Dynamic analysis of stock return volatility in an integrated international capital market

This paper examines the dynamic behavior of the stock return volatility for Canada, Japan, Germany, and the United Kingdom. The evidence indicates that international stock return volatility is mainly influenced by the U.S. stock return volatility and the exchange rate volatility, supporting the international capital market integration hypothesis. There seems to be some correlation between stock return volatility and macroeconomic volatility, but the effect is relatively weaker. In addition to the economic fundamentals, the noise component is found to be time varying, confirming the AR(MA)CH specifications in the stock return models.     

Stock return volatility,operating performance and stock returns: International evidence on drivers of the ‘low volatility’ anomaly

This study highlights the link between stock return volatility, operating performance, and stock returns. Prior studies suggest that there is a ‘low volatility’ anomaly, where firms with a low stock return volatility out-perform firms with a high stock return volatility. This paper confirms that low volatility stocks earn higher returns than high volatility stocks in emerging markets and developed markets outside of North America. We also show that low volatility stocks have higher operating returns and this might explain why low volatility stocks earn higher stock returns. These results provide a partial explanation for the ‘low volatility effect’ that is independent from the existence of market anomalies or per se inefficiencies that might otherwise drive a low volatility effect. We emphasize the importance of controlling for stock return volatility when analyzing operating performance and stock performance.     

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     

An Empirical Examination of the Return Volatility-Volume Relation in Related Markets: The Case of Stock and Options

This paper empirically examines the impact of option trading on the relation between daily stock return volatility and stock trading volume. For a sample of firms for which options were newly listed on the CBOE from 1982 to 1985, the empirical evidence indicates that there is a structural shift in the relation after option trading is introduced. Also, the findings show that daily stock return volatility is significantly and positively correlated with contemporaneous option volume, but not one-day lagged option volume. These results suggest that contemporaneous option volume may be an important variable in modelling daily stock return volatility and heteroskedasticity.     

Trading activity and bid–ask spreads of individual equity options

We empirically examine the impact of trading activities on the liquidity of individual equity options measured by the proportional bid–ask spread. There are three main findings. First, the option return volatility, defined as the option price elasticity times the stock return volatility, has a much higher power in explaining the spread variations than the commonly considered liquidity determinants such as the stock return volatility and option trading volume. Second, after controlling for all the liquidity determinants, we find a maturity-substitution effect due to expiration cycles. When medium-term options (60–90 days maturity) are not available, traders use short-term options as substitutes whose higher volume leads to a smaller bid–ask spread or better liquidity. Third, we also find a moneyness-substitution effect induced by the stock return volatility. When the stock return volatility goes up, trading shifts from in-the-money options to out-of-the-money options, causing the latter’s spread to narrow.     

The Volatility and Price Sensitivities of Managerial Stock Option Portfolios and Corporate Hedging

We use estimates of the Black–Scholes sensitivity of managers' stock option portfolios to stock return volatility and the sensitivity of managers' stock and stock option portfolios to stock price to test the relationship between managers' risk preferences and hedging activities. We find that as the sensitivity of managers' stock and stock option portfolios to stock price increases, firms tend to hedge more. However, as the sensitivity of managers' stock option portfolios to stock return volatility increases, firms tend to hedge less.     

Does foreign institutional ownership increase return volatility? Evidence from China

This paper investigates the impact of foreign institutional ownership on firm-level stock return volatility in China, based on our study of a sample of 1458 firms between 1998 and 2008. The empirical results show that share ownership by foreign institutions (both financial and non-financial) increases firm-level stock return volatility, even after controlling for a complete ownership structure, firm size, turnover, and leverage, and correcting for potential endogeneity problems. However, the results also show that foreign individual shareholdings reduce volatility. Furthermore, we document a positive relationship between domestic shareholdings (individual, institutional, and governmental) and firm-level stock return volatility. Empirical results with interaction terms show that foreign institutional ownership increases firm-level return volatility by strengthening the positive impact of liquidity on volatility. The volatility reduction effect of foreign individual ownership is attenuated by government ownership suggests a poor governance environment as a result of the involvement of the Chinese government.     

