Volatility Spillovers and Contagion from Mature to Emerging Stock Markets

This paper models volatility spillovers from mature to emerging stock markets, tests for changes in the transmission mechanism during turbulences in mature markets, and examines the implications for conditional correlations between mature and emerging market returns. Tri‐variate GARCH–BEKK models of returns in mature, regional emerging, and local emerging markets are estimated for 41 emerging market economies (EMEs). Wald tests suggest that mature market volatility affects conditional variances in many emerging markets. Moreover, spillover parameters change during turbulent episodes. In the majority of the sample EMEs, conditional correlations between local and mature markets increase during these episodes. While conditional variances in local markets rise as well, volatility in mature markets rises more, and this shift is the main factor behind the increase in conditional correlations. With few exceptions, conditional beta coefficients between mature and emerging markets tend to be unchanged or lower during turbulences.     

Revisiting the shock and volatility transmissions among GCC stock and oil markets: A further investigation

The paper explores the empirical evidence of the volatility interactions among the Gulf Cooperation Council (GCC) stock markets and world oil price over the weekly period spanning from June 24, 2005 to March 25, 2011. The study is conducted based on the BEKK-GARCH process developed by Kroner and Ng (1998) and outlining the asymmetry in the conditional variances of the stock and oil markets. The findings show evidence of shock and volatility linkages among GCC stock and oil markets, and reveal that the spillover effects are more apparent for volatility patterns. They also indicate that the stock and oil markets exhibit asymmetry in the conditional variances. From the perspective of portfolio strategies, the results display certain sensitivity to the GCC stock prices, allowing thus better understanding of the relationship between each stock market and oil price. Our findings are crucial for practitioners, policy makers and investors who seek to make earnings by diversifying their portfolios.     

Do oil producing countries offer international diversification benefits? Evidence from GCC countries

This paper provides evidence of the existence of diversification benefits in international stock markets when oil producing countries are included in a global portfolio. Moreover, it examines whether recent oil shocks and financial events have significant impact on the conditional correlations and diversification benefits. Using stock returns from developed, emerging, GCC countries and a global portfolio, the empirical findings show that while developed and emerging stock markets have experienced increased correlations over relatively long periods of time, the correlation in GCC stock markets remained low and constant offering high diversification benefits. Interestingly, the paper also finds that, during 2012–2014, the rising conditional correlation levels have reversed trends in developed and emerging markets alike offering more potential for international diversification. Our results are robust to model selection, data frequency, and innovations distribution.     

Dynamic Correlation Analysis of Asian Stock Markets

This paper examines the stock market linkages within the Asia-Pacific region and between Asian markets and the U.S. market over the period of January 2000 to June 2010, employing the dynamic conditional correlation GARCH model. Our results show that there exist very high correlations among the stock markets during the 2008 financial crisis. Therefore, consistent with the finding in literature, there are no diversification benefits during the financial crisis. However, our results show that there are still substantial opportunities for global investors to improve the risk-return performance between China and other markets during the sample period. In addition, we find evidence that the U.S. market significantly affects the stock markets in the Asia-Pacific region. Using T-GARCH model, there is a strong evidence of an asymmetric effect on conditional variance except stock markets in China and Malaysia.     

Volatility and dynamic conditional correlations of worldwide emerging and frontier markets

This study examines the relationship between time-varying correlations and conditional volatility among 32 worldwide emerging and frontier stock markets and the MSCI World stock market index from January 2000 to December 2012. Correlations are estimated in the standard and asymmetric dynamic conditional correlation model frameworks. The results can be summarized by three main findings: (1) asymmetry in volatility is not a common phenomenon in emerging and frontier markets; (2) asymmetry in correlations is found only with respect to the Hungarian stock market; and (3) the relationship between volatility and correlations is positive and significant in most countries. Thus, diversification benefits decrease during periods of higher volatility.     

Stock market integration between new EU member states and the Euro-zone

This paper measures the degree in stock market integration between five Eastern European countries and the Euro-zone. A potentially gradual transition in correlations is accommodated by smooth transition conditional correlation models. We find that the Czech, Slovenian and Polish markets have increased their correlation to the Euro-zone from 1997 to 2008. However, this is not a broad-based phenomenon across Eastern Europe. The results also show that the increase in correlations is not a reflection of a world-wide phenomenon of financial integration but is mainly driven by EU-related developments.     

Spillover effects of the 2008 financial crisis on NIE stock markets

This article estimates dynamic conditional correlations of stock returns across countries by using DCC–GARCH model and analyse spillover effects of the 2008 financial crisis on the NIE’s stock markets. The results show that there is no regime shift in mean equation of the correlation coefficient during the financial crisis. It may imply there are no mean spillover effects of the US financial crisis on the NIE’s stock markets. However, there are volatility spillover effects of the financial crisis sparked in 2008 from the US to the NIE’s markets.     

How do great shocks influence the correlation between oil and international stock markets?

