偏正態(tài)隨機波動模型及其實證檢驗
發(fā)布時間:2018-07-23 17:21
【摘要】:首先構建了有杠桿效應的隨機波動模型(SV-L),證明了其波動隨機項的條件分布為兩個偏正態(tài)分布,由此稱該模型為偏正態(tài)隨機波動模型(SV-SN).接下來討論了SV-SN模型的經濟含義以及對應隨機波動項的統(tǒng)計特征.最后利用滬深兩市的指數(shù)收益數(shù)據(jù)對模型進行了實證研究,其結論為:相對于一般的SV模型,SV-SN模型的擬合效果更好;新息具有減弱后期波動之效應;與理論預期一致,單位負新息比單位正新息引致的波動要大.
[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.
【作者單位】: 上海立信會計學院金融學院;上海交通大學管理學院;
【基金】:上海市教委高水平特色發(fā)展資助項目(JRXY0903) 上海市教委科研創(chuàng)新重點資助項目(09ZS203)
【分類號】: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.
【作者單位】: 上海立信會計學院金融學院;上海交通大學管理學院;
【基金】:上海市教委高水平特色發(fā)展資助項目(JRXY0903) 上海市教委科研創(chuàng)新重點資助項目(09ZS203)
【分類號】:F224.9;F830.91
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