A Model for Stock Return Distribution
AbstractThe Laplace mixture distribution for stock share returns is derived from conditional N(0, sigma-squared) distribution. The conditioning variable, sigma-squared, is assumed to be an exponentially distributed random variable. This offers a natural stochastic interpretation of the risk involved with the stock share. Maximum likelihood (ML) estimates for returns of the 20 most traded shares and the aggregate index of the Helsinki stock market in late 1980s do not reject the Laplace distribution model. The results extend to returns over longer periods than 1 day. Copyright @ 2001 by John Wiley & Sons, Ltd. All rights reserved.
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Bibliographic InfoArticle provided by John Wiley & Sons, Ltd. in its journal International Journal of Finance & Economics.
Volume (Year): 6 (2001)
Issue (Month): 2 (April)
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Web page: http://www.interscience.wiley.com/jpages/1076-9307/
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