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.     

Does economic policy uncertainty matter for commodity market in China? Evidence from quantile regression

ABSTRACT

This paper investigates the effect of economic policy uncertainty (EPU) on China’s agricultural and metal commodity futures returns across quantiles. We address this issue using the panel quantile regression approach, which allows for a more complete analysis of various conditions in the commodity market (i.e. bearish, normal, and bullish markets). Our empirical results reveal that domestic EPU shocks have a significantly negative effect on agricultural futures returns in bearish markets and a significantly positive effect on metal futures returns in bullish markets. The impacts of both domestic and U.S. EPU shocks on commodity markets are heterogeneous across quantiles and are sector specific. Additionally, by isolating positive and negative EPU shocks, the regression and test results indicate an asymmetric response of commodity futures prices in bullish markets. Moreover, our findings indicate that the metal futures market has a higher financialisation level than the agricultural futures market. The findings can be utilized by policymakers and investors.     

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.     

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.     

Is ‘oil and gas’ industry of ASEAN5 countries integrated with the US counterpart?

ABSTRACT

This paper employs the VARMA-MGARCH-ABEKK model and Granger causality on 15 years’ daily time series data to examine investment opportunities in the oil and gas industries for ASEAN5 countries relative to the US counterpart. It shows that the latter leads the former in decomposing integration into cross-country effects on returns and conditional return volatilities. The empirical results show that investors can gain an international intra-industry diversification benefit in Malaysia, the Philippines, Singapore and Vietnam by holding US oil and gas assets in their portfolios whereas Asian oil and gas assets may result in negative shocks due to the increase in return volatilities for Malaysia, Singapore and Vietnam. However, Thailand are insensitive to the cross-country intra-industry diversification. While making trading decisions, investors should be aware of the impulse responses of ASEAN oil and gas markets from the shocks in the US and the Asian markets and their asymmetric spill over effects.     

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.     

Volatility spillovers across daytime and overnight information between China and world equity markets

This article explores the transmission of daytime and overnight information in terms of returns and volatility between Chinese and Asian, European and North American main stock markets. We propose a bivariate analysis with China as benchmark. By testing the constancy of the conditional correlations, we use an extended constant or dynamic conditional correlation GARCH model. The empirical findings show that across the daytime information transmissions, the relationships between China and Asian markets are closer than China and non-Asian markets, whereas through the overnight information transmissions these relationships are inverse. The analysis provides, before the crisis, that the overnight volatility spillover effects are from China to the United States and the United Kingdom. During the crisis, China affects the United Kingdom in terms of daytime volatility spillovers, whereas in terms of overnight volatility spillovers China affects the United States and is influenced by Japan. After the crisis, daytime volatility spillovers are from Taiwan to China, whereas the overnight volatility spillover effects are from China to the United States and the United Kingdom.     

Volatility spillover and multivariate volatility impulse response analysis of GFC news events

This article applies two measures to assess spillovers across markets: the Diebold and Yilmaz’s (2012) spillover index and the Hafner and Herwartz’s (2006) analysis of multivariate GARCH models using volatility impulse response analysis. We use two sets of data, daily realized volatility (RV) estimates taken from the Oxford-Man RV library, for the S&P500 and the FTSE, plus 10 years of daily returns series for the New York Stock Exchange Index and the FTSE 100 index. Both data sets capture both the global Financial Crisis (GFC) and the subsequent European Sovereign Debt Crisis (ESDC). The spillover index captures the transmission of volatility to and from markets, plus net spillovers. The Volatility Impulse Responses (VIRF) have to be calibrated to conditional volatility estimated at a particular point in time. We explore the impact of three different shocks, the onset of the GFC, the height of the GFC, and the impact of the ESDC. Our modelling includes leverage and asymmetric effects applying a multivariate GARCH model, and further analysis using both BEKK and diagonal BEKK (DBEKK) models. We find the impact of negative shocks is larger, but shorter in duration, in this case a difference between 3 and 6 months.     

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.     

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 heterogeneous dependence between global crude oil and Chinese commodity futures markets: evidence from quantile regression

This paper explores the dependence between global crude oil and Chinese commodity futures markets across different quantiles of the return distributions. Based on weekly data from 11 June 2004 to 7 July 2017, we address this issue by applying a quantile regression method. This technique provides a more detailed investigation of the dependence. Moreover, considering the structural breaks caused by market turmoil or financial crises, we divide the full period of every commodity sector market into sub-periods based on these break dates to further explore the dependence changes. The empirical results indicate that the dependence between global crude oil and Chinese commodity futures markets is different across quantiles in different commodity sectors. The dependence is significantly positive, except in markets with high expected returns. Additionally, the effects caused by structural breaks are distinctly heterogeneous across quantiles. The effect of the same break on the degree of dependence exhibits an increasing tendency as the quantile level increases, which suggests that markets with high expected returns are more susceptible to crises. Finally, we apply a prediction analysis to further verify the heterogeneity of the commodity sectors, which may be the cause of the heterogeneous dependence.     

