Comparing the accuracy of density forecasts from competing GARCH models

Ahmed Shamiri (), Abu Hassan Shaari and Zaidi Isa

MPRA Paper from University Library of Munich, Germany

Abstract: In this paper we introduce an analyzing procedure using the Kullback-Leibler information criteria (KLIC) as a statistical tool to evaluate and compare the predictive abilities of possibly misspecified density forecast models. The main advantage of this statistical tool is that we use the censored likelihood functions to compute the tail minimum of the KLIC, to compare the performance of a density forecast models in the tails. Use of KLIC is practically attractive as well as convenient, given its equivalent of the widely used LR test. We include an illustrative simulation to compare a set of distributions, including symmetric and asymmetric distribution, and a family of GARCH volatility models. Our results on simulated data show that the choice of the conditional distribution appears to be a more dominant factor in determining the adequacy and accuracy (quality) of density forecasts than the choice of volatility model.

Keywords: Density; conditional distribution; forecast accuracy; GARCH; KLIC (search for similar items in EconPapers)
JEL-codes: C14 C15 C32 D53 E37 (search for similar items in EconPapers)
Date: 2008
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:13662

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