• 무역학회지
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• 제47권1호
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• pp.99-114
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• 2022

This paper analyzed the dynamic conditional correlation between the carbon emission trading prices of Korea, China, EU, New Zealand. This paper was analyzed using the daily data of carbon emission trading prices of each country from January 12, 2015 to January 13, 2021 using the DCC-GARCH model. Summarizing the research results, first, the dynamic conditional correlation between carbon emission trading prices in the EU, Korea, and China, excluding New Zealand, was strong, indicating that there was a co-movement phenomenon. Second, it was found that carbon emission trading prices in major countries have a stronger tendency to co-movement due to global shocks. Third, it appears that the dynamic conditional correlation between the carbon emission trading prices of Korea and China is gradually strengthening. This study confirmed that the co-movement between carbon emission trading prices in Korea and other countries gradually intensified as time passed. In particular, it is meaningful in suggesting the implication that the phenomenon of co-movement between carbon emission trading prices in Korea and China is gradually intensifying.

• 재무관리연구
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• 제26권3호
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• pp.199-226
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• 2009

본 논문은 우리나라 주식시장과 외환시장의 기대 수익률과 조건부 변동성간의 시계열적 관계를 2요인 자본자산가격결정모형(two-factor ICAPM)을 이용하여 실증 분석하였다. 주가와 환율의 조건부 분산은 GARCH 모형과 비대칭성을 반영한 GJR(1993) 모형으로 추정하였으며, 주가와 환율과의 조건부 공분산은 Bollerslev(1990)의 일정 상관관계(CCC) 모형과 Engle(2002)의 동태적 조건부상관관계(DCC) 모형을 이용하여 추정하였다. 실증 분석모형은 MGARCH-M 모형을 사용하였으며, 추정방법은 준최우추정법(QMLE)을 사용하였다. 실증 분석결과 외환위기 이후에 주식시장의 기대 수익률은 주가의 분산에 대해, 그리고 환율과의 공분산에 대해 유의한 음(-)의 관계를 갖는 것으로 나타났다. 그러나 외환시장에서 기대 수익률은 조건부 분산과 조건부 공분산에 대해 유의하지 않은 것으로 나타났다. 조건부 분산의 추정에서는 GJR 모형이 GARCH 모형에 비해 더 적합한 것으로 나타났다. 그리고 DCC 모형이 CCC 모형에 비해 설명력이 더 높은 것으로 나타났다. 본 논문의 분석결과는 주식시장에서 환율 변동이 위험 요인으로 작용하고 있기 때문에 포트폴리오 구성이나 위험 관리 등에서 환율 변동을 고려할 필요가 있고, 변수들간의 상관관계는 시변하는 모형을 사용할 필요가 있음을 시사한다.

• The Journal of Asian Finance, Economics and Business
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• 제8권9호
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• pp.143-154
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• 2021

This study aims to explore the dynamic conditional correlation (DCC) between ten Asian stock indexes, the US stock index, and Bitcoin by using the dynamic conditional correlation model. The time span of the daily data is between January 2015 to May 2021, the total observation is 1,116. DCC(1,1)-EGARCH(1,1) with multivariate t and normal distributions for the DCC and EGARCH models, respectively, outperforms other models by the goodness of fit values. Except for Bitcoin, we discovered that the majority of the securities' volatilities have a very high volatility persistence. Furthermore, the negative shocks/news have more impact on the volatilities than positive shocks/news in most of the cases, except the stock index of China and Bitcoin. Most of the correlation pairs exhibit higher correlation during the COVID-19 pandemic compared to the pre-COVID-19, except Hong Kong-The US and Malaysia-Indonesia. Moreover, the correlation between Asian stock indexes during the COVID-19 pandemic is statistically higher than the pre-COVID-19 pandemic. However, there are a few instances where the Hong Kong stock index and a few countries are identical. The result of correlation size shows the connectedness between Asian stock markets, which are well-connected within the region, especially with South Korea, Singapore, and Hong Kong.

• Communications for Statistical Applications and Methods
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• 제21권5호
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• pp.445-459
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• 2014

This paper investigates the dependence structure of Korean financial markets (stock, foreign exchange (FX) rates and bond) using copula-GARCH and dynamic conditional correlation (DCC) models. We examine GJR-GARCH with skewed elliptical distributions and four copulas (Gaussian, Student's t, Clayton and Gumbel) to model dependence among returns, and then employ DCC model to describe system-wide correlation dynamics. We analyze the daily returns of KOSPI, FX (WON/USD) and KRX bond index (Gross Price Index) from $2^{nd}$ May 2006 to $30^{th}$ June 2014 with 2,063 observations. Empirical result shows that there is significant asymmetry and fat-tail of individual return, and strong tail-dependence among returns, especially between KOSPI and FX returns, during the 2008 Global Financial Crisis period. Focused only on recent 30 months, we find that the correlation between stock and bond markets shows dramatic increase, and system-wide correlation wanders around zero, which possibly indicates market tranquility from a systemic perspective.

