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.     

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.     

Modeling Price Volatility Linkages between Corn and Wheat: A Multivariate GARCH Estimation

The present paper attempts an empirical investigation on price volatility linkages between two important agricultural commodities: corn and wheat, by using a multivariate GARCH-BEKK model. Evidence of bidirectional linkages were found between corn and wheat in terms of returns and volatility. Multivariate conditional Student’s-t distribution results show a unidirectional volatility transmission from corn to wheat. Diagnostic tests reveal that the Student’s-t distribution will better model the volatility of returns when compared to the Gaussian distribution. Overall, the results show that the conditional variances and covariances between agricultural commodity market returns exhibit significant changes over time.     

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.     

Volatility persistence and asymmetry under the microscope: the role of information demand for gold and oil

This study explores the relationship between Google search activity and the conditional volatility of oil and gold spot market returns. By aggregating the volume of queries related to the two commodity markets in the spirit of Da et al. ( 2015 ), we construct a weekly Searching Volume Index (SVI) for each market as proxy of households and investors information demand. We employ a rolling EGARCH framework to reveal how the significance of information demand has evolved through time. We find that higher information demand increases conditional volatility in gold and oil spot market returns. Information flows from Google SVI's reduce the proportion of the significant volatility asymmetry produced by negative shocks in both commodity markets. The latter is more profound in the gold market.     

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.     

Dynamic causality between the U.S. stock market,the Chinese stock market and the global gold market: implications for individual investors’ diversification strategies

This paper proposes a generalization of the prior VAR and EGARCH model to explore the linkage between returns and volatility transmissions in the U.S. stock market, the Chinese stock market, and the global gold market from 10 July 1996 to 20 July 2018. We found that past returns of the U.S. stock market can predict the current returns of the other two markets, and that significant reciprocal volatility transmission existed within and across all three markets. We further implemented average out-of-sample (OOS) forecasting to show that a risk-adjusted portfolio, such as mean-variance with sample estimator, does not outperform an equal-weighted portfolio. This provides insights for individual investors and helps to explain the ongoing disagreement in the portfolio literature concerning the effectiveness of risk-adjusted portfolios and equal-weighted portfolios when the number of assets is small.     

Intraday bidirectional volatility spillover across international stock markets: does the global financial crisis matter?

This article studies volatility spillover between the US and the three largest European stock markets (Frankfurt, London and Paris) around the time of the recent Subprime crisis. In order to investigate the impact of the latter, we break our sample down into two sub-periods: a pre-crisis period and a post-crisis period, using a structural break test that has the advantage of endogenously testing for further breaks in the data. Unlike previous studies that have frequently investigated this issue using low frequency data, our article makes use of intraday data. Accordingly, using Threshold generalized autoregressive conditional heteroscedasticity (GARCH) model estimations, we find weak evidence of volatility transmission between the two regions before the Subprime crisis. However, during the post-crisis period, we record returns and volatility spillover from US to European markets and vice versa at different times of the trading day, indicating that the two regions became more dependent during the recent Subprime crisis, a finding that supports the contagion hypothesis between the US and European stock markets.     

FINANCIAL CRISES AND INTERNATIONAL STOCK MARKET VOLATILITY TRANSMISSION

This paper examines the interplay between stock market returns and their volatility, focusing on the Asian and global financial crises of 1997–98 and 2008–09 for Australia, Singapore, the UK, and the US. We use a multivariate generalised autoregressive conditional heteroskedasticity (MGARCH) model and weekly data (January 1992–June 2009). Based on the results obtained from the mean return equations, we could not find any significant impact on returns arising from the Asian crisis and more recent global financial crises across these four markets. However, both crises significantly increased the stock return volatilities across all of the four markets. Not surprisingly, it is also found that the US stock market is the most crucial market impacting on the volatilities of smaller economies such as Australia. Our results provide evidence of own and cross ARCH and GARCH effects among all four markets, suggesting the existence of significant volatility and cross volatility spillovers across all four markets. A high degree of time‐varying co‐volatility among these markets indicates that investors will be highly unlikely to benefit from diversifying their financial portfolio by acquiring stocks within these four countries only.     

