Modeling Maximum Entropy Distributions for Financial Returns by Moment Combination and Selection

Yi-Ting Chen

Journal of Financial Econometrics, 2015, vol. 13, issue 2, 414-455

Abstract: In empirical finance, conditional distributions of financial returns are often established by specifying the standardized error distributions of GARCH-type models. In this article, we apply the maximum entropy (MaxEnt) approach and propose a moment combination and selection method to explore this distribution-building problem. We demonstrate that this framework is useful for unifying and comparing existing distribution specifications, generating more suitable distribution spec-ifications, and shedding light on the roles of different moments in the distribution-building process. We also show the applicability of our method to real data by means of an empirical study on stock index returns.

Keywords: GARCH-type models; maximum entropy; moment combination; moment selection; standardized error distribution (search for similar items in EconPapers)
JEL-codes: C40 C52 G15 (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (1)

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