• Communications for Statistical Applications and Methods
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• 제21권4호
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• pp.335-347
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• 2014

This paper employs dynamic conditional correlation (DCC) model to examine time-varying comovement in the Korean stock market with a focus on the financial industry. Analyzing the daily returns of KOSPI 200 eight sector indices from January 2008 to December 2013, we find that stock market correlations significantly increased during the GFC period. The Financial Sector had the highest correlation between the Constructions-Machinery Sector; however, the Consumer Discretionary and Consumer Staples sectors indicated a relatively lower correlation between the Financial Sector. In terms of model fitting, the DCC with t distribution model concludes as the best among the four alternatives based on BIC, and the estimated shape parameter of t distribution is less than 10, implicating a strong tail dependence between the sectors. We report little asymmetric effect in correlation dynamics between sectors; however, we find strong asymmetric effect in volatility dynamics for each sector return.

• 응용통계연구
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• 제28권5호
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• pp.1013-1024
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• 2015

본 논문에서는 다변량 DCC(dynamic conditional correlation) GARCH 모형에서 동태적 상관계수를 추정하기 위한 대표적 방법인 쌍별 추정법과 다차원 추정법의 효율성을 비교한다. 이를 위하여 금융 시장의 변동성을 반영하는 다변량 시계열을 생성하고 이에 대한 DCC GARCH 모형을 수립 및 추정하는 시뮬레이션을 실시하였다. 또한 KOSPI 200 섹터지수를 이용하여 포트폴리오를 구성하고 이의 변동성 추정 및 VaR 계산을 통하여 동태적 상관계수 추정에 대한 정확성을 평가하였다. 그 결과로서, 전반적으로 다차원 추정법이 쌍별 추정법보다 우수함을 발견하였다. 특히, 다차원 추정법에서 상대적으로 상관관계가 낮은 시계열을 추가할수록 쌍별 시계열에 대한 동태적 상관계수 추정의 정확성을 높여줌을 발견하였다.

• The Journal of Asian Finance, Economics and Business
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• 제8권12호
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• pp.465-471
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• 2021

The study investigates the dynamic correlation of cryptocurrencies and equity in Vietnam and tests the safe-haven property of them from the perspective of the stock market in Vietnam during the pandemic crisis by applying the dynamic conditional correlation (DCC) GARCH model and regression with a dummy variable, respectively. This study employs time series data on the daily dataset from September 2014 to September 2021 with the focus on the two most popular cryptocurrencies - Bitcoin and Litecoin. The results show that the dynamic conditional correlations between cryptocurrencies and equity in Vietnam increased during the pandemic, however, in most periods, positive dynamic correlations often dominate. Besides, the regression results also indicate that Bitcoin and Litecoin act as weak safe-haven investments for stocks in Vietnam during the COVID-19 turmoil. They are more suitable for diversification purposes although the dynamic correlations between them and the stock index in Vietnam vary stronger during the pandemic crisis than before. The findings of this study suggest that in the period of pandemic crisis, cryptocurrencies are not concerned as effective safe-haven assets for stock in Vietnam. Instead, cryptocurrencies are only playing a potential role in diversification benefit in this economy.

• 무역학회지
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• 제47권3호
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• pp.141-156
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• 2022

This study intends to examine the regional blocs of the international crude oil futures market by analyzing the dynamic conditional correlation between the international crude oil futures markets using the DCC-GARCH model. For statistical data, from April 2, 2018 to March 31, 2022, international crude oil futures prices such as Europe, the United States, China, and Dubai were used. To summarize the results of the study, first, the phenomenon of regional blocs in the international crude oil futures market is occurring, and it is found that it is gradually strengthening as time goes by. Second, it was found that the dynamic correlation of the international crude oil futures market is temporarily strengthened when a supply-demand imbalance problem occurs due to a global shock. Third, it was found that the volatility of the Chinese crude oil futures market affects the international crude oil futures market. This study confirmed that the regional blocs phenomenon in the international crude oil futures market is strengthened as time goes by. In particular, it suggested that China's influence in the international oil market would increase.

• ETRI Journal
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• 제43권3호
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• pp.538-548
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• 2021

This paper proposes an approach to improve the performance of no-reference video quality assessment for sports videos with dynamic motion scenes using an efficient spatiotemporal model. In the proposed method, we divide the video sequences into video blocks and apply a 3D shearlet transform that can efficiently extract primary spatiotemporal features to capture dynamic natural motion scene statistics from the incoming video blocks. The concatenation of a deep residual bidirectional gated recurrent neural network and logistic regression is used to learn the spatiotemporal correlation more robustly and predict the perceptual quality score. In addition, conditional video block-wise constraints are incorporated into the objective function to improve quality estimation performance for the entire video. The experimental results show that the proposed method extracts spatiotemporal motion information more effectively and predicts the video quality with higher accuracy than the conventional no-reference video quality assessment methods.

• East Asian Economic Review
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• 제19권4호
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• pp.357-379
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• 2015

We investigate interconnectedness and the contagion effect of default risk in Asian sovereign CDS markets since the global financial crisis. Using dynamic conditional correlation analysis, we find that there are significant co-movements in Asian sovereign CDS markets; that such co-movements tend to be larger between developing countries than between developed and developing countries; and that in the co-movements intra-regional nature is stronger than inter-regional nature. With the Spillover Index model, we measure contagion probabilities of sovereign default risk in CDS markets of seven Asian countries and find evidence of contagion effects among six of them; Japan is the exception. In addition, we find that these six countries are affected more by cross-market spillovers than by their own-market spillovers. Furthermore, a rolling-sample analysis reveals that contagion in the Asian sovereign CDS markets expands during episodes of extreme economic and financial distress, such as the Lehman Brothers bankruptcy, the European financial crisis, and the US-credit downgrade.