We investigate the impacts of great shocks (2003 Iraq War and 2008 Financial Crisis) on the correlations between oil and US/China stock markets, utilizing a novel MADCC (mixed asymmetry dynamic conditional correlation) model. This model successfully captures the coexistence of opposite signed asymmetries. We find that great shocks indeed increased the correlations. Further, results from the news impact surfaces indicate that correlations between oil and stock markets are higher to joint negative shocks; however, correlation between stock markets has stronger response to joint positive shocks.     

Dynamic correlation and equicorrelation analysis of global financial turmoil: evidence from emerging East Asian stock markets

This study investigates the dynamic conditional correlations (DCCs) between eight emerging East Asian stock markets and the US stock market and analyses the dynamic equicorrelation among these nine stock markets. We find a significant increase in the conditional correlations and equicorrelation in the first phase of the global financial crisis. We refer to this finding as contagion from the US stock market to the emerging East Asian markets. We also find an additional significant process of increasing correlations and equicorrelation (herding) in the second phase of the global financial crisis. Further, we employ two new models, namely DCCX-MGARCH (a DCC Multivariate GARCH model with exogenous variables) and DECOX-MGARCH (a dynamic equicorrelation multivariate GARCH model with exogenous variables), to identify the channels of contagion. We find that an increase in the VIX Index increases the conditional correlations and equicorrelation, while increases in TED spreads decrease the conditional correlations of six emerging East Asian countries with the USA. We compare the accuracy of the conditional correlation estimates of the DCC and DCCX models (or DECO and DECOX models) by constructing a loss function. We find that the DCCX (DECOX) model provides more accurate conditional correlation estimates than the DCC (DECO) model by extracting additional information from exogenous variables.     

Spillover Effects of the 2008 Financial Crisis in Latin America Stock Markets

This paper examines the transmission of the 2008 US financial crisis to four Latin American stock markets using daily stock returns from 2006 to 2010, analyzing before, during and after the 2008 financial crisis. The empirical evidence presents a financial contagion by showing persistently higher and more volatile pair-wise conditional correlations during the crisis period. This indicates there are structural changes in mean and volatility of the correlation coefficients due to the 2008 financial crisis in Latin American markets. The results here could be useful in international portfolio diversification decision-making in Latin American region. In addition, the predicting the volatility in different markets could be a useful input for reducing financial instability in crisis episodes to policy makers.     

News and correlations of CEEC-3 financial markets

We employ DCC-MGARCH models to investigate conditional correlations between six CEEC-3 financial markets. In general, the highest correlations exist between Hungary and Poland in foreign exchange and stock markets. Short-term money markets are somewhat isolated from each other. We find that the associations of CEEC-3 exchange rates versus euro are weaker than those versus the US dollar. The persistence of the effect of shocks on the time-varying correlations is strongest for foreign exchange and stock markets, indicating a tendency toward contagion. In searching for the origins of financial market volatility in the CEEC-3, we uncover some evidence of Granger-causality on the foreign exchange markets. Finally, using a pool model, we investigate the impact of euro area, US, and CEEC-3 news on the correlations. Apart from ECB monetary policy news, we observe no broad effects of international news on correlations; instead, local news exerts an influence, which suggests a dominance of country- or market-specific circumstances.     

Trade and Investment Linkages and Stock Market Long‐Run Relationship

This paper aims to examine whether the intensity of trade and investment linkages among the countries matter for their stock market long‐run relationship. To achieve this, we classify Australia's bilateral trade and investment partners into major, medium and minor. Empirical findings of an asymmetric generalised dynamic conditional correlation generalised autoregressive conditional heteroskedasticity model show that correlations are time varying and increased significantly during the global financial crisis (GFC). Results of multivariate cointegration test confirm the long‐run equilibrium relationship between the stock markets of Australia and its major partners in the pre‐GFC and during GFC. Based on the full‐sample results, it indicates that the GFC has segmented the stock markets from the long‐run equilibrium relationship. Granger non‐causality test results on full sample show that Australian stock market causes only the New Zealand market while the USA, the UK, Germany, Canada, Switzerland and Italy drives the Australian market. Our results therefore suggest that the intensity of bilateral trade and investment linkages among the countries matter for their stock markets' long‐term relationship.     

Conditional heteroscedasticity with leverage effect in stock returns: Evidence from the Chinese stock market

In recent years the Chinese stock market has experienced an astonishing growth and unprecedented development, but is also viewed as one of the most volatile markets, which has been called by many observers a “casino”. This study intends to examine the presence of heteroskedasticity and the leverage effect in the Chinese stock markets, and to capture the dynamics of conditional correlation between returns of China's stock markets and those of the U.S. in a bivariate VC-MGARCH framework. The results show that the leverage effect is significant in these markets during the sample period in 2000–2013, and the conditional correlation between mainland China's and the U.S. stock markets is quite low and highly volatile. The Chinese stock markets are found to be highly regimes persistent. These findings have important implication for investors seeking opportunity of portfolio diversification.     

