Spillovers from the USA to stock markets in Asia: a quantile regression approach

This article analyses return spillovers from the USA to stock markets in Asia by means of quantile regressions. Traditional studies consider spillovers as effects of the conditional means of foreign returns onto the conditional means of chronologically succeeding domestic markets’ returns. We, by contrast, study the full range of quantiles of the conditional distribution of the domestic markets’ returns. This enables us to document the detailed structure of spillovers across return quantiles. Generally, we find spillovers from the USA to Asia to be negative. Specifically, however, we reveal an asymmetric structure of spillovers with an increasing negative magnitude from lower to upper return quantiles. Theoretically, this pattern is consistent with an asymmetric overreaction of traders in Asia to news from the US market. Extensions from the baseline model further suggest the presence of contagion throughout the financial crisis of 2007–2008 as well as of calm-down effects over weekends.     

Evidence of the duration-dependence from the stock markets in the Pacific Rim economies

This article investigates the duration-dependent feature of five Pacific Rim economies. The duration-dependent Markov Switching model is employed to achieve this objective. The Savage–Dickey density ratio is also computed in support of the duration-dependent Markov switching model. The possible bull and bear market dates for each stock market are also identified by the posterior probability from the empirical model. It is unambiguous that Japan, South Korea and Hong Kong are all characterized by duration-dependence in a bear market but no duration-dependence in a bull market. In the case of Taiwan and Singapore, the duration-dependence feature holds for both the bear and bull markets.     

Bull or bear markets: A wavelet dynamic correlation perspective

In this paper, we contribute to the literature on the international stock market co-movements and contagion, especially during the recent subprime crisis, by researching the interconnections between international stock markets in time-frequency domain.Our innovative approach consists on carrying out a wavelet decomposition of return time series before investigating the correlation dynamics across stock markets during the recent financial crisis. It thus enables us to show how the contagion dynamics between international stock market returns are changing across time scales corresponding to investors with heterogeneous time horizons. Moreover, our results reveal that the contagion dynamics depends on the bull or bear periods of stock markets, on stock markets maturity, and on regional aspects. Therefore, all these finding should be considered from an international portfolio diversification perspective.     

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.     

Spillovers between Bitcoin and other assets during bear and bull markets

This article contributes to the embryonic literature on the relations between Bitcoin and conventional investments by studying return and volatility spillovers between this largest cryptocurrency and four asset classes (equities, stocks, commodities, currencies and bonds) in bear and bull market conditions. We conducted empirical analyses based on a smooth transition VAR GARCH-in-mean model covering daily data from 19 July 2010 to 31 October 2017. We found significant evidence that Bitcoin returns are related quite closely to those of most of the other assets studies, particularly commodities, and therefore, the Bitcoin market is not isolated completely. The significance and sign of the spillovers exhibited some differences in the two market conditions and in the direction of the spillovers, with greater evidence that Bitcoin receives more volatility than it transmits. Our findings have implications for investors and fund managers who are considering Bitcoin as part of their investment strategies and for policymakers concerned about the vulnerability that Bitcoin represents to the stability of the global financial system.     

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.     

Which Chinese Markets to Diversify into?

This paper investigates the correlation and feedback relationships between the Hong Kong Hang Seng Index (HSI), the Hang Seng Chinese Enterprise Index (CEI) and the S&P 500 Index (SP). We divide the indexes into two separate periods, from the inception of the CEI in 1994 to the stock market crash in 2000, and from 2001 to 2011. Our results show that the feedback relationship between the CEI and the SP is stronger after 2000. As the feedback relationship grows stronger, the diversification benefit reduces for US investors who utilizes the CEI as a tool for diversifying into Chinese markets.     

Return and volatility spillovers effects: Evaluating the impact of Shanghai-Hong Kong Stock Connect

This study investigates the impact of the recently introduced Shanghai-Hong Kong Stock Connect. Using high frequency data and dynamic forecasting techniques, we find that the new Stock Connect does contribute to the increasing importance of the Chinese mainland stock market and economic activity. A weak and unstable cointegration relationship is found after this event. Additionally, the Stock Connect has also increased the conditional variance of both stock markets. We observe a leading role of the Shanghai stock market to the Hong Kong stock market in terms of both mean and volatility spillover effects after the Stock Connect. Our study indicates that the opening up of stock markets in China could enhance the leading power, influence the risk level and improve the market efficiency of the Chinese mainland stock market, since the volatility spillover effect from Shanghai to Hong Kong is strengthened. Besides, our results have important policy implications, especially on how policy makers should deal with the increased market interconnectedness and for portfolio managers in choosing potential hedging instruments. The success of Shanghai-Hong Kong Stock Connect provides valuable operational experience for the forthcoming Shenzhen-Hong Kong Stock Connect which could further improve the market efficiency in China.     

In the Shadow of the United States: The International Transmission Effect of Asset Returns

We examine how fluctuations in financial and housing markets in the United States affect asset returns and GDP in Hong Kong. In contrast to studies using linear specifications, which find that the United States and Hong Kong are virtually delinked in terms of the asset markets, our regime‐switching models indicate that an unexpected change in US stock returns, followed by the TED spread, has the most significant effect on Hong Kong asset returns and GDP, typically in a regime of high return and low volatility. For in‐sample one‐step‐ahead forecasting, the US term spread is the best predictor.     

