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http://dx.doi.org/10.5351/KJAS.2013.26.1.163

Value-at-Risk Estimation of the KOSPI Returns by Employing Long-Memory Volatility Models  

Oh, Jeongjun (Department of Statistics, University of Seoul)
Kim, Sunggon (Department of Statistics, University of Seoul)
Publication Information
The Korean Journal of Applied Statistics / v.26, no.1, 2013 , pp. 163-185 More about this Journal
Abstract
In this paper, we investigate the need to employ long-memory volatility models in terms of Value-at-Risk(VaR) estimation. We estimate the VaR of the KOSPI returns using long-memory volatility models such as FIGARCH and FIEGARCH; in addition, via back-testing we compare the performance of the obtained VaR with short memory processes such as GARCH and EGARCH. Back-testing says that there exists a long-memory property in the volatility process of KOSPI returns and that it is essential to employ long-memory volatility models for the right estimation of VaR.
Keywords
VaR estimation; long-memory; volatility model; FIGARCH; FIEGARCH;
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Times Cited By KSCI : 1  (Citation Analysis)
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