Approximating the probability distribution of functions of random variables: A new approach

Eric Ghysels () and Anders Eriksson Lars Forsberg

No 503, Econometric Society 2004 Far Eastern Meetings from Econometric Society

Abstract: We introduce a new approximation method for the distribution of functions of random variables that are real-valued. The approximation involves moment matching and exploits properties of the class of normal inverse Gaussian distributions. In the paper we we examine the how well the different approximation methods can capture the tail behavior of a function of random variables relative each other. This is obtain done by simulate a number functions of random variables and then investigate the tail behavior for each method. Further we also focus on the regions of unimodality and positive definiteness of the different approximation methods. We show that the new method provides equal or better approximations than Gram-Charlier and Edgeworth expansio

Keywords: Approximation; of; random; variables (search for similar items in EconPapers)
JEL-codes: C0 C1 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm
Date: 2004-08-11
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http://repec.org/esFEAM04/up.23912.1077883072.pdf (application/pdf)

Related works:
Working Paper: Approximating the Probability Distribution of Functions of Random Variables: A New Approach (2004)
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Persistent link: http://EconPapers.repec.org/RePEc:ecm:feam04:503

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