The Determinants of Conditional Autocorrelation in Stock Returns

We investigate whether return volatility, trading volume, return asymmetry, business cycles, and day‐of‐the‐week are potential determinants of conditional autocorrelation in stock returns. Our primary focus is on the role of feedback trading and the interplay of return volatility. We present empirical evidence using conditional autocorrelation estimates generated from multivariate generalized autoregressive conditional heteroskedasticity (M‐GARCH) models for individual U.S. stock and index data. In addition to return volatility, we find that trading volume and market returns are important in explaining the time‐varying patterns of return autocorrelation.     

The effect of exchange rate variability on US shareholder wealth

We examine the relationship between financial crisis exchange rate variability and equity return volatility for US multinationals. Empirical analysis of the major financial crises of the last decades reveals that stock return variability increases significantly in the aftermath of a crisis, even relative to the increase in stock return volatility for other firms belonging to the same industry and market capitalization class. In conjunction with this increase in total volatility, there is also an increase in stock market risk (β) for multinational firms. Moreover, trade and service oriented industries appear to be particularly sensitive to these changing exchange rate conditions.     

中国股市开、收盘波动性的比较研究

利用EGARCH模型,对2000年1月至2007年4月间沪深两市具有代表性的股票及指数的开收盘收益率的波动性进行实证分析,结果表明收益率序列有明显的ARCH效应,其波动性具有显著的非对称性的冲击的持续性;在样本期内,上交所的个股和指数未能观察到开盘波动性高于收盘波动性的现象,而深交所个股在2006年7月实施收盘集合竞价机制之后比较明显地观察到开盘波动性高于收盘波动性的现象。     

Does Trading Volume Contain Information to Predict Stock Returns? Evidence from China's Stock Markets

This paper examines empirical contemporaneous and causal relationships between trading volume, stock returns and return volatility in China's four stock exchanges and across these markets. We find that trading volume does not Granger-cause stock market returns on each of the markets. As for the cross-market causal relationship in China's stock markets, there is evidence of a feedback relationship in returns between Shanghai A and Shenzhen B stocks, and between Shanghai B and Shenzhen B stocks. Shanghai B return helps predict the return of Shenzhen A stocks. Shanghai A volume Granger-causes return of Shenzhen B. Shenzhen B volume helps predict the return of Shanghai B stocks. This paper also investigates the causal relationship among these three variables between China's stock markets and the US stock market and between China and Hong Kong. We find that US return helps predict returns of Shanghai A and Shanghai B stocks. US and Hong Kong volumes do not Granger-cause either return or volatility in China's stock markets. In short, information contained in returns, volatility, and volume from financial markets in the US and Hong Kong has very weak predictive power for Chinese financial market variables.     

ON ESTIMATING STOCK MARKET VOLATILITY: AN EXPLORATORY APPROACH

Traditional methods of estimating market volatility use daily return observations from a stock index to calculate monthly variance. We break with tradition and estimate stock market volatility using the daily, cross-sectional standard deviation of returns for all firms trading on the New York Stock Exchange and the American Stock Exchange. We find a significantly positive relation between risk and return. Market volatility is estimated to be about half the volatility level previously reported. The intraday, cross-sectional market volatility measure provides findings consistent with risk-return theory.     

Stock price synchronicity and liquidity

We argue and provide evidence that stock price synchronicity affects stock liquidity. Under the relative synchronicity hypothesis, higher return co-movement (i.e., higher systematic volatility relative to total volatility) improves liquidity. Under the absolute synchronicity hypothesis, stocks with higher systematic volatility or beta are more liquid. Our results support both hypotheses. We find all three illiquidity measures (effective proportional bid-ask spread, price impact measure, and Amihud's illiquidity measure) are negatively related to stock return co-movement and systematic volatility. Our analysis also shows that larger industry-wide component in returns improves liquidity. We find that improvement in liquidity following additions to the S&P 500 Index is related to the stock's increase in return co-movement.     

Why Does Stock Market Volatility Change Over Time?

This paper analyzes the relation of stock volatility with real and nominal macroeconomic volatility, economic activity, financial leverage, and stock trading activity using monthly data from 1857 to 1987. An important fact, previously noted by Officer (1973) , is that stock return variability was unusually high during the 1929–1939 Great Depression. While aggregate leverage is significantly correlated with volatility, it explains a relatively small part of the movements in stock volatility. The amplitude of the fluctuations in aggregate stock volatility is difficult to explain using simple models of stock valuation, especially during the Great Depression.     

