Asymmetric risk spillovers between Shanghai and Hong Kong stock markets under China’s capital account liberalization

In this paper, we investigate the asymmetric risk spillovers between Shanghai and Hong Kong stock markets under the backdrop of China’s capital account liberalization by measuring the Conditional Value-at-Risk (CoVaR) based on adjusted realized volatilities and variational mode decomposition based copula model. The empirical results show that, the asymmetric features of risk spillovers between the two markets are significant and manifest different states before and after the Shanghai-Hong Kong Stock Connect and Shenzhen-Hong Kong Stock Connect schemes. More specifically, first, the downside risk spillovers from Hong Kong to Shanghai are significantly larger than its upside risk spillovers, while the risk spillovers from Shanghai to Hong Kong is on the contrary. Second, the short-run risk spillovers are more drastic than the long-run risk spillovers, except the risk spillovers from Shanghai to Hong Kong after the Shenzhen-Hong Kong Stock Connect scheme. Finally, by comparing the risk spillovers from two directions, the importance of Shanghai stock market gradually rises up with the implementations of Stock Connect schemes.     

Intraday Volatility Spillover between the Shanghai and Hong Kong Stock Markets—Evidence from A+H Shares after the Launch of the Shanghai-Hong Kong Stock Connect

Using minute data of eligible A+H stocks under the Shanghai-Hong Kong Stock Connect (SHHKSC), we investigate the volatility spillover between the Shanghai and Hong Kong stock markets based on a generalized autoregressive conditional heteroskedasticity-X (GARCH-X) model with four exogenous variables, namely, volatilities of the corresponding stocks on the other market, volatilities of the indexes of both stock markets, and volatilities of the correlated stocks, which are selected using the dynamic conditional correlation model and bootstrap approach. Results show that after the launch of the SHHKSC, volatility spillovers are significant in both directions almost all the time, and the volatility spillover between the two stock markets tends to be larger when bidirectional capital flows under the SHHKSC increase or when important financial events occur. We also analyze the influences of the volatilities of correlated stocks and industries on the volatility spillover and volatilities of A+H stocks. The bidirectional volatility spillovers between Shanghai and Hong Kong stock markets do not change qualitatively after incorporating the volatilities of correlated stocks and industries in the GARCH-X model. Moreover, the average volatilities of the correlated stocks are shown to have significant influences on the volatilities of individual A+H stocks, and the influences increase when the local stock market shows a sharp rise or fall. Compared with the market indexes, the correlated stocks could be regarded as a more important and indispensable factor for individual A+H stocks’ volatilities modeling, which may carry more information than the industry.     

Extreme risk transmission channels between the stock index futures and spot markets: Evidence from China

We develop a skewness-dependent multivariate conditional autoregressive value at risk model (SDMV-CAViaR) to detect the extreme risk transmission channels between the Chinese stock index futures and spot markets. The proposed SDMV-CAViaR model improves the forecast performance of extreme risk by introducing the high-frequency realized skewness. Specifically, the realized skewness has a significant impact on the spillovers, but the realized volatility and realized kurtosis do not, which implies that the jump component plays an important role in extreme risk spillovers. The empirical results indicate there are bidirectional extreme risk spillovers between the stock index futures and spot markets, the decline of one market has direct and indirect channels to exacerbate the extreme risk of the other market. Firstly, the market decline will directly increase the extreme risk of related markets by decreasing market returns. Besides, the decline will indirectly increase the extreme risk by increasing the negative realized skewness and extreme risk spillovers.     

