Do bears and bulls swim across oceans? Market information transmission between greater China and the rest of the world

This study investigates returns and volatilities transmission across Greater China’s four emerging stock markets and three developed international markets, Tokyo, London, and New York. Using daily open and close price data from 1994 to 2001, we provide empirical evidence that the overnight returns on all the Greater China stock indices can be estimated by using information from at least one of the three developed markets’ daytime returns. The contemporaneous return spillovers are in general unidirectional from more advanced major international markets to the Chinese markets. However, split-sample analysis suggests that there is also evidence of bi-directional return spillovers after the 1997 Asian financial crisis. We also find that there are no one-period lagged return spillover effects from the three advanced markets to the Chinese markets, except for Taiwan. Finally, Mainland China’s two stock markets are not affected by contemporaneous nor delayed “bad news”.     

Integration of emerging stock markets with global stock markets

Financial integration for emerging economies should be seen as a long-term objective. In this paper, we examine stock market integration among five selected emerging stock markets (Brazil, China, Mexico, Russia and Turkey) and developed markets of the US, UK and Germany. The bounds testing approach to cointegration and error-correction modeling are used on monthly data from January 2001 to December 2014 to determine the short-run and long-run relationship between emerging stock market returns and the returns of the developed stock markets. The results show evidence of the existence of short-run integration among stock markets in emerging countries and the developed markets. However, the long-run coefficients for stock market returns in all emerging countries show a significant relationship only with Germany stock market return. The empirical findings in this study have important implications for academicians, international investors, and policymakers in emerging markets.     

Firm fundamentals and stock prices in emerging Asian stock markets: some panel data evidence

The purpose of this paper is to investigate the direct link between firm fundamentals and stock prices in a set of emerging Asian stock markets using firm-level panel data. In doing so, we explore the relationship between firm-specific variations in stock returns and firm fundamentals in the context of a simple present value framework. We find that alternative proxies of variation in firm fundamentals—albeit at differing degrees—explain a significant part of firm-specific return variation in a majority of emerging markets in Asia. Findings are robust to the influence of other factors known to affect stock return volatility (e.g. firm size, stock turnover, and leverage). Overall results suggest that stock prices in a majority of the Asian emerging markets contain a significant amount of firm-specific fundamental information and are, therefore, not as murky as commonly thought.     

Term structure of return correlations and international diversification: evidence from European stock markets

The paper examines the term structure of correlations of weekly returns for the stock market in the US, Japan and nine European countries between 1988 and 1994. Stock indices are decomposed into permanent and temporary components using a canonical correlation analysis and then short- and long-horizon return correlations are calculated from these two price components. The empirical results reveal that the relationships of return correlations among these stock markets are not stable across return horizons. While correlations, in general, tend to increase with return horizons, there are several cases showing that correlations decline when investment horizons increase.     

Developed markets’ business cycle dynamics and time-variation in emerging markets’ asset returns

This paper empirically studies the predictability of emerging markets’ stock returns by business cycle variables and the role of developed markets’ business cycle dynamics in this respect. The evidence shows that the link between business cycles and future stock market returns among emerging markets is considerably weaker than among developed markets. By contrast, I find strong evidence of stock return predictability by the respective country’s dividend-price ratio. This latter finding could reflect that variation in dividend-price ratios potentially reflects both the temporary impact of “hot money” inflows on emerging markets’ asset prices and rational expectations of future returns.     

Have European Stocks become More Volatile? An Empirical Investigation of Idiosyncratic and Market Risk in the Euro Area

We examine the dynamics of idiosyncratic risk, market risk and return correlations in European equity markets using weekly observations from 3515 stocks listed in the 12 euro area stock markets over the period 1974–2004. Similarly to Campbell et al. (2001) , we find a rise in idiosyncratic volatility, implying that it now takes more stocks to diversify away idiosyncratic risk. Contrary to the US, however, market risk is trended upwards in Europe and correlations are not trended downwards. Both the volatility and correlation measures are pro‐cyclical, and they rise during times of low market returns. Market and average idiosyncratic volatility jointly predict market wide returns, and the latter impact upon both market and idiosyncratic volatility. This has asset pricing and risk management implications.     

Causal and Dynamic Relationships among Stock Returns,Return Volatility and Trading Volume: Evidence from Emerging markets in South-East Asia

This paper examines the causal and dynamic relationships among stock returns, return volatility and trading volume for five emerging markets in South-East Asia—Indonesia, Malaysia, Philippines, Singapore and Thailand. We find strong evidence of asymmetry in the relationship between the stock returns and trading volume; returns are important in predicting their future dynamics as well as those of the trading volume, but trading volume has a very limited impact on the future dynamics of stock returns. However, the trading volume of some markets seems to contain information that is useful in predicting future dynamics of return volatility.     

