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http://dx.doi.org/10.7465/jkdi.2014.25.6.1449

Hedging effectiveness of KOSPI200 index futures through VECM-CC-GARCH model  

Kwon, Dongan (Department of Statistics, Hankuk University of Foreign Studies)
Lee, Taewook (Department of Statistics, Hankuk University of Foreign Studies)
Publication Information
Journal of the Korean Data and Information Science Society / v.25, no.6, 2014 , pp. 1449-1466 More about this Journal
Abstract
In this paper, we consider a hedge portfolio based on futures of underlying asset. A classical way to estimate a hedge ratio for a hedge portfolio of a spot and futures is a regression analysis. However, a regression analysis is not capable of reflecting long-run equilibrium between a spot and futures and volatility clustering in the conditional variance of financial time series. In order to overcome such defects, we analyzed KOSPI200 index and futures using VECM-CC-GARCH model and computed a hedge ratio from the estimated conditional covariance-variance matrix. In real data analysis, we compared a regression and VECM-CC-GARCH models in terms of hedge effectiveness based on variance, value at risk and expected shortfall of log-returns of hedge portfolio. The empirical results show that the multivariate GARCH models significantly outperform a regression analysis and improve hedging effectiveness in the period of high volatility.
Keywords
CC-GARCH; hedge; KOSPI200 futures; KOSPI200 index; VECM;
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Times Cited By KSCI : 2  (Citation Analysis)
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