The asymmetric effect of crude oil prices on stock prices in major international financial markets

The aim of this paper is to explore the potential asymmetric impacts of positive and negative shocks in crude oil prices on stock prices in six major international financial markets which include China, Hong Kong, America, Japan, Britain, and Germany. We test for these asymmetric effects on 8 major international financial markets indices over the 2007M01–2020M03 periods. Our independent measures include the prices of Brent crude oil futures and West Texas Intermediate (WTI) futures. We use the nonlinear ARDL (NARDL) model proposed by Shin et al. (2014), which can capture both short- and long-run nonlinearities through positive and negative partial sum decompositions of the explanatory variables. This research finds that positive and negative fluctuations of oil price have asymmetric effects on stock price index in four financial markets, but the performance of the asymmetry is different. Specifically, the impacts of volatility in oil prices on two indices of Chinese stock prices are different, and the asymmetric effects of oil price volatility on stock price indices in China and other financial markets are significantly different.     

Measuring extreme risk spillovers across international stock markets: A quantile variance decomposition analysis

This paper proposes a quantile variance decomposition framework for measuring extreme risk spillover effects across international stock markets. The framework extends the spillover index approach suggested by Diebold and Yilmaz (2009) using a quantile regression analysis instead of the ordinary least squares estimation. Thus, the framework provides a new tool for further study into the extreme risk spillover effects. The model is applied to G7 and BRICS stock markets, from which new insights emerged as to the extreme risk spillovers across G7 and BRICS stock markets, and revealed how extreme risk spillover across developed and emerging stock markets. These findings have important implications for market regulators.     

Risk spillovers and hedge strategies between global crude oil markets and stock markets: Do regime switching processes combining long memory and asymmetry matter?

This paper investigates risk spillovers and hedge strategies between global crude oil markets and stock markets. In the paper, we propose a multivariate long memory and asymmetry GARCH framework that integrates state-dependent regime switching in the mean process with multivariate long memory and asymmetry GARCH in the variance process. Our results first show that there are linear risk spillovers running from the US stock markets to the WTI oil market in the short term. However, the linear risk spillover effect running from the oil market to the US stock market can only exist in the long term. In addition, there is a bidirectional linear risk spillover effect between the European stock markets and the Brent oil market in the short and long terms. Furthermore, there is no linear risk spillover effect between the Dubai oil market and the Chinese stock market. Second, the nonlinear risk spillovers running from the WTI oil market to the US stock market can be found in the tranquil regime. Moreover, there is also a nonlinear risk spillover effect running from the European stock markets to the Brent oil market in the tranquil regime. In addition, the nonlinear risk spillover effect running from the Brent oil markets to the European stock market can be found in the crisis regime. Furthermore, there is bidirectional nonlinear Granger causality between the Dubai crude oil market and the Chinese stock market in the tranquil regime. Finally, dynamic hedge effectiveness shows that the regime switching process combined with long memory and asymmetry behavior seems to be a plausible and feasible way to conduct hedge strategies between the global crude oil markets and stock markets.     

Volatility spillovers among the U.S. and Asian stock markets: A comparison between the periods of Asian currency crisis and subprime credit crisis

This paper examines the changing nature of volatility spillovers among the U.S. and eight East Asian stock markets between two financial crises: the Asian currency crisis and the U.S. subprime credit crisis. Our empirical results suggest that volatility is not always spilled over from the directly affected markets to surrounding markets in crisis periods. The East Asian markets who directly suffered from the Asian currency crisis are the ones to which volatility is spilled over from other markets during the Asian currency crisis period, whereas uni-directional volatility spillovers from the U.S. market to other markets are observed during both crisis periods. This difference can be explained by a pre-determined hierarchy in which volatility spillovers tend to start from the U.S. market regardless of the geographical origin of the crisis. Furthermore, our results reveal that the markets in three major Asian financial hubs, i.e., Japan, Hong Kong and Singapore, are the markets to which volatility is spilled over uni-directionally from several other countries during the subprime credit crisis period, but not during the Asian currency crisis period. We attribute this difference to crisis-specific (currency or credit crisis), market-specific (credit derivatives market participation and foreign currency reserves), and time-specific (more integrated global market) factors.     

