An empirical analysis of the US stock market and output growth volatility spillover effects on three Anglo-Saxon countries

This paper examines the dynamic and switching effects of volatility spillovers arising from US stock market returns and GDP growth on those of Australia, Canada and the UK. For this purpose, we use quarterly data (1961q1–2013q1) and a constant probability Markov regime switching model. We found that the US stock market volatility significantly affects the stock market volatility of all three countries at least in one of the two specified regimes over time. However, the stock market volatilities in none of the three countries are contemporaneously influenced by the US output volatility even after allowing for two distinct regimes. On the other hand, the US stock market volatility exerts significant influences on the output volatilities of both Australia and the UK. Compared with Australia and the UK, Canada and the US show substantial output volatility co-movements, thereby confirming the close association between the two neighbouring economies through the NAFTA (North American Free Trade Agreement). We conclude that shocks emanating from the US stock market have unequivocal flow-on effects on the output and return volatilities of the other economies.     

DYNAMIC STOCK RETURN–VOLUME RELATION: EVIDENCE FROM EMERGING ASIAN MARKETS

This paper empirically examines the dynamic stock return–volume relations for six emerging Asian markets: Indonesia, Malaysia, Singapore, South Korea, Taiwan, and Thailand. Evidence is found that trading volume Granger causes stock return in quantiles and the causal effects of volume are heterogeneous across quantiles. This shows that volume carries some information to the return and could be interpreted in light of theoretical models. In addition, we find that there is bi‐directional causality between stock return and trading volume in most of the markets. The finding indicates that those Asian emerging markets with different institutions and information flows than more mature markets have present similar causal effects on the stock return–volume relation. Furthermore, the cross‐country evidence shows that the US market helps to predict the returns of the emerging Asian markets.     

THE DYNAMIC RELATION BETWEEN RETURNS,TRADING VOLUME,AND VOLATILITY: LESSONS FROM SPILLOVERS BETWEEN ASIA AND THE UNITED STATES

This paper investigates the dynamic relationship between index returns, return volatility, and trading volume for eight Asian markets and the US. We find cross‐border spillovers in returns to be non‐existent, spillovers in absolute returns between Asia and the US to be strong in both directions, and spillovers in volatility to run from Asia to the US. Trading volume, especially on the Asian markets, depends on shocks in domestic and foreign returns as well as on volatility, especially those shocks originating in the US. However, only weak evidence is found for trading volume influencing other variables. In the light of the theoretical models, these results suggest sequential information arrivals, with investors being overconfident and applying positive feedback strategy. Furthermore, new information causes price volatility to rise due to differences in its interpretation among traders, but the subsequent market reaction takes the form of adjustment in price level, not volatility. Lastly, the intensity of cross‐border spillovers seems to have increased following the 1997 crisis, which we interpret as evidence of increased noisiness in prices and diversity in opinions about news originating abroad. Our findings might also help to understand the nature of financial crises, to predict their further developments and consequences.     

Sources of volatility in stock returns in emerging markets

In this study, the short-term fluctuations in the monthly returns on composite indexes of 17 emerging markets affected by the financial crises in the late 1990s and 2000 are decomposed with vector autoregressive estimates. The results are compared to the behaviour of variation in returns in developed markets. Three different models are estimated for each market. Due to first order autocorrelations, lagged returns contribute significantly to return volatility in emerging markets. Decomposition of variances indicates that dividend yield and interest rate are determining factors of volatility, but at varying degrees in different emerging markets. However, the role of dividend yield is not as strong as it is in the developed markets as efficient markets hypothesis would imply. In some cases, exchange rates significantly influence market volatility. Fluctuations in the world portfolio return have a small effect on return volatility in national markets. However, there are significant differences across all emerging markets that point to differences in market structures and particular conditions in each country. Significant contributions of interest rates, exchange rates and inflation imply the role of monetary and fiscal policy as precedents of financial crises.     

