Comparing the accuracy of density forecasts from competing GARCH models

In this research 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...

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Main Authors: Abu Hassan Shaari Mohd Nor, Ahmad Shamiri, Zaidi Isa
Format: Article
Language:English
Published: Universiti Kebangsaan Malaysia 2009
Online Access:http://journalarticle.ukm.my/77/
http://journalarticle.ukm.my/77/1/
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author Abu Hassan Shaari Mohd Nor,
Ahmad Shamiri,
Zaidi Isa,
author_facet Abu Hassan Shaari Mohd Nor,
Ahmad Shamiri,
Zaidi Isa,
author_sort Abu Hassan Shaari Mohd Nor,
building UKM Institutional Repository
collection Online Access
description In this research 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.
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spelling ukm-772016-12-14T06:26:20Z http://journalarticle.ukm.my/77/ Comparing the accuracy of density forecasts from competing GARCH models Abu Hassan Shaari Mohd Nor, Ahmad Shamiri, Zaidi Isa, In this research 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. Universiti Kebangsaan Malaysia 2009-02 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/77/1/ Abu Hassan Shaari Mohd Nor, and Ahmad Shamiri, and Zaidi Isa, (2009) Comparing the accuracy of density forecasts from competing GARCH models. Sains Malaysiana, 38 (1). pp. 109-118. ISSN 0126-6039 http://www.ukm.my/~jsm/utama.html
spellingShingle Abu Hassan Shaari Mohd Nor,
Ahmad Shamiri,
Zaidi Isa,
Comparing the accuracy of density forecasts from competing GARCH models
title Comparing the accuracy of density forecasts from competing GARCH models
title_full Comparing the accuracy of density forecasts from competing GARCH models
title_fullStr Comparing the accuracy of density forecasts from competing GARCH models
title_full_unstemmed Comparing the accuracy of density forecasts from competing GARCH models
title_short Comparing the accuracy of density forecasts from competing GARCH models
title_sort comparing the accuracy of density forecasts from competing garch models
url http://journalarticle.ukm.my/77/
http://journalarticle.ukm.my/77/
http://journalarticle.ukm.my/77/1/