• 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.

• International Area Studies Review
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• v.20 no.3
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• pp.123-144
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• 2016

This paper investigates the linkages between returns both in foreign exchange and stock markets, and uncertainties in two markets using daily data for the period of 16 July 2004 to 30 June 2014 in Nepalese economy. Four hypotheses are tested about how uncertainty influences the stock index and exchange rates. From the empirical results, a bivariate EGARCH-M model is the best to explain the volatility in the two markets. There is a negative relationship from the exchange rates return to stock price return. Empirical results do provide strong empirical confirmation that negative effect of stock index uncertainty and positive effect of exchange rates uncertainty on average stock index. GARCH-in-mean variables in AR modeling are significant and shows that there is positive effect of exchange rates uncertainty and negative effect of stock index uncertainty on average exchange rates. Stock index shocks have longer lived effects on uncertainty in the stock market than exchange rates shock have on uncertainly in the foreign exchange market. The effect of the last period's shock, volatility is more sensitive to its own lagged values.

• 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.

• International Area Studies Review
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• v.14 no.1
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• pp.55-76
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• 2010

This paper analyses interaction between yen/dollar exchange rates and NIKKEI index using bivariate GJR-GARCH(1,1) model. The data employed for the study is daily data series for the period of Jan. 4, 1995 through Aug. 30, 2009. One of main findings is that market inefficiency appears in the periods of financial crisis. Second, the volatility of exchange rates and stock returns has more increased in the wake of the volatility shock of the previous period during financial crisis than during non-financial crisis. Third, interestingly, the asymmetric volatility shock by bad news in those markets is bigger in financial crisis period than in non financial crisis. Fourth, in the period of current global financial crisis triggered by subprime mortgage crisis in U.S, volatility shock at the previous period is bigger than that of Asian financial crisis that happened in 1997. Lastly, the correlation between both returns of exchange rates and stock prices turns up positive according to the empirical estimation. This result may come from the fact that Japanese stock market does not have much attraction for international financial investment compared to stock markets of neighbouring countries like China, Korea and so on, while real sector's contribution to the economy is considered more importantly.

• 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.

• The Korean Journal of Financial Management
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• v.23 no.1
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• pp.243-266
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• 2006

This paper tests cross hedging performance of the KOSPI 200 stock index futures to hedge the downside risk of the KOSPI, KOSPI 200 and KOSDAQ50 spot market. For this purpose we introduce the minimum variance hedge model, bivariate GARCH(1,1) and EGARCH(1,1) model as hedge models. The main results are as follows; First, we find that the direct hedge performance of KOSPI 200 index futures is better than those of indirect hedge performance. second, in case or cross hedge performance the hedge effect of KOSPI 200 stock index futures market against KOSPI 200 stock index spot market is relatively better than those of KOSPI 200 index futures against KOSPI and KOSDAQ spot position. Third, for the out-sample, hedging effectiveness of the risk-minimization with constant hedge ratios is higher than those of the time varying bivariate GARCH(1,1) and EGARCH(1,1) model. In conclusion, investors are encouraged to use simple risk-minimization model rather than the time varying hedge models like GARCH and EGARCH model to hedge the position of the Korean stock index cash 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.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.8
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• pp.297-309
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• 2021

In this study, to capture the skewness and kurtosis detected in both conditional and unconditional return distributions of the stock markets of Kazakhstan and Russia, two versions of normal mixture GARCH models are employed. The data set consists of daily observations of the Kazakhstan and Russia stock prices, and world crude oil price, covering the period from 1 June 2006 through 1 March 2021. From the empirical results, incorporating the long memory effect on the returns not only provides better descriptions of dynamic behaviors of the stock market prices but also plays a significant role in improving a better understanding of the return dynamics. In addition, normal mixture models for time-varying volatility provide a better fit to the conditional densities than the usual GARCH specifications and has an important advantage that the conditional higher moments are time-varying. This implies that the volatility skews implied by normal mixture models are more likely to exhibit the features of risk and the direction of the information flow is regime-dependent. The findings of this study contain useful information for diverse purposes of cross-border stock market players such as asset allocation, portfolio management, risk management, and market regulations.

• Communications for Statistical Applications and Methods
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• v.30 no.1
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• pp.75-94
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• 2023

The growing trend of cyber risk has put forward the importance of cyber risk management. Cyber risk is defined as an accidental or intentional risk related to information and technology assets. Although cyber risk is a subset of operational risk, it is reported to be handled differently from operational risk due to its different features of the loss distribution. In this study, we aim to detect the characteristics of cyber loss and find a suitable model by measuring value at risk (VaR). We use the loss distribution approach (LDA) and the time series model to describe cyber losses of financial and non-financial business sectors, provided in SAS^® OpRisk Global Data. Peaks over threshold (POT) method is also incorporated to improve the risk measurement. For the financial sector, the LDA and GARCH model with POT perform better than those without POT, respectively. The same result is obtained for the non-financial sector, although the differences are not significant. We also build a two-dimensional model reflecting the dependence structure between financial and non-financial sectors through a bivariate copula and check the model adequacy through VaR.

• The Korean Journal of Financial Management
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• v.23 no.1
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• pp.49-67
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• 2006

This study examines whether won/dollar futures have price discovery function and volatility spillover effect or not, using intraday won/dollar futures prices, volumes, and spot rates for the interval from March 2, 2005 through May 30, 2005. Futures prices and spot rates are non-stationary, but there is the cointegration relationship between two time series. Futures returns, spot returns, and volumes are stationary. Asymmetric effects on volatility in futures returns and spot returns does not exist. Analytical results of mean equations of the BGARCH-EC (bivariate GARCH-error correction) model show that the increase of futures returns raise spot returns after 5 minutes, which implies that futures returns lead spot returns and won/dollar futures have price discovery function. In addition, the long-run equilibrium relationship between the two returns could help forecast spot returns. Analytical results of variance equations indicate that short-run innovations in the futures market positively affect the conditional variances of spot returns, that is, there is the volatility spillover effect in the won/dollar futures market. A dummy variable of volumes does not have an effect on two returns but influences significantly on two conditional variances.