Properties and Estimation of Asymmetric Exponential Power Distribution

Dongming Zhu and Victoria Zinde-Walsh

Cahiers de recherche from Centre interuniversitaire de recherche en économie quantitative, CIREQ

Abstract: The new distribution class, Asymmetric Exponential Power Distribution (AEPD), proposed in this paper generalizes the class of Skewed Exponential Power Distributions (SEPD) in a way that in addition to skewness introduces different decay rates of density in the left and right tails. Our parametrization provides an interpretable role for each parameter. We derive moments and moment-based measures: skewness, kurtosis, expected shortfall. It is demonstrated that a maximum entropy property holds for the AEPD distributions. We establish consistency, asymptotic normality and efficiency of the maximum likelihood estimators over a large part of the parameter space by dealing with the problems created by non-smooth likelihood function and derive explicit analytical expressions of the asymptotic covariance matrix; where the results apply to the SEPD class they enlarge on the current literature. Finally, we give a convenient stochastic representation of the distribution; our Monte Carlo study illustrates the theoretical results.

Keywords: asymmetric distributions; maximum likelihood estimation (search for similar items in EconPapers)
JEL-codes: C13 C16 (search for similar items in EconPapers)
Pages: 40 pages
Date: 2007
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Related works:
Journal Article: Properties and estimation of asymmetric exponential power distribution (2009)
Working Paper: PROPERTIES AND ESTIMATION OF ASYMMETRIC EXPONENTIAL POWER DISTRIBUTION (2007)
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Persistent link: https://EconPapers.repec.org/RePEc:mtl:montec:13-2007

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