Asymmetric spillover effects between the Shanghai and Hong Kong stock markets: evidence from quantile lagged regression

This article surveys the asymmetric spillover effects between the mainland China-based Shanghai Composite Index (SCI) and the Hong Kong based Hang Seng Index (HSI) using a quantile lagged regression model. Compared to previous studies, this article, based on data before and after the 2008 global financial crisis, presents a more detailed analysis, as we investigate the spillovers in terms of returns, volatilities and exchange rates between the renminbi (RMB) and the Hong Kong dollar (HKD) throughout the entire conditional return distribution, including the central quantiles, which are closely related to the normal circumstances, and the extreme quantiles, which correspond to the bear and bull markets. First, we find that the return spillovers from its lagged returns or from the other index not only vary across time but also depend on stock state. Second, while return volatility may boost the stock market in a bull market, it accelerates the decline in a bear market. Third, the depreciation of the RMB relative to the HKD does not significantly affect current returns for the HSI, while it negatively affects current returns for the SCI in a bad state after the crisis. The findings presented in this article will facilitate investors’ understanding of the two stock markets.     

Foreign News and Spillovers in Emerging European Stock Markets

We analyze foreign news and spillovers in the emerging EU stock markets (the Czech Republic, Hungary, and Poland). We employ high‐frequency five‐minute intraday data on stock market index returns and four classes of EU and US macroeconomic announcements during 2004–07. We account for the difference of each announcement from its market expectation and we jointly model the volatility of the returns accounting for intraday movements and day‐of‐the‐week effects. Our findings show that intraday interactions on the new EU markets are strongly determined by mature stock markets as well as the macroeconomic news originating thereby. We show that strong contemporaneous links across markets are present even after controlling for macroeconomic announcements. Finally, in terms of specific announcements, we are able to show the exact sources of macro news spillovers from the developed foreign markets to the three new EU markets under research.     

An analysis of the spillover effects of exchange-traded funds

This article used the Generalized Autoregressive Conditional Heteroscedasticity-Autoregressive Moving Average (GARCH-ARMA) and the exponentially Generalized Autoregressive Conditional Heteroscedasticity-Autoregressive Moving Average (EGARCH-ARMA) models to study the impact of the spillover and the leverage effects on returns and volatilities of stock index and Exchange Trade Fund (ETF) for developed and emerging markets. Previous unexpected returns for developed and emerging markets which have an opposite influence pattern on ETFs’ returns were identified. The spillover effects from returns are excellent for Hong Kong, followed by Singapore. Meanwhile, Taiwan's stock index return was recorded to have a strong negative impact on ETF return. Notably, this article shows that the spillover effects on stock index and ETF volatilities existed with bilateral influences. Despite a strong positive asymmetric volatility effect in Korea's ETF market, the leverage effect appears to play important roles in the explanation of both stock index and ETF returns.     

Where does return and volatility come from? The case of Asian ETFs

We analyze return and volatility of Asian iShares traded in the U.S. The difference in trading schedules between the U.S. and Asia offers a unique market setting that allows us to distinguish various return and volatility sources. We find Asian ETFs have higher overnight volatility than daytime volatility, explained by public information released during each local market's trading session. Local Asian markets also play an important role in determining each Asian ETF return. Nonetheless, returns for these funds are highly correlated with U.S. markets, indicative of the effects of investor sentiment and location of trade. Finally, returns in the U.S. market Granger-cause returns in all six Asian markets are analyzed.     