Local Return Factors and Turnover in Emerging Stock Markets

The factors that drive cross-sectional differences in expected stock returns in emerging equity markets are qualitatively similar to those that have been documented for developed markets. Emerging market stocks exhibit momentum, small stocks outperform large stocks, and value stocks outperform growth stocks. There is no evidence that high beta stocks outperform low beta stocks. A Bayesian analysis of the return premiums shows that the combined evidence of developed and emerging markets strongly favors the hypothesis that similar return factors are present in markets around the world. Finally, there exists a strong cross-sectional correlation between the return factors and share turnover.     

Determinants of equity return correlations: a case study of the Amman Stock Exchange

This paper seeks to explain time-varying correlations among equity returns. The literature has shown that fundamental and economic factors can explain stock returns or the volatility of markets. Here, panel data analysis is employed to examine whether these factors can also explain the comovement of stock returns. Time-varying correlations among sectoral indexes are estimated using a restricted multivariate threshold GARCH model with dynamic conditional correlation controlling for the asymmetric effects of news and the influence of financial crises. The empirical results from this panel data analysis show that equity return correlations can be explained not only by macroeconomic variables but also by fundamentals within an industry.     

Characteristics of permanent and transitory returns in oil-sensitive emerging stock markets: The case of GCC countries

The estimates suggest that for both return components there exists a statistically significant high volatility regime for all the Gulf Cooperation Council (GCC) stock markets and the oil market. On the other hand, the results for the low volatility state of both components are mixed. The individual GCC markets vary in terms of sensitivity to volatility and its duration; with Saudi Arabia and Oman having the highest overall return volatility. All the GCC markets are much less volatile than that of the more open, crisis-ridden, oil-exporting Mexico. All GCC returns move in the same direction, whether in terms of total return, fundamentals or fads under both volatility regimes. The correlations between themselves and with Mexico, the oil price and the Morgan Stanley Capital International Index (MSCI) returns are weak compared to the correlations among stock returns of Germany, Japan UK and the US [Bhar, R., Hamori, S., 2004. Empirical characteristics of the permanent and transitory components of stock returns: analysis in a Markov-switching heteroscedasticity framework. Economics Letters 82, 157–165]. Mexico has considerably higher correlation with both MSCI and the oil price than all the GCC countries.     

Empirical Analysis of Stock Returns and Volatility: Evidence from Seven Asian Stock Markets Based on TAR-GARCH Model

This paper investigates the time-series behavior of stock returns for seven Asian stock markets. In most cases, higher average returns appear to be associated with a higher level of volatility. Testing the relationship between stock returns and unexpected volatility, the evidence shows that four out of seven Asian stock markets have significant results. Further analyzing the relationship between stock returns and time-varying volatility by using Threshold Autoregressive GARCH(1,1)-in-mean specification indicates that the null hypothesis of no asymmetric effect on the conditional volatility is rejected for the daily data. However, the null cannot be rejected for the monthly data.     

Expected stock returns,common idiosyncratic volatility and average idiosyncratic correlation

Motivated by Herskovic et al. (2016), we examine the role of the average idiosyncratic correlation (ICOR) in two types of markets: an emerging market and a developed market. Examining daily stock data from the Chinese stock market for the period 1995 to 2020 and from the US for the period 1926 to 2019, we adopt high-dimensional principal component analysis (PCA) and thresholding methods to re-estimate ICOR. We find that ICOR plays an important role in explaining the expected stock returns, as the common idiosyncratic volatility (CIV) does in Herskovic et al. (2016). ICOR has been neglected in the literature due to large estimation error in the idiosyncratic covariance matrix and our analysis provides evidence that ICOR is nonnegligible in both markets when we control for several common market factors. We show that the average idiosyncratic covariance, which is the numerator of ICOR, exhibits the same pattern as CIV. Furthermore, our regression analyses of expected stock returns in response to ICOR change in both markets show that, in contrast to the negative result for CIV, the stocks’ high risk exposure to ICOR change comes with a higher risk premium, perhaps because of the synchronized but disproportionate changes in the monthly idiosyncratic covariance and idiosyncratic volatility.     

Corrections for Trading Frictions in Multivariate Returns

When observed stock returns are obtained from trades subject to friction, it is known that an individual stock's beta and covariance are measured with error. Univariate models of additive error adjustment are available and are often applied simultaneously to more than one stock. Unfortunately, these multivariate adjustments produce non-positive definite covariance and correlation matrices, unless the return sample sizes are very large. To prevent this, restrictions on the adjustment matrix are developed and a correction is proposed, which dominates the uncorrected estimator. The estimators are illustrated with asset opportunity set estimates where daily returns have trading frictions.     

The Seasonal Stability of the Factor Structure of Stock Returns

This paper investigates the month-by-month stability of (a) daily returns and correlation coefficients of stock returns, (b) correlation and covariance matrices, (c) number of return-generating factors, and (d) the APT pricing relationship. The results show that there is a January effect and a small-firm effect in stock returns. Correlation matrices are more stable than covariance matrices, but both types of matrices are not stable across months and across the sample groups. The number of return-generating factors is rather stable most of the time and for most of the sample groups, but there is some significant instability that is related to the average correlation coefficients among stocks. The APT pricing relationship does not seem to be supported by the two-stage process using the maximum-likelihood factor analysis.     

