The Meixner distribution is a special case of the generalized z-distributions. Its properties make it potentially very useful in modeling short-term financial returns. This article proposes an algorithm to simulate the Meixner distribution, and shows how to obtain maximum likelihood estimators of its parameters. A GARCH-type model is then assessed, assuming that the innovation distribution is a standardized Meixner. Goodness-of-fit properties are investigated for some real financial time series, using bootstrap tests based on the empirical process of the residuals.

Simulation and estimation of the Meixner distribution

GRIGOLETTO, MATTEO;PROVASI, CORRADO
2009

Abstract

The Meixner distribution is a special case of the generalized z-distributions. Its properties make it potentially very useful in modeling short-term financial returns. This article proposes an algorithm to simulate the Meixner distribution, and shows how to obtain maximum likelihood estimators of its parameters. A GARCH-type model is then assessed, assuming that the innovation distribution is a standardized Meixner. Goodness-of-fit properties are investigated for some real financial time series, using bootstrap tests based on the empirical process of the residuals.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/2442232
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