Procyclical volatility in Chinese stock markets

Review of Quantitative Finance and Accounting - We investigate the macroeconomic determinants of stock market volatility in China using the two-component GARCH-MIDAS model of Engle et al....     

Intraday volatility in the stock index and stock index futures markets

We examine the intraday relationship between returns and returnsvolatility in the stock index and stock index futures markets.Our results indicate a strong intermarket dependence in thevolatility of the case and futures returns. Price innovationsthat originate in either the stock or futures markets can predictthe future volatility in the other market. We show that thisrelationship persists even during periods in which the dependencein the returns themselves appears to weaken. The findings arerobust to controlling for potential market frictions such asasynchronous trading in the stock index. Our results have implicationsfor understanding the pattern of information flows between thetwo markets.     

Transmission of movements in stock markets

The paper analyses the relationships between three stock markets: New York, Tokyo and Frankfurt. The non-simultaneity of the trading times in these three markets determines the results of cross-correlations and regressions with daily returns. To cope with this and other problems, an empirical model is proposed and estimated. This model allows the separation of the ability to influence and the sensitivity of the different markets, and New York is found to be the most influential market, with Tokyo the most sensitive.     

Empirical relationship between macroeconomic volatility and stock returns: Evidence from Latin American markets

Emerging market stock returns have been characterized as having higher volatility than returns in the more developed markets. But previous studies give little attention to the fundamentals driving the reported levels of volatility. This paper investigates whether dynamics in key macroeconomic indicators like exchange rates, interest rates, industrial production and money supply in four Latin American countries significantly explain market returns. The MSCI world index and the U.S. 3-month T-bill yield are also included to proxy the effects of global variables. Using a six-variable vector autoregressive (VAR) model, the study finds that the global factors are consistently significant in explaining returns in all the markets. The country variables are found to impact the markets at varying significance and magnitudes. These findings may have important implications for decision-making by investors and national policymakers.     

Modelling return and conditional volatility exposures in global stock markets

This article empirically investigates the exposure of country-level conditional stock return volatilities to conditional global stock return volatility. It provides evidence that conditional stock market return volatilities have a contemporaneous association with global return volatilities. While all the countries included in the study exhibited a significant and positive relationship to global volatility, emerging market volatility exposures were considerably higher than developed market exposures. JEL Classification G12     

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.     

Sudden changes in volatility in emerging markets: The case of Gulf Arab stock markets

This article examines sudden changes in volatility for five Gulf area Arab stock markets using the iterated cumulative sums of squares (ICSS) algorithm and analyzes their impacts on the estimated persistence of volatility. This algorithm identifies large shifts in volatility of the stock markets during the weekly period 1994 to 2001. In contrast to Aggarwal et al. [Aggarwal, R., Inclan, C., & Leal, R., 1999, Volatility in emerging markets. Journal of Financial and Quantitative Analysis 34, 33-55], this paper found that most of the Gulf Arab stock markets are more sensitive to major global events than to local and regional factors. The 1997 Asian crisis, the collapse of oil prices in 1998 after the crisis, the adoption of the price band mechanism by OPEC in 2000, and the September 11th attack have been found to have consistently affected the Gulf markets. Accounting for these large shifts in volatility in the GARCH(1,1) models significantly reduces the estimated persistence of the volatility in the Gulf stock markets.     

International nonlinear causality between stock markets

In this paper, we test for linear and nonlinear Granger causality between the French, German, Japanese, UK and US daily stock index returns from 1973 to 2003. We find a strong contemporaneous linear dependence between European countries and a directional linear dependence from the US towards the other markets. Besides, linear causality increases after 1987, a finding consistent with the expected effects of financial liberalization of the 1980s and the 1990s. Above all, we document the presence of bidirectional nonlinear causality between daily returns. To check for spurious nonlinear causality, we filter out heteroskedasticity using a FIGARCH model. The dramatic decrease in the number of significant nonlinear causality lags confirms that heteroskedasticity played a major part in the previous findings. We then check if a few structural breaks can explain the remaining nonlinear causality. We find that a large number of nonlinear relationships vanish when we control for structural breaks, whereas linear causality remains.     

Sudden changes in volatility: The case of five central European stock markets

This paper investigates sudden changes in volatility in the stock markets of new European Union (EU) members by utilizing the iterated cumulative sums of squares (ICSS) algorithm. Using weekly data over the sample period 1994–2006, the time period of sudden change in variance of returns and the length of this variance shift are detected. A sudden change in volatility seems to arise from the evolution of emerging stock markets, exchange rate policy changes and financial crises. Evidence also reveals that when sudden shifts are taken into account in the GARCH models, the persistence of volatility is reduced significantly in every series. It suggests that many previous studies may have overestimated the degree of volatility persistence existing in financial time series.     

Testing stock market contagion properties between large and small stock markets

Review of Quantitative Finance and Accounting - The heterogeneity of large and small stock market structures results in different degrees of cross-market contagion. The causality test reveals that...