Information content and other characteristics of the daily cross-sectional dispersion in stock returns

We study the cross-sectional dispersion in daily stock returns, or daily return dispersion (RD). Our primary empirical contribution is to demonstrate that RD contains reliable incremental information about the future traditional volatility of both firm-level and portfolio-level returns. The relation between RD and future stock volatility is pervasive across time and across different industry portfolios, size-based portfolios, and beta-based portfolios. Further, our results suggest that RD contains more incremental information about the future volatility of firm-level stock returns than do lagged market-level return shocks. To further characterize RD and assist in interpretation, we also document how dispersion varies with stock turnover and macroeconomic news.     

Index Futures Trading and Stock Return Volatility: Evidence from the Introduction of Mid Cap 400 Index Futures

The MidCap 400 stock index is used to provide new evidence on the relation between stock index futures trading and stock return volatility. The study documents a significant decrease in return volatility and systematic risk, and a significant increase in trading volume for the MidCap 400 stocks after the introduction of the MidCap index. A control sample of medium-capitalization stocks, however, exhibits similar contemporaneous changes in these measures. The MidCap stocks and the control stocks also experience a significant decrease in volatility and an increase in volume after the introduction of MidCap 400 index futures. Thus, the study finds no difference in the behavior of the MidCap 400 stocks and the control stocks and no evidence of a relation between index futures trading and volatility in the stock market.     

Causality in volatility and volatility spillover effects between US, Japan and four equity markets in the South China Growth Triangular

In examining co-movement across international stock markets, previous researchers usually pre-determine the direction of causation and neglect the Chinese equity markets. In this study, we examine the spillover effects of volatility among the two developed markets and four emerging markets in the South China Growth Triangular using Chueng and Ng's causality-in-variance test. Several findings deserve mention: (1) the Japanese stock market affects the US stock market and there is a feedback relationship between the Hong Kong and US stock market. (2) Markets of the SCGT are contemporaneously correlated with the return volatility of the US market. (3) Econometric models constructed according to the results of variance-in-causality tests have greater explanatory power than the conventional GARCH(1,1) model. (4) Using the return volatility of foreign exchange as a proxy for informational arrival can explain excess kurtosis of a stock return series, especially for the less open emerging market. (5) Geographic proximity and economic ties do not necessarily lead to a strong relationship in volatility across markets.     

Asymmetry in spillover effects: Evidence for international stock index futures markets

The paper investigates the asymmetry in return and volatility spillovers across futures markets with non-overlapping stock exchange trading hours. The transmission of positive and negative return and volatility shocks is analysed for 104 channels of information conveyance identified by combining 9 developed and 11 emerging markets in markets pairs with non-overlapping trading hours. The asymmetric causality test is employed to daily stock index futures returns and volatilities for the period from 03 October 2010 to 03 October 2014. The paper sheds light on the relatively little explored concept of asymmetry in return and volatility spillovers across markets, providing novel evidence on stabilizing and destabilizing spillover effects.     

Time-varying risk The case of the American computer industry

A bivariate GARCH-in-mean model for individual stock returns and the market portfolio is designed to model volatility and to test the conditional Capital Asset Pricing Model versus the conditional Residual Risk Model. We find that a univariate model of volatility for individual stock returns is misspecified. A joint modelling of the market return and the individual stock return shows that a major force driving the conditional variances of individual stocks is the history contained in the market return variance. We find that a conditional residual risk model, where the variance of the individual stock return is used to explain expected returns, is preferred to a conditional CAPM. We propose a partial ordering of securities according to their market risk using first and second order dominance criteria.     

Dynamic spillovers across oil,gold and stock markets in the presence of major public health emergencies

Extreme events have a systemic impact on global financial markets, leading to significant cross-market spillovers in the oil, gold, and stock markets and raising widespread concerns about market linkages and risk contagion. In this paper, with a focus on both return and volatility, a frontier spillover network analysis is used to examine the strength and scale characteristics of spillovers in the oil, gold and stock markets under major public health emergency shocks. In addition, the paper adopts a marginal spillover and network analysis to evaluate linkage relationships, risk sources and transmission paths in the oil, gold, and stock markets during such events. The results show that the return and volatility spillover effects generated across the oil, gold, and stock markets are significant, with return spillovers being more stable and volatility spillovers being highly sensitive to emergencies. Meanwhile, the COVID-19 pandemic has displayed the strongest return and volatility spillovers. The high intensity of the shocks during the COVID-19 period has changed the usual characteristics of the market, with the gold market becoming the risk receiver and the oil market becoming risk sources.