On the relationship between energy returns and trading volume: a multifractal analysis

Forecasting and modelling commodities price movements and the activity of energy markets are of real interest to investors and policymakers, especially during turbulent times. This study investigates the volume–returns relationship for two major energy markets (oil and gas) during the recent global financial crisis. Unlike previous studies, we examine this relationship by applying an original fractal approach to intraday data, which has the advantage of accounting for further non-normality, nonstationarity, and fat-tailedness properties. Our study provides two interesting findings. First, we find a significant multifractal relationship between returns and volume in both markets and across all timescales, suggesting nonlinearity in the cross-correlation between returns and volume and rejecting the efficiency assumption. Second, the measure of multifractality in this relationship shows that the magnitude of the fluctuations during bearish and bullish trends affects the volume–return relationship differently, and that the oil market exhibits higher volatility than does the gas market.     

The linkages,persistence, asymmetry in the volatility,the price discovery and efficiency,and the effect of the US subprime mortgage financial crisis on the spot and the futures market’s returns: the case of India

This article examines the effects of persistence, asymmetry and the US subprime mortgage crisis on the volatility of the returns and also the price discovery, efficiency and the linkages and causality between the spot and futures volatility by using various classes of the ARCH and GARCH models, and through the Granger’s causality. We have used two indices: one for spot and the other for futures, for the daily data from 12 June 2000 to 30 September 2013 from Nifty stock indices. We have then tested for ARCH effects, and subsequently employed various models of the ARCH and GARCH conditional volatility. The GARCH(1,1) model is found to be significant, and it implies that the returns are not autocorrelated and have ‘short memory’. It supports the hypothesis of the efficiency of the markets. The negative ‘news’ has more significant effect on volatility, corroborating the ‘leverage impact’ in finance on market volatility. We have also tested the volatility spillover effects. The two methods we employed support the spillover effects and the causality is bidirectional. We also have used the dummy variable for the US subprime mortgage financial crisis and found that they are statistically significant. Indian stock market is thus integrated to the world stock markets.     

人民币NDF与即期汇率的动态关联性研究

文章以2005年7月25日~2006年6月13日间人民币NDF和即期汇率为研究对象,以MA(1)-GARCH(1,1)模型分析人民币NDF市场和即期市场间均值和波动的溢出效应。分析结果表明,两个市场的波动没有相互溢出效应,即期市场对人民币NDF市场没有报酬溢出效应,而人民币NDF市场对即期市场具有报酬溢出效应。可见,我国汇制改革后,境外因素已开始影响人民币即期市场。     

Modeling the volatility of futures return in rubber and oil—A Copula-based GARCH model approach

This paper attempts to make use of a Copula-based GARCH (Generalized AutoRegressive Conditional Heteroskedasticity) Model to find out the relationships between the volatility of rubber futures returns in the Agricultural Futures Exchange of Thailand (AFET) and other four main markets, namely, the volatility of rubber futures returns in the Singapore Commodity Exchange (SICOM), the volatility of rubber futures returns, crude oil returns, and gas oil returns in the Tokyo Commodity Exchange (TOCOM). The results illustrate that the Student-t dependence only shows better explanatory power than the Gaussian dependence structure and the persistence pertaining to the dependence structure between rubber futures returns in AFET and oil futures returns, namely, crude oil futures returns and gas oil futures returns in TOCOM. Whereas, the Gaussian dependence shows better explanatory ability between rubber futures returns in AFET and other rubber futures returns, namely, the volatility of rubber futures in SICOM and TOCOM. For the multivariate Copula model, all the parameters between AFET and other variables are significant. Based on these results, with the liberalization of agricultural trade and the withdrawal of government support to agricultural producers, there is in many countries a new need for price discovery and even physical trading mechanisms, a need that can often be met by commodity futures exchanges. Hence, this paper recommends that the government supports the hedge mutual funds that can be invested in every commodities futures exchange in the world. It can also put the funds together that will contribute farmers to invest in each commodities futures market.     