股市暴涨暴跌的界定及比较——以中国、美国、英国、日本股市为例

本文运用经验分布函数对中、美、英、日四国股市的暴涨暴跌进行了界定,并对四国股市暴涨暴跌的表现进行了比较分析。相比其它三国,中国股市在过去15年间成长性最强,暴涨暴跌的幅度最大,表现出较强的"政策驱动型"特征。美、英、日股市的暴涨暴跌呈现出明显的"市场和事件驱动型"特征。英国和美国股市波动呈现出较强的同步性,但日本股市波动较为独特。政策建议上,各国应通力合作,以应对全球系统性风险对股市的影响;中国政府应加强股市的市场化建设,同时谨慎开放资本市场。     

The impact of news,oil prices,and global market developments on Russian financial markets1

This paper analyses the impact of news, oil prices, and international financial market developments on daily returns on Russian bond and stock markets. First, regarding returns, energy news affects returns, while news from the war in Chechnya is not significant. Market volatility does not appear to be sensitive to either type of news. Second, a significant effect of the growth in oil prices on Russian stock returns is detected. Third, the international influence on Russian financial markets depends upon the degree of financial liberalization. The higher the degree of financial liberalization, the stronger is the impact of US stock returns on Russian financial markets. In addition, banking reform and interest rate liberalization efforts seem to dictate the globalization of Russian stock markets, while it is the progress in liberalizing securities markets and non‐bank financial institutions that matters more for the globalization of Russian bond markets.     

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.     

The relationship between South Asian stock returns and macroeconomic variables

This article investigates whether economic variables have explanatory power for share returns in South Asian stock markets. In particular, using data for four South Asian emerging stock markets over the period 1998–2012, the article examines the influence of a selection of local, regional and global economic variables in explaining equity returns; most previous studies that have examined this issue have tended to focus on only local and/or global factors. Important factors are identified by distilling the macroeconomic variables into principal components. Economic activities, real interest rates, real exchange rates and the trade balance represent local factors. Regional factors are represented by interregional trade and regional economic activity while global factors are represented by world financial asset returns and world economic activity. The vector autoregression results suggest that the South Asian markets examined are not efficient. Both local and regional factors can directly and indirectly explain Bangladeshi, Pakistani and Sri Lankan stock returns while the lagged returns of the Pakistani stock market and world economic activity can explain Indian stock returns.     

Asymmetric Linkages between BRICS Stock Returns and Country Risk Ratings: Evidence from Dynamic Panel Threshold Models

This study investigates the asymmetric linkages between the five BRICS (Brazil, Russia, India, China and South Africa) countries’ stock markets and three country risk ratings (financial, economic and political risk) in the presence of major global economic and financial factors. Using the dynamic panel threshold models, we find evidence of asymmetry in most cases. However, the significance and the signs of the effects of these risk ratings on the BRICS market returns differ across the lower and upper regimes. Furthermore, improvements in the global stock, West Texas Intermediate (WTI) and gold markets enhance the BRICS stock market performance. Increases in implied volatility indices lead to drops in the BRICS markets.     

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.     

On the detection of extreme movements and persistent behaviour in Mediterranean stock markets: a wavelet-based approach

We combine the global Hurst exponent and Morlet wavelet multi-resolution analysis (MRA) to investigate the dynamic behaviour of six selected stock markets in the Mediterranean region. Specifically, we employ the resonance coefficients and their power spectra to identify potential extreme movements and long-term dependence in stock returns. Using weekly data for the period 2005 to 2010, our results reveal that the wavelet MRA is able to reconstruct the effects of major extreme shocks on stock returns of studied markets, such as the Asian financial crisis, the 9/11 terrorist attacks and the 2007–2009 financial crisis. Moreover, the wavelet-based global Hurst exponent indicates the presence of long-term dependencies in stock returns of all the considered markets, except for France where the anti-persistent behaviour is detected. Overall, our findings are useful to assess the stock market efficiency and provide new insights into stock market dynamics over different time scales.     

