MEAN AND VOLATILITY SPILLOVERS ACROSS MAJOR NATIONAL STOCK MARKETS: FURTHER EMPIRICAL EVIDENCE

This paper provides additional insight into the nature and degree of interdependence of stock markets of the United States, Japan, the United Kingdom, Canada, and Germany, and it reports the extent to which volatility in these markets influences expected returns. The analysis uses the multivariate GARCH-M model. Although they are considered weak, statistically significant mean spillovers radiate from stock markets of the U.S. to the U.K., Canada, and Germany, and then from the stock markets of Japan to Germany. No relation is found between conditional market volatility and expected returns. Strong time-varying conditional volatility exists in the return series of all markets. The own-volatility spillovers in the U.K. and Canadian markets are insignificant, supporting the view that conditional volatility of returns in these markets is “imported” from abroad, specifically from the U.S. Significant volatility spillovers radiate from the U.S. stock market to all four stock markets, from the U.K. stock market to the Canadian stock market, and from the German stock market to the Japanese stock market. The results are robust and no changes occur in the correlation structure of returns over time.     

A Conditional Assessment of the Relationships between the Major World Bond Markets

This paper uses a bivariate GARCH framework to examine the lead‐lag relations and the conditional correlations between 10‐year US government bond returns and their counterparts from the UK, Germany, and Japan. We find that while mean and volatility spillovers exist between the major international bond markets, they are much weaker than those between equity markets. The results also indicate that the correlations between the US and other major bond market returns are time varying and are driven by changing macroeconomic and market conditions. However, in contrast to the finding that the benefits of international diversification in equity markets evaporate during high‐stress periods, we find that the benefits of diversification across major government bond markets do not decrease during periods of extremely high bond market volatility or following extremely negative US and foreign bond returns.     

Transmission of Stock Returns and Volatility between the U.S. and Japan: Evidence from the Stock Index Futures Markets

In this paper, we examine the nature of transmission of stock returns and volatility between the U.S. and Japanese stock markets using futures prices on the S&P 500 and Nikkei 225 stock indexes. We use stock index futures prices to mitigate the stale quote problem found in the spot index prices and to obtain more robust results. By employing a two-step GARCH approach, we find that there are unidirectional contemporaneous return and volatility spillovers from the U.S. to Japan. Furthermore, the U.S.'s influence on Japan in returns is approximately four times as large as the other way around. Finally, our results show no significant lagged spillover effects in both returns and volatility from the Osaka market to the Chicago market, while a significant lagged volatility spillover is observed from the U.S. to Japan. This revised version was published online in August 2006 with corrections to the Cover Date.     

Empirical Identification of Non-Informational Trades Using Trading Volume Data

This paper empirically identifies non-informational and informational trades using stock returns and trading volume data of the U.S., Japanese, and U.K. stock markets and five individual firms. We achieve the identification by imposing a restriction from theoretical considerations. Our results show that trading volume is mainly driven by non-informational trades, while stock price movements are primarily driven by informational trades. We also find that, around the 1987 stock market crash, trading volumes due to non-informational trades increased dramatically, while the decline in stock market prices was due mainly to informational trades. Increases in volatilities both in returns and in trading volumes during and after the crash are mainly due to non-informational trades. Regarding the trading volume-serial correlation in the stock returns relationship, we find evidence that is consistent with theoretical predictions that non-informational components can account for high trading volume accompanied by a low serial correlation of stock returns.     

Volatility Spillovers Between Stock Returns and Exchange Rate Changes: International Evidence

We investigate interdependencies between stock returns and exchange rate changes for six industrialised countries, namely the US, the UK, Japan, Germany, France and Canada, by testing for volatility spillovers using a bivariate EGARCH model. Volatility spillovers from stock returns to exchange rate changes are found for all countries except Germany. These spillovers are symmetric in nature. No evidence is found of volatility spillovers from exchange rate changes to stock returns for any country. Spillovers from stock returns to exchange rate changes have increased since October 1987. This finding is consistent with the notion that international financial markets have become increasingly integrated.     

