[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.7465/jkdi.2016.27.6.1661

The GARCH-GPD in market risks modeling: An empirical exposition on KOSPI

Atsmegiorgis, Cheru (Department of Statistics, Daegu University)
Kim, Jongtae (Department of Computer Science and Statistics)
Yoon, Sanghoo (Department of Computer Science and Statistics)

Publication Information

Journal of the Korean Data and Information Science Society / v.27, no.6, 2016 , pp. 1661-1671 More about this Journal

Abstract

Risk analysis is a systematic study of uncertainties and risks we encounter in business, engineering, public policy, and many other areas. Value at Risk (VaR) is one of the most widely used risk measurements in risk management. In this paper, the Korean Composite Stock Price Index data has been utilized to model the VaR employing the classical ARMA (1,1)-GARCH (1,1) models with normal, t, generalized hyperbolic, and generalized pareto distributed errors. The aim of this paper is to compare the performance of each model in estimating the VaR. The performance of models were compared in terms of the number of VaR violations and Kupiec exceedance test. The GARCH-GPD likelihood ratio unconditional test statistic has been found to have the smallest value among the models.

Keywords

ARMA; GARCH; GARCH-GPD; KOSPI; Value at Risk;

Citations & Related Records

Times Cited By KSCI : 7 (Citation Analysis)

Reference
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