A long memory property of stock market returns and a new model
A long memory property of stock market returns and a new model
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DOI：
10.1017/cbo9780511753978.020
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发表时间：
1993-06
期刊：
影响因子：
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通讯作者：
Zhuanxin Ding;C. Granger;R. Engle
中科院分区：
文献类型：
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作者：
Zhuanxin Ding;C. Granger;R. Engle
本文研究了股票市场收益率的长记忆性。研究发现，绝对收益率之间的相关性不仅远大于收益率本身，而且绝对收益率的幂次转换也与绝对收益率之间的相关性有关。|RT| d对于长滞后也具有相当高的自相关性。可以表征|RT| d是“长记忆”，当d在1附近时，这种特性最强。这一结果似乎反对基于平方收益的非线性类型规范。但我们的蒙特-卡罗研究表明，无论是基于平方收益率的模型还是基于绝对收益率的模型都能产生这种性质。提出了一类新的通用模型，它允许从数据中估计异方差方程的幂δ。
A "long memory" property of stock market returns is investigated in this paper. It is found that not only there is substantially more correlation between absolute returns than returns themselves, but the power transformation of the absolute turn |rt|d also has quite high autocorrelation for long lags. It is possible to characterize |rt|d to be "long memory" and this property is strongest when d is around 1. This result appears to argue against ARCH type specifications based upon squared returns. But our Monte-Carlo study shows that both ARCH type models based on squared returns and those based on absolute return can produce this property. A new general class of models is proposed which allows the power δ of the heteroskedasticity equation to be estimated from the data.