Volatility Spillovers Between Stock Returns and Exchange Rate Changes: International Evidence

We investigate interdependencies between stock returns and exchange rate changes for six industrialised countries, namely the US, the UK, Japan, Germany, France and Canada, by testing for volatility spillovers using a bivariate EGARCH model. Volatility spillovers from stock returns to exchange rate changes are found for all countries except Germany. These spillovers are symmetric in nature. No evidence is found of volatility spillovers from exchange rate changes to stock returns for any country. Spillovers from stock returns to exchange rate changes have increased since October 1987. This finding is consistent with the notion that international financial markets have become increasingly integrated.     

DOES THE OCTOBER 1987 CRASH STRENGTHEN THE CO-MOVEMENTS AMONG NATIONAL STOCK MARKETS?

This study examines the effect of the October 1987 crash on the co-movements among national stock markets. Interrelationships among the price movements in different national stock markets are analyzed using correlation and exploratory factor analysis. The data on weekly returns of 12 national stock market indices over the period from August 1984 to December 1990 are used in both local-currency and U.S. dollar terms for the analysis. This study finds that national stock markets became more interrelated after the crash, and the strengthening co-movements among national stock markets continued for a longer period after the crash. In addition, it is shown that the co-movements among national stock markets were stronger when the U. S. stock market was more volatile. These results imply that after investors experienced the October crash, they tend to give more weight to international factors in making investment decisions after the crash than before.     

Extreme downside risk spillover from the United States and Japan to Asia-Pacific stock markets

This paper proposes a binary response model approach to measure and forecast extreme downside risks in Asia-Pacific markets given information on extreme downside risks in the U.S. and Japanese markets. The extreme downside risk of a market is measured as the occurrence of extreme downside movement—market returns falling below left-tail Value at Risk in a Markov switching framework. The empirical findings are consistent with the following notions. First, extreme downside movements of the S&P 500 and Nikkei 225 are significantly predictive for the likelihood of extreme downside movements in all the investigated Asia-Pacific markets. Second, the majority of Asia-Pacific markets become more sensitive to Japan's extreme downside risk when the Japanese market switches into high volatility periods, whereas the U.S. spillover effect is intensified only on Taiwan during high volatility periods in the U.S. Third, mainland China is the least sensitive to extreme downside risk in the U.S. and Japan, Australia is the most sensitive to the U.S., and Singapore is the most sensitive to Japan.     

Comparative analysis on the effects of the Asian and global financial crises on precious metal markets

The global financial crisis has vigorously struck major financial markets around the world, in particular in the developed economies since they have suffered the most. However, some commodity markets, and in particular the precious metal markets, seem to be unscathed by this financial downturn. This paper investigates therefore the nature of volatility spillovers between precious metal returns over fifteen years (1995-2010 period) with the attention being focused on these markets’ behavior during the Asian and the global financial crises. Daily closing values for precious metals are analyzed. In particular, the variables under study are the US$/Troy ounce for gold, the London Free Market Platinum price in US$/Troy ounce, the London Free Market Palladium price in US$/Troy once, and the Zurich silver price in US$/kg. The main sample is divided into a number of sub periods, prior to, during and after the Asian crisis. The aim of this division is to provide a wide and deep analysis of the behavior of precious metal markets during this financial event and of how these markets have reacted during times of market instability. In addition, this paper also looks at the effects of the global financial crisis from August 2007 to November 2010 using GARCH and EGARCH modeling. The main results show that there is clear evidence of volatility persistence between precious metal returns, a characteristic that is shared with financial market behavior as it has been demonstrated extensively by the existing literature in the area. In terms of volatility spillover effects, the main findings evidence volatility spillovers running in a bidirectional way during the periods; markets are not affected by the crises, with the exception of gold, that tends to generate effects in all other metal markets. However, there is little evidence in the case of the other precious metals generating any kind of influence on the gold market. On the other hand, there is little evidence of spillover effects during the two crisis episodes. Finally, the results from asymmetric spillover effects show that negative news/information have a stronger impact in these markets than positive news, again a characteristic that has been also exhibited by financial markets.     