IDENTIFYING INTERDEPENDENCIES BETWEEN SOUTH-EAST ASIAN STOCK MARKETS: A NON-LINEAR APPROACH

This paper considers the question of how shocks to returns are transmitted across South-East Asian equity markets. Using a reasonably general statistical model our results suggest that a negative-return innovation leads to higher levels of domestic volatility than a positive innovation of equal magnitude. There is strong evidence that returns shocks are transmitted across markets, impacting not only on prices, but also on volatility. Any shock, positive or negative, serves to raise volatility.     

Does speculation Granger cause return in Chinese commodity markets?

We test the Granger causal relations between speculation and returns in Chinese commodity markets using quantile regression method. We find that speculation Granger causes returns in rebar, bean pulp and rapeseed oil markets. At lower quantiles, estimates are negative; but estimates are positive at upper quantiles. This indicates that larger speculation results in larger return volatility.     

Cross-sectional and time-series momentum returns and market dynamics: evidence from Japan

We test the behavioural theories of overconfidence and underreaction on cross-sectional (CS) and time-series (TS) momentum returns in the Japanese stock markets. Both CS and TS momentum returns are large and significant when the market continues in the same state and turns into losses when the market transitions to another state, consistent with the overconfidence but not the underreaction model. We find that TS conditional momentum returns exceed conditional CS momentum returns because of its active position since TS takes a net long (short) position following UP (DN) markets while CS is a zero-cost strategy irrespective of the market state. Finally, we find no relation between idiosyncratic volatility (IV) and momentum returns which is not supportive of either the overconfidence or underreaction model but implies that IV is not a significant limit to arbitrage in Japan.     

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.     

Intraday return and volatility relationships between the Ibex 35 spot and futures markets

This paper analyses the intraday lead-lag relationships between returns and volatilities in the Ibex 35 spot and futures markets. Using hourly data, we jointly analyze the interactions between markets, estimating a bivariate error correction model with GARCH perturbations which captures stochastically the presence of an intraday U-shaped curve for both spot and futures market volatility. Our findings show a bidirectional causal relationship between market volatilities, with a positive feedback. This two-way transmission of volatility is consistent with market prices evolving according to a long-run equilibrium relationship, and shocks affecting both markets in the same direction. Our empirical results also support a unidirectional cross interaction from futures to spot market returns. This pattern suggests that the futures market leads the spot market in order to incorporate the arrival of new information.     

Tail risk in emerging markets of Southeastern Europe

This article examines the left-tail behaviour of returns on stocks in Southeastern Europe (SEE). We apply conditional extreme value theory (EVT) approach on daily returns of six stock market indices from SEE between 2004 and 2013. Predictive performance of value-at-risk (VaR) and expected shortfall (ES) based on EVT is compared against several alternatives, such as historical simulation and analytical approach based on GARCH with a single conditional distribution. Model backtesting with daily returns shows that EVT-based models provide more reliable VaR and ES forecasts than the alternative models in all six markets. Unlike the alternatives, the EVT-based models cannot be rejected as VaR confidence level is increased. This emphasizes the importance of extreme events in SEE markets and indicates that the ability of a model to capture volatility clustering accurately is not sufficient for a correct assessment of risk in these markets.     

亚洲金融危机后亚洲各国汇市的波动特征改变了吗

亚洲金融危机首先爆发在各国的汇市上。危机过后多年,亚洲汇市的波动与危机前的状况有实质性改变吗?本文运用GARCH模型比较了亚洲各国及地区(韩国、泰国、台湾地区、新加坡、日本、印度、马来西亚和中国)汇市波动变化并进行了排序。实证结果表明,亚洲危机后各国汇市波动的方差扩大,冲击的影响在汇市上持续时间也有所延长。其原因是亚洲各国汇市的联动增加了。为了确保在第三国市场的份额,各国都在频繁调整和干预本国汇市。