偏正态随机波动模型及其实证检验
发布时间：2018-07-23 17:21
【摘要】：首先构建了有杠杆效应的随机波动模型(SV-L),证明了其波动随机项的条件分布为两个偏正态分布,由此称该模型为偏正态随机波动模型(SV-SN).接下来讨论了SV-SN模型的经济含义以及对应随机波动项的统计特征.最后利用沪深两市的指数收益数据对模型进行了实证研究,其结论为:相对于一般的SV模型,SV-SN模型的拟合效果更好;新息具有减弱后期波动之效应;与理论预期一致,单位负新息比单位正新息引致的波动要大.
[Abstract]:Firstly, a stochastic volatility model with leverage effect (SV-L) is constructed. It is proved that the conditional distribution of the random term is two partial normal distributions, and the model is called the biased stochastic volatility model (SV-SN). Then the economic meaning of the SV-SN model and the statistical characteristics of the corresponding stochastic volatility are discussed. Finally, using the index income data of Shanghai and Shenzhen stock markets, the paper makes an empirical study on the model. The conclusions are as follows: compared with the general SV model, the SV-SN model has better fitting effect; the innovation has the effect of weakening the fluctuation in the later stage; it is in line with the theoretical expectation. The unit of negative innovation is more volatile than the unit of positive innovation.
【作者单位】： 上海立信会计学院金融学院;上海交通大学管理学院;
【基金】：上海市教委高水平特色发展资助项目(JRXY0903) 上海市教委科研创新重点资助项目(09ZS203)
【分类号】：F224.9;F830.91
[Abstract]:Firstly, a stochastic volatility model with leverage effect (SV-L) is constructed. It is proved that the conditional distribution of the random term is two partial normal distributions, and the model is called the biased stochastic volatility model (SV-SN). Then the economic meaning of the SV-SN model and the statistical characteristics of the corresponding stochastic volatility are discussed. Finally, using the index income data of Shanghai and Shenzhen stock markets, the paper makes an empirical study on the model. The conclusions are as follows: compared with the general SV model, the SV-SN model has better fitting effect; the innovation has the effect of weakening the fluctuation in the later stage; it is in line with the theoretical expectation. The unit of negative innovation is more volatile than the unit of positive innovation.
【作者单位】： 上海立信会计学院金融学院;上海交通大学管理学院;
【基金】：上海市教委高水平特色发展资助项目(JRXY0903) 上海市教委科研创新重点资助项目(09ZS203)
【分类号】：F224.9;F830.91
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