Financial crises and the dynamics of the spillovers between the U.S. and BRICS stock markets

We examine the spillover dynamics between the U.S. and BRICS stock markets using the multivariate DECO-GJR-GARCH model and spillover index method. We identify time variations in volatility equicorrelation and significant dynamic spillovers between these stock markets, as well as an increased impact of uncertainty on spillovers. Spillovers between markets intensify after the inception of the global financial crisis and subsequent European sovereign debt crisis. We also find, following the commencement of the crisis periods, that the U.S., Brazilian, and Chinese markets are net volatility transmitters, whereas the Russian, Indian, and South African markets are net recipients. These results shed new light on the information transmission channels between the U.S. and BRICS stock markets.     

Dynamic volatility spillovers across oil and natural gas futures markets based on a time-varying spillover method

This paper analyzes dynamic volatility spillovers between four major energy commodities (i.e., crude oil, gasoline, heating oil and natural gas) in the oil-natural gas future markets. We construct a time-varying spillover method by combining the TVP-VAR-SV model and the spillover method of Diebold and Yilmaz (2009, 2012, 2014). We use the spillover method to obtain time-varying total, directional and pairwise volatility spillover indices. Our results summarize as follows: (1) The volatility spillover indices present peaks and troughs during some periods, such as shale gas revolution, financial crisis, and oil price crash; (2) After the U.S. shale gas revolution, the size of volatility spillover from natural gas future market has reduced sharply, but volatility doesn't decouple from the other three oil future markets; (3) The directional spillover is asymmetric. The crude oil and heating oil futures market are main net transmitter of volatility risk information, while the gasoline and natural gas futures markets are the net receiver; (4) For natural gas future market, the pairwise volatility spillover from crude oil future market has the most significant influence.     

The Impulse of Stock Market Volatility and the Market Crash of October 1987

This paper employs the technique of variance decomposition and impulse response functions to examine the dynamic nature of stock market volatility relationships among six major countries during the pre, around, and post October 1987 crash period. During the period around the crash, the US stock market volatility explains much better the variations of the stock market volatility of Australia, Hong Kong, Japan, Singapore and the UK. Our findings clearly indicate that the crash originated in the US and then spread to other major stock markets.     

Asymmetric volatility spillovers between economic policy uncertainty and stock markets: Evidence from China

This study explores the spillovers between economic policy uncertainty (EPU) and stock market realized volatility (RV). The monthly index of Chinese and US EPU and RV are used to analyze the pairwise directional spillovers. We find that RV is a net receiver that is more vulnerable to shocks from U.S. EPU than to shocks from Chinese EPU. We further decompose the RV into good and bad volatility to test the asymmetric spillover effect between the stock market and EPU. The results suggest that EPU has a bigger effect on bad volatility in the stock market throughout most of the sample period. However, we find that good volatility spillovers become larger during periods of stimulated reform, whereas bad volatility spillovers become larger during periods of international disputes. We show that Chinese stock market volatility is sensitive to both U.S. and Chinese EPU and that the spillover is asymmetric in different periods.     

Tail Dependence in International Real Estate Securities Markets

??Tail dependence?? characterizes the cross market linkages during stressful times. Analyzing tail dependence is of primary interest to portfolio managers who systematically monitor the co-movements of asset markets. However, the relevant literature on real estate securities markets is very thin. Our study extends the literature by using the flexible symmetrized Joe-Clayton (SJC) copula to estimate the tail dependences for six major global markets (U.S., U.K., Japan, Australia, Hong Kong, and Singapore). In implementing the SJC copula, we model the marginal distributions of returns through a semi-parametric method which has never been applied to real estate returns. Our major findings suggest that international markets display different strength and dynamics of tail dependence. We extensively discuss the implications of our findings for financial practices such as portfolio tail diversifications, portfolio selections, portfolio risk management and hedging strategies. Our study also demonstrates that the widely used linear correlation is an inadequate measure of market linkages, especially during periods of crisis.     

