT系数之间的关系，将局部似然函数表示为模型参数和局部小波方差估计的形式．用该方法对中国股市收益进行了时变长记忆SV模型参数的估计．
英文摘要：
The parameters estimation method of time varying long memory SV model based on wavelet transformation is studied. In terms of the fact that wavelet transformation can decompose a process to different scales and the approximate uncorrelation property of DWT coefficients of long memory SV process in the same scale and different scales, a local likelihood function of time varying long memory SV model is set up. Then, according to the relationship between DWT and MODWT coefficients, the local likelihood function of time varying long memory SV model is represented in the form of parameters of the model and estimator of local wavelet variance. The method suggested is applied to the parameters estimation of time varying long memory SV model of return series of China stock markets.
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