• Title/Summary/Keyword: DCC - GARCH

Search Result 19, Processing Time 0.026 seconds

Analysis of Multivariate-GARCH via DCC Modelling (DCC 모델링을 이용한 다변량-GARCH 모형의 분석 및 응용)

  • Choi, S.M.;Hong, S.Y.;Choi, M.S.;Park, J.A.;Baek, J.S.;Hwang, S.Y.
    • The Korean Journal of Applied Statistics
    • /
    • v.22 no.5
    • /
    • pp.995-1005
    • /
    • 2009
  • Conditional correlation between financial time series plays an important role in risk management, asset allocation and portfolio selection and therefore diverse efforts for modeling conditional correlations in multivariate-GARCH processes have been made in last two decades. In particular, CCC (cf. Bollerslev, 1990) and DCC(dynamic conditional correlation, cf. Engle, 2002) models have been commonly used since they are relatively parsimonious in the number of parameters involved. This article is concerned with DCC modeling for multivariate GARCH processes in comparison with CCC specification. Various multivariate financial time series are analysed to illustrate possible advantages of DCC over CCC modeling.

Performance Comparison of Estimation Methods for Dynamic Conditional Correlation (DCC 모형에서 동태적 상관계수 추정법의 효율성 비교)

  • Lee, Jiho;Seong, Byeongchan
    • The Korean Journal of Applied Statistics
    • /
    • v.28 no.5
    • /
    • pp.1013-1024
    • /
    • 2015
  • We compare the performance of two representative estimation methods for the dynamic conditional correlation (DCC) GARCH model. The first method is the pairwise estimation which exploits partial information from the paired series, irrespective to the time series dimension. The second is the multi-dimensional estimation that uses full information of the time series. As a simulation for the comparison, we generate a multivariate time series similar to those observed in real markets and construct a DCC GARCH model. As an empirical example, we constitute various portfolios using real KOSPI 200 sector indices and estimate volatility and VaR of the portfolios. Through the estimated dynamic correlations from the simulation and the estimated volatility and value at risk (VaR) of the portfolios, we evaluate the performance of the estimations. We observe that the multi-dimensional estimation tends to be superior to pairwise estimation; in addition, relatively-uncorrelated series can improve the performance of the multi-dimensional estimation.

Dependence Structure of Korean Financial Markets Using Copula-GARCH Model

  • Kim, Woohwan
    • Communications for Statistical Applications and Methods
    • /
    • v.21 no.5
    • /
    • pp.445-459
    • /
    • 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.

A Study on the Volatility Transition of Steel Raw Material Transport Market (제철원료 운송시장의 변동성 전이 분석에 대한 연구)

  • Yo-Pyung Hwang;Ye-Eun Oh;Keun-Sik Park
    • Korea Trade Review
    • /
    • v.47 no.4
    • /
    • pp.215-231
    • /
    • 2022
  • Analysis and forecasting of the Baltic Capsize Index (BCI) is important for managing an entity's losses and risks from the uncertainty and volatility of the fast-changing maritime transport market in the future. This study conducted volatility transition analysis through the GARCH model, using BCI which is highly related to steel raw materials. As for the data, 2,385 monthly data were used from March 1999 to March 2021. In this study, after basic statistical analysis, unit root and cointegration test, the GARCH, EGARCH, and DCC-GARCH models were used for volatility transition analysis. As the results of GARCH and EGARCH model, we confirmed that all variables had no autocorrelation between the standardized residuals for error terms and the square of residuals, that the variability of all variables at this time was likely to persist in the future, and that the variability of the time-series error term impact according to Iron ore trade (IoT). In addition, through the EGARCH model, the magnitude convenience of all variables except the Iron ore price (IOP) and Capesize bulk fleet (BCF) variables was greater than the positive value (+). As a result of analyzing the DCC-GARCH (1,1) model, partial linear combinations were confirmed over the entire period. Estimating the effect of variability transition on BCF and C5 with statistically significant linear combinations with BCI confirmed that the impact of BCF on BCI was greater than the impact of BCI itself.

