Gone fishin’: Seasonality in trading activity and asset prices

We use seasonality in stock trading activity associated with summer vacation as a source of exogenous variation to study the relationship between trading volume and expected return. Using data from 51 stock markets, we first confirm a widely held belief that stock turnover is significantly lower during the summer because market participants are on vacation. Interestingly, we find that mean stock return is also lower during the summer for countries with significant declines in trading activity. This relationship is not due to time-varying volatility. Moreover, both large and small investors trade less and the price of trading (bid-ask spread) is higher during the summer. These findings suggest that heterogeneous agent models are essential for a complete understanding of asset prices.     

Multimarket Trading and Liquidity: Theory and Evidence

We develop a new model of multimarket trading to explain the differences in the foreign share of trading volume of internationally cross‐listed stocks. The model predicts that the trading volume of a cross‐listed stock is proportionally higher on the exchange in which the cross‐listed asset returns have greater correlation with returns of other assets traded on that market. We find robust empirical support for this prediction using stock return and volume data on 251 non‐U.S. stocks cross‐listed on major U.S. exchanges.     

Regime shift,speculation, and stock price

We investigate the impacts of speculation on stock price and return volatility in a framework with regime shifting. We find that greater difference in beliefs about the probability of bad state leads to higher stock prices. The intuition is that in periods of higher dispersion of beliefs, the investors perceive greater speculative opportunities, leading to increased demands and valuations of the stock. When investors agree with each other on the state of dividend growth, they have a stronger incentive to invest in the riskless bond, when becoming more pessimistic about the dividend growth. As a result, the demand and the valuations of stock decrease. Moreover, higher level of heterogeneity in beliefs gives rise to higher volatility of the stock returns, even in the absence of dividend shocks. Furthermore, with homogeneous beliefs, return volatility with respect to investors’ beliefs follows an inverted-U shape.     

Market-wide impact of the disposition effect: evidence from IPO trading volume

I study empirically the market-wide importance of investors’ reluctance to realize losses by investigating IPO trading volume. In IPOs all initial investors have a common purchase price, and the disposition effect should thus be at its strongest. Turnover is significantly lower for negative initial return IPOs when the stock trades below the offer price, and increases significantly on the day the price surpasses the offer price for the first time. The increase in volume lasts for two weeks. On a daily level, attaining new maximum and minimum stock prices also produces strong increase in volume. These results suggest that reference price effects play a role in aggregate stock market activity.     

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 Price Is (Almost) Right

Most previous research tests market efficiency using average abnormal trading profits on dynamic trading strategies, and typically rejects the joint hypothesis of market efficiency and an asset pricing model. In contrast, we adopt the perspective of a buy‐and‐hold investor and examine stock price levels. For such an investor, the price level is more relevant than the short‐horizon expected return, and betas of cash flow fundamentals are more important than high‐frequency stock return betas. Our cross‐sectional tests suggest that there exist specifications in which differences in relative price levels of individual stocks can be largely explained by their fundamental betas.     

The High-Volume Return Premium

The idea that extreme trading activity contains information about the future evolution of stock prices is investigated. We find that stocks experiencing unusually high (low) trading volume over a day or a week tend to appreciate (depreciate) over the course of the following month. We argue that this high-volume return premium is consistent with the idea that shocks in the trading activity of a stock affect its visibility, and in turn the subsequent demand and price for that stock. Return autocorrelations, firm announcements, market risk, and liquidity do not seem to explain our results.     

The Impact of Information Release on Stock Price Volatility and Trading Volume: The Rights Offering Case

This paper examines whether information released via rights offering announcements induces changes in price volatility and trading volume of underlying stock. The results of this paper provide support for the release of new information via offering announcements and evidence of its effects on price volatility and volume of underlying stock. Specifically, utilization of the announced information by investors is evidenced by greater trading volume following the announcement date than during the pre-announcement period. We interpret this result to mean that informedness dominates consensus. However, stock price volatility decreased from the pre-announcement period to the post-expiration period of rights offerings.     

The Media and the Diffusion of Information in Financial Markets: Evidence from Newspaper Strikes

The media are increasingly recognized as key players in financial markets. I investigate their causal impact on trading and price formation by examining national newspaper strikes in several countries. Trading volume falls 12% on strike days. The dispersion of stock returns and their intraday volatility are reduced by 7%, while aggregate returns are unaffected. Moreover, analysis of return predictability indicates that newspapers propagate news from the previous day. These findings demonstrate that the media contribute to the efficiency of the stock market by improving the dissemination of information among investors and its incorporation into stock prices.     

