Gram Charlier and Edgeworth Expansion for Sample Variance

14 Pages Posted: 11 Oct 2018

See all articles by Eric Benhamou

Eric Benhamou

A.I. Square Connect; LAMSADE- Paris Dauphine University

Date Written: September 18, 2018

Abstract

In this paper, we derive a valid Edgeworth expansions for the Bessel corrected empirical variance when data are generated by a strongly mixing process whose distribution can be arbitrarily. The constraint of strongly mixing process makes the problem not easy. Indeed, even for a strongly mixing normal process, the distribution is unknown. Here, we do not assume any other assumption than a sufficiently fast decrease of the underlying distribution to make the Edgeworth expansion convergent. This results can obviously apply to strongly mixing normal process and provide an alternative to the work of Moschopoulos (1985) and Mathai (1982).

Keywords: sample variance, Edgeworth expansion

Suggested Citation

Benhamou, Eric, Gram Charlier and Edgeworth Expansion for Sample Variance (September 18, 2018). Available at SSRN: https://ssrn.com/abstract=3251324 or http://dx.doi.org/10.2139/ssrn.3251324

Eric Benhamou (Contact Author)

A.I. Square Connect ( email )

35 Boulevard d'Inkermann
Neuilly sur Seine, 92200
France

LAMSADE- Paris Dauphine University ( email )

Place du Marechal de Lattre de Tassigny
Pais, 75016
France

HOME PAGE: http://https://www.lamsade.dauphine.fr/

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