Investigation on the Correlation between the Housing and Stock Markets (주택시장과 주식시장 사이의 상관관계에 관한 연구)

  • Kim, Sang Bae
    • Korea Real Estate Review
    • /
    • v.28 no.2
    • /
    • pp.21-34
    • /
    • 2018
  • The purpose of this study is to investigate the effect of macro-finance variables on the correlation between the housing and stock markets because understanding the nature of time-varying correlations between different assets has important implications on portfolio allocation and risk management. Thus, we adopted the AG-DCC GARCH model to obtain time-varying, conditional correlations. Our sample ranged from January 2004 to November 2017. Our empirical result showed that the coefficients on asymmetric correlation were significantly positive, implying that correlations between the housing and stock markets were significantly higher when changes in the housing price and stock returns were negative. This finding suggested that the housing market has less hedging potential during a stock market downturn, when such a hedging strategy might be necessary. Based on the regression analysis, we found that the term spread had a significantly negative effect on correlations, while the credit spread had a significantly positive effect. This result could be interpreted by the risk premium effect.

The Contagion Effect from U.S. Stock Market to the Vietnamese and the Philippine Stock Markets: The Evidence of DCC - GARCH Model

  • LE, Thao Phan Thi Dieu;TRAN, Hieu Luong Minh
    • The Journal of Asian Finance, Economics and Business
    • /
    • v.8 no.2
    • /
    • pp.759-770
    • /
    • 2021
  • Using a DCC - GARCH model analysis, this paper examines the existence of financial contagion from the U.S. stock market to the Vietnamese and the Philippine stock markets during the global financial crisis and the COVID-19 pandemic crisis. We use daily data from the S&P 500 (U.S.), VN-Index (Vietnam), and the PSEi (the Philippines). As a result, there is no evidence of contagion from the U.S stock market to the Philippine stock market that can be found during global financial crisis, while the Vietnamese market is influenced by this effect. Besides, both these developing stock markets (the Vietnamese and Philippine stock markets) are influenced by the contagion effect in COVID-19 pandemic crisis. Another finding is that the contagion effect during the coronavirus pandemic crisis in Vietnam is smaller than that during the global financial crisis, however, the opposite is the case for the Philippines. It is noticed that the Philippines seems to be more affected by the contagion effect from the COVID-19 pandemic than Vietnam at the time of this study. Because financial contagion is important for monetary policy, asset pricing, risk measurement, and portfolio allocation, the findings in this paper may give some useful information for policymakers and investors.

A Study on the Dynamic Correlation between the Korean ETS Market, Energy Market and Stock Market (한국 ETS시장, 에너지시장 및 주식시장 간의 동태적 상관관계에 관한 연구)

  • Guo-Dong Yang;Yin-Hua Li
    • Korea Trade Review
    • /
    • v.48 no.4
    • /
    • pp.189-208
    • /
    • 2023
  • This paper analyzed the dynamic conditional correlation between the Korean ETS market, energy market and stock market. This paper conducted an empirical analysis using daily data of Korea's carbon credit trading price, WTI crude oil futures price, and KOSPI index from February 2, 2015 to December 30, 2021. First, the volatility of the three markets was analyzed using the GARCH model, and then the dynamic conditional correlations between the three markets were studied using the bivariate DCC-GARCH model. The research results are as follows. First, it was found that the Korean ETS market has a higher rate of return and higher investment risk than the stock market. Second, the yield volatility of the Korean ETS market was found to be most affected by external shocks and least affected by the volatility information of the market itself. Third, the correlation between the Korean ETS market and the stock market was stronger than that of the WTI crude oil futures market. This paper analyzed the correlation between the Korean ETS market, energy market, and stock market and confirmed that the level of financialization in the Korean ETS market is quite low.