After-Hours Stock Prices and Post-Crash Hangovers

After-hours pricing in foreign equity markets of multiple-listed U.S. securities appeared to be efficient in predicting New York prices in the weeks immediately following the October 1987 crash but relatively uninformative in succeeding months. By contrast, daily changes in New York prices appear to be efficiently incorporated in after-hours trading on both the Tokyo and London exchanges throughout the sample period. This paper suggests that the asymmetry and temporal variations in cross-market correlations are consistent with rational investor behavior in equity markets with nonzero transaction costs and time-varying share price volatility.     

No Contagion, Only Interdependence: Measuring Stock Market Comovements

Heteroskedasticity biases tests for contagion based on correlation coefficients. When contagion is defined as a significant increase in market comovement after a shock to one country, previous work suggests contagion occurred during recent crises. This paper shows that correlation coefficients are conditional on market volatility. Under certain assumptions, it is possible to adjust for this bias. Using this adjustment, there was virtually no increase in unconditional correlation coefficients (i.e., no contagion) during the 1997 Asian crisis, 1994 Mexican devaluation, and 1987 U.S. market crash. There is a high level of market comovement in all periods, however, which we call interdependence.     

Spatial linkage of volatility spillovers and its explanation across G20 stock markets: A network framework

This paper empirically estimates the spatial correlation relationship of volatility spillovers and its influencing factors across G20 stock market. We apply GARCH-BEKK model to estimate volatility spillover and construct dynamic volatility networks. The connectedness analysis shows that the spatial linkage of volatility spillover is time varying and has obvious multiple superposition phenomena. As somewhat innovation results, we use the factor analysis method to obtain centrality comprehensive indicators that can clearly depict the risk contagion intensity and risk acceptance intensity. In general, the developed markets are more influential than the emerging markets during periods of turbulence, and the emerging markets are more sensitive to volatility shocks than developed markets during any period. Finally, this paper introduces quadratic assignment procedure (QAP) method to identify the major factors that influence the spatial linkage of volatility spillovers. Results show that geography influences the volatility spatial correlation differently across economic cycles, and the centrality structure factors have greater impact on the spatial correlation than the external economic factors. The QAP regression analysis shows that these influencing factors can explain about 50% of the spatial correlation variation of international financial markets' volatility spillovers.     

The behaviour of asset return and volatility spillovers in Turkey: A tale of two crises

This paper examines return and volatility spillovers between the Turkish stock market with international stock, exchange rate and commodity markets. Our aim is not only to examine spillover behaviour with a large emerging market but also to examine cross—asset spillovers and how they vary across two periods of financial market crisis; the dotcom crash and the liquidity-induced financial crisis. This is to be compared with existing work that typically focuses on industrialised countries or single asset markets only. Using the spillover index methodology we uncover an interesting distinction between these two periods of markets stress. Over the dotcom period spillovers are largely between the same asset class, notably two exchange rate series and two international stock markets series. However, in the period including the financial crisis, spillovers both increase and cross asset types and suggest a much greater degree of market interdependence. Understanding this changing nature in spillovers is key for investors, regulators and academics involved in theoretical model development.     

Spillovers of stock return volatility to Asian equity markets from Japan and the US

This paper examines the magnitude of return and volatility spillovers from Japan and the US to seven Asian equity markets. I construct a volatility spillover model that deals with the US shock as an exogenous variable in a bivariate EGARCH for Japan and Asian markets. First, only the influence of the US is important for Asian market returns; there is no influence from Japan. Second, the volatility of the Asian market is influenced more by the Japanese market than by the US. Third, there exists an adverse influence of volatility from the Asian market to the Japanese market.     

Price and Volatility Spillovers in the Case of Stock Markets Located in Different Time Zones

This paper investigates the interdependence of price volatility across the U.S. stock market and two emerging markets: Poland and Hungary. Using daily data for countries located in different time zones, we point out the problems caused by the presence of nonsynchronous trading effects. To address this problem we use open-to-close logarithmic returns of major stock market indexes. The asymmetric impact of good and bad news is described by a multivariate exponential general autoregressive conditional heteroskedastic model. We investigate the sample from May 2004 to December 2011. The evidence is that the U.S. prices spill over to other markets. Our results show no pronounced volatility spillovers among the three examined markets. Moreover, we observe the presence of negative asymmetry in the case of all markets.