The Chinese Stock Market Does not React to the Japanese Market: Using Intraday Data to Analyse Return and Volatility Spillover Effects

In this paper, we use high‐frequency data to explore the effects of return and volatility spillover during periods in which trading hours in China and Japan overlap. Specifically, we utilize 5‐min returns to estimate fractionally integrated asymmetric power autoregressive conditional heteroskedasticity and fractionally integrated exponential generalized autoregressive conditional heteroskedasticity models, then use the models' standardized residuals to employ a cross‐correlation function approach that tests for the degree to which the Chinese and Japanese markets affect each other. Results indicate a unidirectional influence of the Chinese stock market on Japanese markets in terms of return. This result is likely attributable to restrictions on foreign investment in the Chinese market and the lack of diversified international portfolios among individual Chinese investors.     

Portfolio style: Return-based attribution using quantile regression

Return-based classification identifies a portfolio's style signature in the time series of its returns. Detection is based on a regression of portfolio returns on returns of factor mimicking indices. The method is easy to apply and does not require information about portfolio composition. Classification using least squares means that style is determined by the way factor exposure influences expected returns. We introduce regression quantiles as a complement to the standard analysis. The regression quantiles extract additional information from the time series of returns by identifying the way style affects returns at places other than the expected value. This allows discrimination among portfolios that would be otherwise judged equivalent based on conditional expectations. It also provides direct information about the impact of style on the tails of the conditional return distribution. Simple examples are presented to illustrate regression quantile classification.     

How are Africa's emerging stock markets related to advanced markets? Evidence from copulas

The finance literature provides ample evidence that diversification benefits hinges on dependence between assets returns. A notable feature of the recent financial crisis is the extent to which assets that had hitherto moved mostly independently suddenly moved together resulting in joint losses in most advanced markets. This provides grounds to uncover the relative potential of African markets to provide diversification benefits by means of their correlation with advanced markets. Therefore, we examine the dependence structure between advanced and emerging African stock markets using copulas. Several findings are documented. First, dependence is time-varying and weak for most African markets, except South Africa. Second, we find evidence of asymmetric dependence, suggesting that stock return comovement varies in bearish and bullish markets. Third, extreme downward stock price movements in the advanced markets do not have significant spillover effects on Africa’s emerging stock markets. Our results, implying that African markets, with the exception of South Africa, are immune to risk spillover from advanced markets, improves the extant literature and have implications for portfolio diversification and risk management.     

Monetary environments and stock returns revisited: A quantile regression approach

We investigate the impact of monetary conditions on stock market returns at different points on the return distributions. Our results reveal no association between stock returns and monetary environments at the lower quantiles. At the upper quantiles, however, we find that expansive monetary conditions lead to significantly larger stock returns. The relationship between returns and monetary conditions at the upper quantiles is also found to be asymmetric, exhibiting a monotonic increase in responsiveness at successive quantiles.     

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.     

Dynamic linkages between Asian stock prices and exchange rates: new evidence from causality in quantiles

This article applies the Granger causality test in quantiles to investigate causal relations between stock returns and exchange rate changes for nine Asian markets over the period 1 January 1997 to 16 August 2010. Our empirical results indicate that the quantile causal relations vary across different quantiles and different periods. Although the causal effects of exchange rate changes on stock returns (or stock returns on exchange rate changes) are heterogeneous across quantiles, the overall evidence suggests that most stock and foreign exchange markets are negatively correlated. The result shows that there are more bidirectional causal relations in accordance with this method than the conventional least square (LS) estimation. The symmetry of these quantile causal effects (the ‘averaging effect’) helps to explain why conventional LS method usually obtains an insignificant result of causality.     

Linear and non-linear transmission of equity return volatility: evidence from the US, Japan and Australia

This paper models the transmission of shocks between the US, Japanese and Australian equity markets. Tests for the existence of linear and non-linear transmission of volatility across the markets are performed using parametric and non-parametric techniques. In particular the size and sign of return innovations are important factors in determining the degree of spillovers in volatility. It is found that a multivariate asymmetric GARCH formulation can explain almost all of the non-linear causality between markets. These results have important implications for the construction of models and forecasts of international equity returns.     

Okun’s law revisited: a threshold in regression quantiles approach

This article proposes, for the first time, a threshold in regression quantiles approach to the analysis of Okun’s law. By applying to US data over the 1948Q1–2016Q4 period, we have three major findings. First, a single threshold is detected for both multiple and individual quantiles cases. However, the effect of threshold nonlinearity is only present in the middle to upper quantiles of the conditional unemployment distribution in the individual quantiles case. Second, the first-order autoregressive coefficients of unemployment are significantly larger in the lower-growth regime, indicating that shocks to unemployment appear to be more persistent during recessions. Finally, the Okun’s coefficients are all negative across the recessionary and expansionary regimes, confirming the validity of Okun’s law. Moreover, the Okun’s coefficients are smaller (more negative) in the lower-growth regime, suggesting that the effect of differenced output on differenced unemployment is asymmetric, and is more pronounced in recessions.     

Causal effects of the United States and Japan on Pacific-Rim stock markets: nonparametric quantile causality approach

This article adopts a nonparametric quantile causality approach to examine the causal effects of the U.S. and Japan stock markets on the stock markets of the Pacific-Rim region. This approach allows us to detect not only nonlinear causalities in conditional return (mean) and conditional volatility (variance) but also the asymmetries of causalities under extreme market conditions (bullish vs. bearish states). Our results provide significant evidence of causality in return and volatility at different points of the conditional distributions of returns, with the greater effects from the U.S. than from Japan. Asymmetric quantile causality patterns are particularly pronounced in the case of Japan.