The impact of China's stock market reforms on its international stock market linkages

This paper investigates how China's stock market reforms have affected the stock market linkages between China and Korea, Japan and the US respectively. We firstly use a 4 × 4 asymmetric GARCH-BEKK model and a series of likelihood ratio tests to uncover China's regional and global linkages between 1992 and 2010 and during three sub-periods representing the stages of the Chinese reforms. The results show that Chinese stock market is linked to these overseas markets and the reforms permit spillovers to these markets from China. The subsequent regression analyses of the time-varying conditional correlations, in the presence of growing economic integration, exchange rate risk and financial turbulence, further indicate that the interdependences between China and the regional markets increase due to the implementation of liberalisation policies. However, the correlation between China and the global market remains weak even though this correlation responds positively to the institutional reforms on China's stock market additionally.     

Chinese Lunar New Year effect in Asian stock markets, 1999–2012

This study investigates the Chinese Lunar New Year (CLNY) holiday effect in major Asian stock markets. These are China, Hong Kong, Japan, Malaysia, South Korea and Taiwan. For robustness test, India is also examined in this paper. Daily stock index returns for each market are analysed for the period of 01/09/1999 to 28/03/2012. Using an ARMA(1,1)-GARCH (1,1) model, we find that there is a significantly positive pre-CLNY holiday effect for all cases. The findings are robust for most cases with the exception of China. It is found that high pre-CLNY returns for China are rewards for high risk, whereas for the other markets, high returns are caused by unknown factors, other than the conditional risk.     

COVID-19 and asymmetric volatility spillovers across global stock markets

In this study, I improve the assessment of asymmetry in volatility spillovers, and define six asymmetric spillover indexes. Employing Diebold-Yilmaz spillover index, network analysis, and my developed asymmetric spillover index, this study investigates the time-varying volatility spillovers and asymmetry in spillovers across stock markets of the U.S., Japan, Germany, the U.K., France, Italy, Canada, China, India, and Brazil based on high-frequency data from June 1, 2009, to August 28, 2020. I find that the global markets are well connected, and volatility spillovers across global stock markets are time-varying, crisis-sensitive, and asymmetric. Developed markets are the main risk transmitters, and emerging markets are the main risk receivers. Downside risk dominates financial contagion effects, and a great deal of downside risk spilled over from stock markets of risk transmitters into the global markets. Moreover, during the coronavirus recession, the total degree of volatility spillover is staying at an extremely high level, and emerging markets are the main risk receivers in the 2020 stock markets crash.     

Dynamic interaction of risk–return trade-offs between oil market and China’s stock market: An analysis from the risk preferences perspective

The risk–return trade-off refers to the compensation required by investors for bearing risks, which can be viewed as the risk preference of investors in a market. The current study investigates the dynamic interdependence of risk–return trade-offs between China’s stock market and the crude oil market from the perspective of risk preference of investors, which is designed to explore the transmission process of investors’ risk preference in both markets. Specifically, this study applies the time-varying parameter GARCH-M model, namely TVP-GARCH-M model, to characterize the time-dependent risk–return trade-offs (investors’ risk preferences) in the crude oil and China’s stock markets, then examines their relationship through Granger causality tests. Results show that a variation in risk preferences of the oil market investors can dramatically cause a variation in risk preferences of the Chinese stock market investors, while the risk preference of investors in the Chinese stock market does not lead to that in the crude oil market, which is in accordance with expectations. The dynamic effect of investors’ risk appetite in the crude oil market is further examined by the TVP-VAR model. The findings of this work suggest that there generally exists a positive impact of investors’ risk preference in the oil market and that the effect is time-varying to a greater degree during the short and medium term. Moreover, responses of the Chinese stock market investors’ risk preference were more significant during the 2008 financial crisis. Additionally, the empirical results remain robust when applying alternative crude oil prices and China’s stock prices.     