Idiosyncratic volatility and cross‐sectional stock returns in Southeast Asian stock markets

We examine the role of idiosyncratic risk in five ASEAN markets of Malaysia, Singapore, Thailand, Indonesia, and the Philippines. Our research was motivated by the findings of Ang et al. (2006, 2009) of a ‘puzzling’ negative relation between idiosyncratic volatility and 1‐month ahead stock returns in developed markets and the suggestion of the ubiquity of these results in other markets. In contrast, we find no evidence of an idiosyncratic volatility puzzle in these Asian stock markets; instead, we document a positive relationship between idiosyncratic volatility and returns in Malaysia, Singapore, Thailand, and Indonesia and no relationship in the Philippines. The idiosyncratic volatility trading strategy could result in significant trading profits in Malaysia, Singapore, Thailand, and to some extent in Indonesia. Our study underscores the fact that generalizing empirical results obtained in developed stock markets to new and emerging markets could potentially be misleading.     

Correlation and return dispersion dynamics in Chinese markets

This paper studies the relation between firm-level return dispersions and correlations among Chinese stocks during periods of unusually large upward and downward swings. We analyze individual stock returns across 18 sectors and test if return dispersions and stock correlations show asymmetric patterns for extreme up and down markets. Evidence from studies on U.S. stocks suggests that equity return correlations tend to be much greater on the downside than on the upside and that the degree of comovement gets even stronger during extreme market states. However, in the case of Chinese stock market, we find that higher downside correlations apply to only stocks within the Financial sector. With the exception of Financial stocks, we find that stock correlations are significantly higher during up markets, rather than down markets. Regarding firm-level return dispersions, our findings are consistent with rational asset pricing model predictions. We find that equity return dispersions are significantly higher during periods of large price changes.     

A simple indicator of systemic risk

We examine the relevance and effectiveness of stock return correlations among financial institutions as an indicator of systemic risk. By analyzing the trends and fluctuations of daily stock return correlations and default correlations among the 22 largest bank holding companies and investment banks from 1988 to 2008, we find that daily stock return correlation is a simple, robust, forward-looking, and timely systemic risk indicator. There is an increasing trend in stock return correlation among banks, whereas there is no obvious correlation trend among non-banks. We also disaggregate the stock returns into systematic and idiosyncratic components and find that the correlation increases are largely driven by the increases in correlations between banks’ idiosyncratic risks, which give rise to increasing systemic risk. Correlation spikes tend to predict or coincide with significant economic or market events, especially during the 2007–2008 financial crisis. Furthermore, we show that stock return correlations offer a perspective on the level of systemic risk in the financial sector that is not already captured by default correlations. Stock return correlations are not subject to data limitations or model specification errors that other potential systemic risk measures may face. Therefore, we recommend that regulators and businesses monitor daily stock return correlations among those large and highly leveraged financial institutions to track the level of systemic risk.     

CO-MOVEMENTS IN INTERNATIONAL EQUITY MARKETS

We examine the co-movements of equity returns in four major international markets by characterizing the time-varying cross-country covariances and correlations. Using a generalized positive definite multivariate GARCH model, we find that the Japanese and U.S. stock markets have significant transitory covariance, but zero permanent covariance. The other pairs of markets examined display significant permanent and transitory covariance. We also find that, while conditional correlations between returns are generally small, they change considerably over time. An event analysis suggests that basing diversification strategies on these conditional correlations is potentially beneficial.     

Empirical analysis of dynamic correlations of stock returns: evidence from Chinese A-share and B-share markets

This paper examines the dynamic correlation structure between A-share and B-share stock returns based on three different measures of correlation coefficients. Testing the models by employing daily stock-return data for the period from 1996 through 2003, we reach the following empirical conclusions. First, the correlation coefficients between A-share and B-share stock returns are time varying. Second, the dynamic path of the correlation coefficients indicates that the correlation coefficients are significantly correlated with the trend factor. Third, there is a substantial spillover effect from the Asian crisis to Chinese stock-return dynamic correlations. Fourth, the evidence suggests that the time-varying correlations are significantly associated with excessive trading activity as measured by excessive trading volumes and high–low price differentials. Fifth, the correlation between A-share and B-share markets has increased since the relaxation of the restriction on B-share market investments by domestic investors.     

International Equity Index and Currency Futures: Commodity Currencies or Emerging Versus Developed Markets?

Equity index futures in both emerging and developing markets that are net commodity exporters are strongly linked to their respective currency futures markets. Unconditional correlations among equity and currency futures are the highest for these net basic materials producers in both emerging and developed markets. Granger causality tests also indicate that stock market returns are more strongly related to currency futures returns for commodity-exporting countries. Additionally, conditional correlations among currency and equity futures returns are the strongest for commodity-producing countries in both emerging and developed economies. Volatility spillover analysis provides consistent results. The overall results indicate that the status of a country as a net importer or exporter of raw materials is more important to the relationship between equity and currency futures than whether it is an emerging or developed economy.