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.     

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.     

Two centuries of bull and bear market cycles

Very few economic phenomena attract more attention than bull and bear market cycles do, and there is also agreement that bull markets are associated with persistently rising share prices, strong investor interest, and enhanced financial well-being. This paper identifies bull and bear market turning points using a formal turning-point identification procedure and finds that the bull and bear market phases are associated with distinct and persistent mean return shifts. The analysis highlights return evidence that distinguishes bull markets as distinct investment return regimes. The paper also emphasizes the properties of bull markets that can be important to investors, including the persistence of return differences between bull and bear markets as well as interrelationships amongst bull markets and investor interest.     

Spillovers of volatility index: evidence from U.S., European,and Asian stock markets

We investigated the cross-market relations of volatility indexes with U.S. and non-U.S. stock market returns. We found that the pervasive VIX influence at both U.S. and non-U.S. stock markets. The VSTOXX and VKOSPI capture the major shocks to the global economy and show movements similar to the VIX. The empirical findings indicate that volatility index changes are important in explaining stock returns. We also examined spillover effects across volatility indexes. The VIX is a main transmitter, and the VKOSPI the main receiver, of these spillovers. The results point to a leading role for the VIX in the international market.     

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.     

A reliable performance measure to differentiate China’s actively managed open-end equity mutual funds

We compare different fund performance measures to examine which performance measures can generate risk-adjusted returns between high ranked and low ranked China’s actively managed open-end equity mutual funds. Our results show that only the six-factor (five factors (market, size, b/m, profitability & Investment facotrs) plus a momentum factor) alpha as the performance measure meets the criteria. Separated by the six-factor alpha, better performing funds have a larger asset under management, a better past 6-month cumulative return, a better stock picking ability, and a higher percentage of hybrid funds. Through our sample period from July 2004 to December 2015, the highest ranked quintile funds generate a monthly risk-adjusted return of 0.24% more than the lowest ranked quintile funds and the six-factor alpha reliably selects a better fund portfolio in both bear and bull markets on the basis of both fund return and holding data. Furthermore, our results from fund trading data show that funds with the highest six-factor alpha rank demonstrate a better trading skill in bear markets, suggesting that those better performing funds exhibit their market timing and stock picking abilities when investors need them most.     

The winner-loser anomaly: recent evidence from Greece

This article finds evidence of significant reversals in returns over the medium term in Greek stocks. In contrast with previous research, return reversals are more pronounced for past winners, suggesting that the market overreacts to a greater extent to good news. These contrarian returns are particularly elevated when portfolios are formed using quartiles and during tranquil and bull markets. The optimum contrarian strategy involves skipping the first 6 months of the holding period and implementing the contrarian strategy for a period of 18 months, as returns exhibit continuation followed by reversal. The profitability of the contrarian investment strategy is robust to adjustments for risk and seasonalities. It is the tranquil times and not the crisis/volatile times that generates a significant and profitable contrarian strategy. The recent credit crisis and resulting stock market falls, resulted in extreme movements in some Greek stocks and testing of the contrarian strategy problematic, especially when portfolios are decile ordered. Our findings also highlight the importance of survivorship bias and also suggest that contrarian strategies that just use market beta may be ill-equipped to take into consider extreme market movements, illiquidity and short-sales constraints.     

Impacts of China's crash on Asia-Pacific financial integration: Volatility interdependence,information transmission and market co-movement

This paper examines the price and volatility dynamics between China and major stock markets in the Asia-Pacific, investigating the effects of the Chinese stock market crash (2015–2016) for the first time. Employing the Bayesian VAR and BEKK GARCH, we observe that price and volatility spillover behaviours are different during the stable and stress periods. Particularly, price spillovers from China to other regional markets are more significant during a bullish period, showing that ‘good news’ emanating from China has strong impacts on its neighbours during better market condition. In the turbulent period, we observe strong shock spillover effects and enhanced volatility spillovers from China to most Asia-Pacific stock markets. This is because China, as an important trading partner and strategic financial centre shows to exert significant influence on the Asia-Pacific region through various economic channels. We also find that the Asia-Pacific stock markets spill over their shocks to China during the crisis, indicating that China is becoming more integrated with the regional financial markets.     

An empirical examination of factors driving the offshore renminbi market

Following the 2010 establishment of the offshore renminbi market in Hong Kong, renminbi deposits there quickly rose above RMB 1 trillion. In this article, we examine fluctuations between the offshore value of the renminbi in Hong Kong and its onshore value in mainland China. The size of the spot market spread appears to be influenced by stock market sentiment as reflected in the spread between A-shares listed in Shanghai and H-shares listed in Hong Kong. There is also some evidence of a link between the spread and the pace of renminbi deposit growth in Hong Kong.     

Intraday Stock Market Behavior After Shocks: The Importance of Bull and Bear Markets in Spain

The stock market behavior after different shocks has been analyzed from different points of view, but none has considered, as in this work, the possibility of combining different procedures, intraday returns over six days, and different phases of the markets in the Spanish stock market. The inconclusive results that we find following the previous empirical methodologies make way to interesting results when bull and bear markets are considered. We find that positive shocks are much more important than negative shocks, especially in downward trends where we find a significant overreaction effect that can be associated with the pessimism prevailing in a bear market after the “dead cat bounce” which represents those positive shocks.