• The Korean Journal of Financial Management
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• v.21 no.2
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• pp.183-209
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• 2004

This paper uses both the bivariate GARCH type BEKK error correction model and Bivariate-AR(1)-Markov-Switching-VECM model to estimate the volatility, time-varying correlation and hedge ratio for the KTB spot and futures indexes, sampled daily over 1/4/2000-10/30/2003. This study suggests that the volatility regime has more significant influence on KTB markets than incline/decline regime does. The results support the importance of the bivariate model in stead of univariate model between KTB spot and futures markets, which may consider not only individual variance process but also covariance process at the same time.

• Journal of the Korean Data and Information Science Society
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• v.18 no.4
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• pp.915-925
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• 2007

Multivariate GARCH has been useful to model dynamic relationships between volatilities arising from each component series of multivariate time series. Methodologies including EWMA(Exponentially weighted moving-average model), DVEC(Diagonal VEC model), BEKK and CCC(Constant conditional correlation model) models are comparatively reviewed for bivariate time series. In addition, these models are applied to evaluate VaR(Value at Risk) and to construct joint prediction region. To illustrate, bivariate stock prices data consisting of Samsung Electronics and LG Electronics are analysed.

• The Journal of Fisheries Business Administration
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• v.46 no.3
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• pp.119-127
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• 2015

This study is to analyse the causality and volatility spillover between farming fish species in consumption replacement relation using flatfish(oliver flounder) and rockfish's wholesale market price data from September 2006 to July 2015. For the analysis, VAR(5) model and bivariate asymmetric GARCH-BEKK model are employed. The empirical results of this study are summarized as follows: First, the price volatility of flatfish and rockfish is very large without the trend during the sample period. Second, the correlation coefficient between flatfish and rockfish wholesale markets has positive 0.1059 value. Third, causality relation is unidirectional from rockfish market to flatfish market. Fourth, conditional volatility spillover effect is unidirectional from rockfish market to flatfish market, but asymmetric volatility effect is bidirectional between flatfish and rockfish markets that implies the bad news arising from flatfish wholesale market impact on rockfish market's volatility and the bad news arising from rockfish wholesale market impact on flatfish market's volaltilty. Consequently, based on the thus results, the volatility spillover effect interacts and is bidirectional between flatfish and rockfish wholesale markets.

• Environmental and Resource Economics Review
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• v.22 no.4
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• pp.671-689
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• 2013

Transmission mechanisms of volatility between two crude oil markets (WTI and Brent markets) have drawn the attention of numerous academics and practitioners because they both play crucial roles in portfolio and risk management in crude oil markets. In this context, we examined the volatility linkages between two representative crude oil markets using a VECM and an asymmetric bivariate GARCH model. First, looking at the return transmission through the VECM test, we found a long-run equilibrium and bidirectional relationship between two crude oil markets. However, the estimation results of the GARCH-BEKK model suggest that there is unidirectional volatility spillover from the WTI market to the Brent market, implying that the WTI market tends to exert influence over the Brent market and not vice versa. Regarding asymmetric volatility transmission, we also found that bad news volatility in the WTI market increases the volatility of the Brent market. Thus, WTI information is transmitted into the Brent market, indicating that the prices of the WTI market seem to lead the prices of the Brent market.