Momentum and Reversals in Equity-Index Returns During Periods of Abnormal Turnover and Return Dispersion

We document new patterns in the dynamics between stock returns and trading volume. Specifically, we find substantial momentum (reversals) in consecutive weekly returns when the latter week has unexpectedly high (low) turnover. This pattern is evident in equity indices, index futures, and individual stocks. Similarly, we also find that the autocorrelation in equity‐index returns is increasing with the unexpected dispersion across the latter week's firm‐level returns. Weeks with extreme turnover and dispersion shocks (both high and low) tend to have more macroeconomic news releases. Our findings bear on understanding price formation and the economic interpretation of turnover and dispersion shocks.     

MACROECONOMIC NEWS,STOCK TURNOVER,AND VOLATILITY CLUSTERING IN DAILY STOCK RETURNS

We study volatility clustering in daily stock returns at both the index and firm levels from 1985 to 2000. We find that the relation between today's index return shock and the next period's volatility decreases when important macroeconomic news is released today and increases with the shock in today's stock market turnover. Collectively, our results suggest that volatility clustering tends to be stronger when there is more uncertainty and disperse beliefs about the market's information signal. Our findings also contribute to a better understanding of the joint dynamics of stock returns and trading volume.     

Asymmetric Volume‐Return Relation and Concentrated Trading in LIFFE Futures

This study demonstrates that intraday volume and return on LIFFE interest rate and currency futures exhibit an asymmetric volume‐return relationship characterised by significantly larger volume associated with negative returns than with non‐negative returns. This finding is unlike the stylised asymmetric relation often observed in equity markets, where the volume on price rise is larger than the volume on price decline. The asymmetric relationship in LIFFE futures is also found to be dynamic as the direction of asymmetry can reverse during the day. It has been argued in the past that a costly short sale restriction that requires a higher transaction cost on a short position than on a long position is responsible for the asymmetric effect in equity markets. Since such a restriction is absent in futures markets, they should not exhibit any asymmetric volume behaviour. Based on the results of this research, the costly short sale hypothesis is rejected. An alternative explanation of the asymmetric relation observed in futures is presented based on recent information models that take into consideration asymmetrically‐informed traders, their dispersion of beliefs, quality and quantity of the information signal, and how the traders process it. The paper also confirms a strong U‐shape trading pattern in 15‐minute volume, but no such pattern is identified in intraday returns.     

Competition among Trading Venues: Information and Trading on Electronic Communications Networks

This paper explores the competition between two trading venues, Electronic Communication Networks (ECNs) and Nasdaq market makers. ECNs offer the advantages of anonymity and speed of execution, which attract informed traders. Thus, trades are more likely to occur on ECNs when information asymmetry is greater and when trading volume and stock‐return volatility are high. ECN trades have greater permanent price impacts and more private information is revealed through ECN trades than though market‐maker trades. However, ECN trades have higher ex ante trading costs because market makers can preference or internalize the less informed trades and offer them better executions.     

Stock returns,trading volume,and volatility: The case of African stock markets

The presence of the African Stock Markets (ASMs) in the global frontier markets indices confirms their global portfolio diversification role. This study investigates the asymmetric and intertemporal causality among the stock returns, trading volume, and volatility of eight ASMs. Results based on the linear model reveal that return generally Granger cause trading volume. However, evidence from the quantile regression shows that lagged trading volume has a negative causal effect on returns at low quantiles and positive causal effects at high quantiles. This evidence is consistent with volume-return equilibrium models, disposition and overconfidence models, and information asymmetry models. The positive causal effects of volatility on volume support the dispersion of beliefs model. In contrast, intertemporal evidence of contemporaneous and lagged causal relationships from trading volume to volatility supports the mixture of distribution hypothesis, sequential information acquisition hypothesis, and dynamic efficient market hypothesis. Volume-return and return-volume causality dynamics are quantile-specific and therefore driven by market conditions. However, the volume-volatility causality is dependent on volatility regimes. The linear model results confirm how model misspecification can distort and even reverse empirical evidence relative to nonlinear models.     