Conditional volatility and correlations of weekly returns and the VaR analysis of 2008 stock market crash

Modelling of conditional volatilities and correlations across asset returns is an integral part of portfolio decision making and risk management. Over the past three decades there has been a trend towards increased asset return correlations across markets, a trend which has been accentuated during the recent financial crisis. We shall examine the nature of asset return correlations using weekly returns on futures markets and investigate the extent to which multivariate volatility models proposed in the literature can be used to formally characterize and quantify market risk. In particular, we ask how adequate these models are for modelling market risk at times of financial crisis. In doing so we consider a multivariate t version of the Gaussian dynamic conditional correlation (DCC) model proposed by Engle (2002), and show that the t-DCC model passes the usual diagnostic tests based on probability integral transforms, but fails the value at risk (VaR) based diagnostics when applied to the post 2007 period that includes the recent financial crisis.     

Co-movements of Shanghai and New York stock prices by time-varying regressions

We use time-varying regression to model the relationship between returns in the Shanghai and New York stock markets, with possible inclusion of lagged returns. The parameters of the regressions reveal that the effect of current stock return of New York on Shanghai steadily increases after the 1997 Asian financial crisis and turns significantly and persistently positive after 2002 when China entered WTO. The effect of current return of Shanghai on New York also becomes significantly positive and increasing after 2002. The upward trend has been interrupted during the recent global financial crisis, but reaches the level of about 0.4–0.5 in 2010 for both markets. Our results show that China’s stock market has become more and more integrated to the world market in the past twenty years with interruptions occurring during the recent global economic downturn.     

股市收益率与波动性长期记忆效应的实证研究

股票市场长期记忆效应问题是近来金融实证研究的一个热点.多数的研究集中在收益率长期相关性的考察上,较少有对波动率序列的研究.然而,波动率的长期记忆性不仅会导致金融市场上的波动持久性特征,而且将对波动率的预测与衍生证券定价产生重要的影响.基于此,本文通过修正的R/S分析与ARFIMA模型对我国股市收益率及其波动性的长期相关性进行了实证研究.结果表明:中国股市具有显著的非线性特征,虽然收益率序列的自相关性较弱,但波动性序列却表现出显著的长期记忆效应.这一结论将为研究股票价格行为特征与金融经济学理论提供新的方向.     

The source of global stock market risk: A viewpoint of economic policy uncertainty

This study explores the effect of economic policy uncertainty (EPU) in four countries or regions (China, Japan, Europe, and the United States) on the contagion risk of investments in the global stock market. The stock returns of 22 stock markets worldwide are analyzed to determine which region’s EPU exhibits the greatest effect on regional systematic risk in the global stock market and on volatility risk in individual stock markets. First, all of the samples, the markets of different continents and the spillover indices of the developed and emerging markets, are calculated to observe the dynamic correlation among these markets with the aim of quantifying regional systematic risk and further examining the contagion risk effect of EPU. The results indicate the following: EPU in China is the most influential, and its contagion risk spreads to different regional markets, except for Europe; the effect of EPU in the United States is inferior to that in China; EPU in Japan merely influences contagion risk in emerging markets; contagion risk in European markets is not influenced by the four EPU indices; and EPU in Europe is not influenced by contagion risk in the global stock market. However, according to the volatility risk in each market, the EPU in Europe and China respectively influence Asian countries and European countries the most. These results may be attributable to the extremely high trade dependence among these countries because the performance of international enterprises is mainly determined by the economic policies of their trading partners.     

Financial Integration Among the ASEAN 5 ＋ 3 Stock Markets： A Preliminary Look at the First 10 Years of the New Millenium

The purpose of this study is to investigate the financial integration of the stock markets of the ASEAN 5 ＋ 3 countries. These countries include Indonesia, Malaysia, Philippines, Singapore, Thailand, China, Japan, and South Korea. The research determined the stock return volatility for each country＇s index during the first decade of the new millennium. The findings showed that there is the presence of integration and co-integration with Philippine index＇s return with the index＇s returns of the following countries： Indonesia, Singapore, and Thailand. Furthermore, there is evidence of volatility clustering in these stock markets. The study concluded with the policy implications of greater integration in light of the planned cross trading among four ASEAN bourses, namely, Philippines, Singapore, Thailand, and Malaysia by 2012.