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A Long-Memory Property of Stock Market Returns and a New Model (1993)
| Venue: | Journal of Empirical Finance |
| Citations: | 629 - 18 self |
BibTeX
@ARTICLE{Ding93along-memory,
author = {Zhuanxin Ding and Clive W. J. Granger and Robert F. Engle},
title = {A Long-Memory Property of Stock Market Returns and a New Model},
journal = {Journal of Empirical Finance},
year = {1993},
pages = {83--106}
}
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Abstract
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 them-selves, but the power transformation of the absolute return lrfl ” also has quite high autocorrel-ation for long lags. It is possible to characterize lrfld 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 6 of the heteroskedasticity equation to be estimated from the data. 1.
Keyphrases
stock market return new model long-memory property absolute return arch type model long lag squared return power transformation new general class arch type specification long memory heteroskedasticity equation high autocorrel-ation return them-selves monte-carlo study long memory property absolute return lrfl