Stock market volatility and equity returns: Evidence from a two-state Markov-switching model with regressors

This paper proposes a two-state Markov-switching model for stock market returns in which the state-dependent expected returns, their variance and associated regime-switching dynamics are allowed to respond to market information. More specifically, we apply this model to examine the explanatory and predictive power of price range and trading volume for return volatility. Our findings indicate that a negative relation between equity market returns and volatility prevails even after having controlled for the time-varying determinants of conditional volatility within each regime. We also find an asymmetry in the effect of price range on intra- and inter-regime return volatility. While price range has a stronger effect in the high volatility state, it appears to significantly affect only the transition probabilities when the stock market is in the low volatility state but not in the high volatility state. Finally, we provide evidence consistent with the ‘rebound’ model of asset returns proposed by Samuelson (1991), suggesting that long-horizon investors are expected to invest more in risky assets than short-horizon investors.     

The bivariate GARCH approach to investigating the relation between stock returns,trading volume,and return volatility

We use a bivariate GJR-GARCH model to investigate simultaneously the contemporaneous and causal relations between trading volume and stock returns and the causal relation between trading volume and return volatility in a one-step estimation procedure, which leads to the more efficient estimates and is more consistent with finance theory. We apply our approach to ten Asian stock markets: Hong Kong, Japan, Korea, Singapore, Taiwan, China, Indonesia, Malaysia, the Philippines, and Thailand. Our major findings are as follows. First, the contemporaneous relation between stock returns and trading volume and the causal relation from stock returns and trading volume are significant and robust across all sample stock markets. Second, there is a positive bi-directional causality between stock returns and trading volume in Taiwan and China and that between trading volume and return volatility in Japan, Korea, Singapore, and Taiwan. Third, there exists a positive contemporaneous relation between trading volume and return volatility in Hong Kong, Korea, Singapore, China, Indonesia, and Thailand, but a negative one in Japan and Taiwan. Fourth, we find a significant asymmetric effect on return and volume volatilities in all sample countries and in Korea and Thailand, respectively.     

WHEN‐ISSUED SHARES,SMALL TRADES,AND THE VARIANCE OF RETURNS AROUND STOCK SPLITS

The increases in volatility after stock splits have long puzzled researchers. The usual suspects of discreteness and bid‐ask spread do not provide a complete explanation. We provide new clues to solve this mystery by examining the trading of when‐issued shares that are available before the split. When‐issued trading permits noise traders to compete with a more homogenous set of traders, decreasing the volatility of the stock before the split. Following the split, these noise traders reunite in one market and volatility increases. Thus, the higher volatility after the ex date of a stock split is a function of the introduction of when‐issued trading, the new lower price level after the split date, and the increased activity of small‐volume traders around a stock split.     

Effects of Passive Intensity on Aggregate Price Dynamics

We find that passive intensity (PI), measured by the passive‐linked share of total stock market trading volume, is strongly related to the overall pattern of stock price movements. A one‐standard‐deviation increase in PI is associated with an 8% higher price synchronicity. We further investigate the channels through which this relation is established by separately analyzing its impact on aggregate systematic and idiosyncratic volatility of stock returns. PI has a positive effect on systematic volatility and a negative impact on firm‐specific volatility. Consistent with the effect of passive trading on price dynamics, we find evidence that PI is negatively associated with mutual funds alpha dissimilarity. After controlling for market and idiosyncratic volatility, a one‐standard‐deviation increase in PI corresponds to a 0.20% decrease in fund dissimilarity. Our findings are robust after controlling for various macro and corporate factors known to affect systematic or firm‐specific volatility.     

Speculative dynamics and price behavior in the Shanghai Stock Exchange

This article examines the extent to which the trading behavior of heterogeneous investors manifests in stock price changes of asset portfolios which constitute the Shanghai Stock Exchange. There are three major findings that materialize. Firstly, reliable statistical evidence of a negative relation between the conditional first and second moments of the return distributions of stock prices lends support to the volatility feedback effect. Secondly, ‘feedback’, or momentum-type investors, are not present in this market as is often detected from the daily price changes of other industrialized markets. Finally, trade volume as a proxy for ‘information-driven’ trading suggests that such investors play a statistically significant role in stock price movements. Parameter estimates from this latter group of investors imply that a rise in stock prices from a high volume trading day is more likely than a rise resulting from a low volume trading day.