Dynamic behaviors and contributing factors of volatility spillovers across G7 stock markets

This paper investigates the evolutions and determinants of volatility spillover dynamics in G7 stock markets in a time-frequency framework. We decompose volatility spillovers into short-, medium-, and long-term components, using a spectral representation of variance decompositions. The impacts of hypothesized factors on the decomposed volatility spillovers are also examined, using a linear regression model and fixed effects panel model. We find that the volatility spillovers across G7 stock markets are crisis-sensitive and are, in fact, closer to a memory-less process. The low-frequency components are the main contributors to the volatility spillovers; the high-frequency components are very sensitive to market event shocks. Moreover, our results reveal that the contributing factors have different effects on short-, medium-, and long-term volatility spillovers. There is no systematic pattern of the impacts of the contributing factors on volatility spillovers. However, whether the country is the transmitter or recipient of volatility spillovers could be a potential reason.     

Risk spillover and network connectedness analysis of China’s green bond and financial markets: Evidence from financial events of 2015–2020

This study investigated the dynamic return and volatility spillovers, together with the network connectedness analysis between China’s green bond and main financial markets. Based on a multidimensional DCC-GJRGARCH model and the spillover index method, we found significant two-way risk spillovers between the green bond market and traditional bond markets. Moreover, the green bond market was subject to one-way risk spillover from the stock and commodities markets. Meanwhile, risk spillovers between the green bond market, forex market, and monetary market were not significant. Finally, network connectedness analysis provided specific information about connectivity and strength during different subperiods corresponding to financial events. The analysis indicated that under the influence of emergencies, China’s financial market will enhance the risk-spillover level by transforming the same type of market’s internal spillover into cross-market spillover.     

股指期货投资策略与技巧

随着股指期货的渐行渐近,人们对股指期货的关注程度也在日益提高。作为中国内地第一个金融期货产品的沪深300指数期货,有其与其他金融产品不同的投资方法,并且有一定的复杂性。沪深300指数期货的主要用途有两个:利用沪深300指数期货对股票投资组合进行风险管理以及进行套利活动来获取无风险利润。正确认识股指期货并且能熟练掌握股指期货的投资策略对于投资者而言是十分重要的。文章阐述了股指期货两种投资用途的投资策略与技巧。     

Value at risk and return in Chinese and the US stock markets: Double long memory and fractional cointegration

Given that the United States is an engine of global stock market while China is the largest emerging market with a cornucopia of anomalies in particular, it is vital to investigate the risk-return relationship in the two markets. This paper brings new insights not only into risk-return tradeoff, but also to the leverage effect, with the application of the fractionally co-integrated vector auto-regression (FCVAR) model capturing the fractional cointegrated relationship and long memory property. Results show that China stock markets own the property of double long memory but the US markets don’t. Most of all, in the US market, a positive risk-return tradeoff exists for the whole sample while after the crisis, even we find the negative relation, it’s not a volatility feedback effect but low risk and high returns. However, there is only a volatility feedback effect in China stock markets. Besides, there is a leverage effect in the US market, while Chinese market exhibits a reverse one, another anomaly, indicating significant difference in the two markets again.     

Economic policy uncertainty and stock market sector time-varying spillover effect: Evidence from China

This paper investigates the volatility spillover effect among the Chinese economic policy uncertainty index, stock markets, gold and oil by employing the time-varying parameter vector autoregressive (TVP-VAR) model. Three main results are obtained. Firstly, the optional consumption, industry, public utility and financial sectors are systemically important during the sample period. Secondly, among the four policy uncertainties, the uncertainty of fiscal policy and trade policy contributes more to the spillover effect, while the uncertainty of monetary policy and exchange rate policy contributes less to the spillover effect. Thirdly, during COVID-19, oil spillovers from other sources dropped rapidly to a very low point, it also had a significant impact on the net volatility spillover of the stock market. This paper can provide policy implication for decision-makers and reasonable risk aversion methods for investors.     