A Study on Co-movements and Information Spillover Effects Between the International Commodity Futures Markets and the South Korean Stock Markets: Comparison of the COVID-19 and 2008 Financial Crises

  • Yin-Hua Li;Guo-Dong Yang;Rui Ma
    • Journal of Korea Trade
    • /
    • v.27 no.5
    • /
    • pp.167-198
    • /
    • 2023
  • Purpose - This paper aims to compare and analyze the co-movements and information spillover effects between the international commodity futures markets and the South Korean stock markets during the COVID-19 and the 2008 financial crises. Design/methodology - The DCC-GARCH model is used in the co-movements analysis. In contrast, the BEKK-GARCH model is used to evaluate information spillover effects. The statistical data used is from January 1, 2005, to December 31, 2022. It comprises the Korea Composite Stock Price Index data and daily international commodity futures prices of natural gas, West Texas Intermediate crude oil, gold, silver, copper, nickel, soybean, and wheat. Findings - The results of the co-movement analysis were as follows: First, it was shown that the co-movements between the international commodity futures markets and the South Korean stock markets were temporarily strengthened when the COVID-19 and 2008 financial crises occurred. Second, the South Korean stock markets were shown to have high correlations with the copper, nickel, and crude oil futures markets. The results of the information spillover effects analysis are as follows: First, before the 2008 financial crisis, four commodity futures markets (natural gas, gold, copper, and wheat) were shown to be in two-way leading relationships with the South Korean stock markets. In contrast, seven commodity futures markets, except for the natural gas futures market, were shown to be in two-way leading relationships with the South Korean stock markets after the financial crisis. Second, before the COVID-19 crisis, most international commodity futures markets, excluding natural gas and crude oil future markets, were shown to have led the South Korean stock markets in one direction. Third, it was revealed that after the COVID-19 crisis, the connections between the South Korean stock markets and the international commodity futures markets, except for natural gas, crude oil, and gold, were completely severed. Originality/value - Useful information for portfolio strategy establishment can be provided to investors through the results of this study. In addition, it is judged that financial policy authorities can utilize the results as data for efficient regulation of the financial market and policy establishment.

COVID-19 Pandemic and Dependence Structures Among Oil, Islamic and Conventional Stock Markets Indexes

  • ALQARALLEH, Huthaifa;ABUHOMMOUS, Alaa Adden
    • The Journal of Asian Finance, Economics and Business
    • /
    • v.8 no.5
    • /
    • pp.515-521
    • /
    • 2021
  • The popularity of Islamic financial instruments among Muslims is not surprising. The Islamic capital market is where sharia-compliant financial assets are transacted. It works parallel to the conventional market and helps investors find sharia-compliant investment opportunities. At a time of collective confusion when the COVID-19 epidemic is contributing to unprecedented change, this paper is keen to understand how attractive conventional and Islamic stock markets have been to investors recently. Second, this paper takes advantage of the time-scale decomposition property of the wavelet to simultaneously capture risk exposure and distinguish the risks faced by short- and long-term investors. To this end, this research conducted a two-step investigation of the daily closing equity market price indices for three Islamic stock markets and their conventional counterparts. Given that different financial decisions occur with greater or less frequency, the paper examines the connectedness of stock markets operating at heterogeneous rates and identifies the timescales using wavelet-DCC-GARCH analysis to take account of both the time and the frequency domains of stock market connectedness. The paper findings highlight the strong evidence of contagion that can be seen in nearly all conventional stock markets in the COVID-19 pandemic; they reach a high level of dependency in such health crises. Furthermore, Islamic stock markets prove to be a rich ground for global diversification.

A Study on Regional Blocs of International Crude Oil Futures Market (국제 원유선물시장의 지역블록화에 관한 연구)

  • Rui Ma;Yin-Hua Li
    • Korea Trade Review
    • /
    • v.47 no.3
    • /
    • pp.141-156
    • /
    • 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.