A Reexamination of Finite- and Infinite-Variance Distributions as Models of Daily Stock Returns

Alan L Tucker

Journal of Business & Economic Statistics, 1992, vol. 10, issue 1, 73-81

Abstract: This study investigates the general (asymmetric) stable Paretian distribution and three finite-variance, time-independent distributions applied to daily stock-return series. Previous empirical comparisons have, in general, ignored the existence and effects of skewness on the process parameters of stable laws. The results of log-likelihood ratio and log-odds tests indicate that finite-variance models still dominate after accounting for documented skewness. In particular, the mixed diffusion-jump and compound normal models appear to be the most descriptive time-independent models.

Date: 1992
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Persistent link: https://EconPapers.repec.org/RePEc:bes:jnlbes:v:10:y:1992:i:1:p:73-81

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