Risk spillovers and portfolio management between developed and BRICS stock markets

This paper investigates spillover effects and portfolio diversification between the four major developed stock markets (USA, Europe, Japan and Asia) and five of the most important emerging stock markets known as the BRICS (Brazil, Russia, India, China and South Africa). To this end, we apply the multivariate DECO-FIEGARCH model to daily spot indices during the period 1998–2016. The results reveal a significant and asymmetric long memory process for both the developed and the BRICS markets. Moreover, we find a significant variability in the time-varying conditional correlations between the considered markets during both bull and bear markets, particularly from early 2007 to summer 2008. Additionally, we analyze the optimal portfolio weights, time-varying hedge ratios and hedging effectiveness based on the estimates of the model. The results underline the importance of overweighting the optimal portfolios with stocks from the developed countries over those from the BRICS. Finally, we assess the practical implications for mixed developed-BRICS stock portfolios, based on finding strong evidence of diversification benefits and downside risk reductions that confirm the usefulness of using developed market stocks in the BRICS stock portfolio risk management.     

Dynamic spillover and connectedness between oil futures and European bonds

This paper examines the spillovers and connectedness between crude oil futures and European bond markets (EBMs) having different maturities. We also analyze the hedging effectiveness of crude oil futures-bond portfolios in tranquil and turbulent periods. Using the spillovers index of Diebold and Yilmaz (2012, 2014), we show evidence of time-varying spillovers between markets under investigations, which varies between 65% and 83%. Moreover, three-month, six-month, one-year, three-year and thirty-year bonds and crude oil futures are net receivers of risk from other markets, whereas the remaining bonds are net contributors of risk to the other markets. Crude oil futures receive more risk from long-term than short-term bonds. Moreover, the magnitude of risk transmission is low for the pre-crisis and economic recovery periods. Crude oil futures market contributes significantly to the risk of other markets during the oil crisis and Brexit period. A portfolio risk analysis shows that that most investments should be in oil rather than bonds (except the short-term bonds). The hedge ratio is sensitive to market conditions, where the cost of hedging increases during GFC and ESDC period. Finally, a crude oil futures-bond portfolio offers the best hedging effectiveness during the COVID-19 pandemic period.     

Conditional correlations and volatility spillovers between crude oil and stock index returns

This paper investigates the conditional correlations and volatility spillovers between the crude oil and financial markets, based on crude oil returns and stock index returns. Daily returns from 2 January 1998 to 4 November 2009 of the crude oil spot, forward and futures prices from the WTI and Brent markets, and the FTSE100, NYSE, Dow Jones and S&P500 stock index returns, are analysed using the CCC model of Bollerslev (1990), VARMA-GARCH model of Ling and McAleer (2003), VARMA-AGARCH model of McAleer, Hoti, and Chan (2008), and DCC model of Engle (2002). Based on the CCC model, the estimates of conditional correlations for returns across markets are very low, and some are not statistically significant, which means the conditional shocks are correlated only in the same market and not across markets. However, the DCC estimates of the conditional correlations are always significant. This result makes it clear that the assumption of constant conditional correlations is not supported empirically. Surprisingly, the empirical results from the VARMA-GARCH and VARMA-AGARCH models provide little evidence of volatility spillovers between the crude oil and financial markets. The evidence of asymmetric effects of negative and positive shocks of equal magnitude on the conditional variances suggests that VARMA-AGARCH is superior to VARMA-GARCH and CCC.     

Frontier stock market integration and the global financial crisis

This paper examines the stock market integration between frontier and leading markets, focusing on the periods of pre and post global financial crisis. Using time-series analysis, the results mostly support leading markets can Granger-cause frontier markets. Frontier markets in different regions have distinct relationships with leading markets. Population growth, industry value, interest rate, tax rate, and tariff of the frontier markets significantly influence the integration between both markets. Energy, gross national income, stock traded value, and high-technology exports of leading markets saliently influence the integration. Finally, the global financial crisis impacts the relationship between the frontier and leading markets and changes the determinants of stock market integration.