Stock market integration of emerging Asian economies: Patterns and causes

In this study, we examine the patterns and causes of stock market integration of selected emerging Asian nations against the US, Australia, China, and India for the period 1 January 2001 to 31 March 2012. We compare patterns of market integration for countries on a daily, weekly, or monthly basis using the time-varying correlation technique, namely, GARCH-dynamic conditional correlations (DCCs). In doing so, we suggest that opportunities in cross border investment vary by frequencies. We also divide daily data into subsamples and find that correlations were strongest during the global financial crisis (GFC) of 2007–09. The time varying bilateral correlations are found to be highly volatile. We also investigate the causes of identified correlations and find that apart from the GFC, the underlying economic and financial conditions have also been responsible for the higher correlations between these stock markets.     

商品期货对资产配置的风险分散价值研究

基于BEKK-GARCH模型,本文考察了我国部分商品期货品种与股价指数收益率之间条件相关系数的动态变化特征,结果表明:商品期货与股价指数收益率之间存在较低的相关性;一些商品期货品种价格与股价指数的市场相关性呈长期减弱的趋势;而且,两者之间的相关性随股票市场波动率的增大而下降,股市波动幅度越大,商品期货与股价指数之间的相关性越低;这些都意味着商品期货对于资产配置有较好的风险分散价值。     

Return and volatility transmission between oil prices and oil-exporting and oil-importing countries

This paper provides further evidence of the comovements and dynamic volatility spillovers between stock markets and oil prices for a sample of five oil-importing countries (USA, Italy, Germany, Netherland and France) and four oil-exporting countries (United Arab Emirates, Kuwait, Saudi Arabia and Venezuela). We make use of a multivariate GJR-DCC-GARCH approach developed by Glosten et al. (1993). The results show that: i) dynamic correlations do not differ for oil-importing and oil-exporting economies; ii) cross-market comovements as measured by conditional correlation coefficients increase positively in response to significant aggregate demand (precautionary demand) and oil price shocks due to global business cycle fluctuations or world turmoil; iii) oil prices exhibit positive correlation with stock markets; and iv) oil assets are not a good ‘safe haven’ for protection against stock market losses during periods of turmoil.     

Long-run Relationships between Selected Central European Indexes

In the paper we discuss the results of the long-run relationships (cointegration) between the Warsaw Stock Exchange and the other three stock exchanges situated in Central Europe: the Vienna Stock Exchange, the Prague Stock Exchange, and the Budapest Stock Exchange. Cointegration analysis is applied to check if the markets are integrated. Highly integrated markets are not isolated from international shocks.     

Stock market interdependence between Australia and its trading partners: does trade intensity matter?

We investigate the extent and manner of stock market interdependence between Australia and its trading partners and examine whether this is affected by trade intensity. Based on trade intensity, we classify Australia’s trading partners into major, medium and minor partners. We hypothesize that markets with greater (lower) trade intensity will be more (less) interdependent with Australia. We perform correlation (unconditional and conditional) analyses between Australia and its trading partners. Our results indicate that most of the markets that are highly correlated with Australia are its major trading partners. We conduct panel regression analysis to investigate whether trade intensity has any impact on the stock market correlations between Australia and its trading partners. The results show that trade intensity significantly and positively affect the correlations of Australia with its major trading partners. Thus, the results confirm our hypothesis that trade intensity drives stock market interdependence between Australia and its trading partners.     

Economic integration and stock market dynamic linkages: evidence in the context of Australia and Asia

Countries are becoming economically integrated and it is contended that this will also lead to their financial markets becoming integrated. This contention is important since international financial market integration diminishes portfolio diversification benefits and creates contagion risk. We test this contention in this article in the context of the Australasian region. Australia and Asia have experienced very significant economic integration through a rapid growth in their bilateral trade. We utilize a battery of econometric techniques – cointegration, asymmetric generalized dynamic conditional correlations and panel regression models. As expected, we find that trade intensity significantly drives the interdependence between their stock markets in both the short run and the long run. Thus, given the ever increasing economic integration in this region, this finding implies that their stock markets face the risk of contagion, and that investors in these markets would also be confronted with the prospect of lower diversification benefits.     

Stock Market Integration between Three CEECs,Russia, and the UK

This paper estimates a trivariate VAR‐GARCH(1,1)‐in‐mean model to examine linkages between the stock markets of three Central and Eastern European countries (CEECs), specifically the Czech Republic, Hungary, and Poland, and both the UK and Russia. The adopted framework allows to analyze interdependence by estimating volatility spillovers, and also contagion by testing for possible shifts in the transmission of volatility following the introduction of the euro and EU accession. Further evidence on possible changes in the transmission mechanism (namely, on whether there is contagion) can be obtained by examining the conditional correlations implied by the estimated model over different time periods. The empirical findings suggest that there is significant co‐movement (interdependence) of these CEEC markets with both the Russian and the UK ones. Furthermore, whilst the introduction of the euro has had mixed effects, EU accession has resulted in an increase in volatility spillovers between the three CEECs considered and the UK (contagion).