Return Volatility,Trading Imbalance and the Information Content of Volume

In this paper, we examine the relationship between volume and return volatility using the transaction data. We introduce transaction and volume imbalance measures to capture the information content of trades. These two information measures are shown to have a strong explanatory power for return volatility and contain incremental information about the asset values over and above that conveyed by the size and frequency of trades. Also, return volatility is significantly correlated with the percentage of trading volume taking place at NYSE. This result suggests that NYSE trades are more informative and contribute more to price discovery. There is evidence that price discovery concentrates in more heavily traded stocks, particularly the Dow Jones Stocks. Finally, return volatility is found to be persistent at the intraday level. The persistence level is higher for less frequently traded stocks. Return volatility also exhibits temporal variations. In particular, return volatility is significantly higher in the opening half-hour for less frequently traded stocks. Thus, stocks with different frequencies of trades may follow different volatility processes.     

Variations in Trading Volume,Return Volatility,and Trading Costs: Evidence on Recent Price Formation Models

Patterns in stock market trading volume, trading costs, and return volatility are examined using New York Stock Exchange data from 1988. Intraday test results indicate that, for actively traded firms trading volume, adverse selection costs, and return volatility are higher in the first half-hour of the day. This evidence is inconsistent with the Admati and Pfleiderer (1988) model which predicts that trading costs are low when volume and return volatility are high. Interday test results show that, for actively traded firms, trading volume is low and adverse selection costs are high on Monday, which is consistent with the predictions of the Foster and Viswanathan (1990) model.     

Earnings Volatility, Cash Flow Volatility, and Informed Trading

I examine whether earnings that are smoother or more volatile than cash flows provide or garble information. Consistent with theories that predict more informed trading when public information is less informative, I find that bid-ask spreads and the probability of informed trading are higher both when earnings are smoother than cash flows and also when earnings are more volatile than cash flows. Additional tests suggest that managers' discretionary choices that lead to smoother or more volatile earnings than cash flows garble information, on average. However, I find that informed trading is attenuated in settings in which theory suggests that discretionary smoothing or volatizing of earnings is likely to be informative.     

期货市场的交易量与价格波动

本文检验了美国期货市场WTI原油、S＆P500指数和10年期国债品种的日内、日间价格波动与日内交易量、隔日交易量之间的关系,发现预期的日内和隔日交易量都有平抑期货市场价格波动的作用,非预期的隔日交易量与期货价格波动之间有正相关关系,非预期的目内交易量对价格波动的影响不显著。从信息对称性的角度分析,预期的交易量中含有更多信息,能抑制期货价格的偏离;非预期的交易量主要由信息反馈者提供,他们往往对期货价格的变动做出过度反应,从而加剧价格波动。     

How Persistent is Stock Return Volatility? An Answer with Markov Regime Switching Stochastic Volatility Models

Abstract:  We propose generalised stochastic volatility models with Markov regime changing state equations (SVMRS) to investigate the important properties of volatility in stock returns, specifically high persistence and smoothness. The model suggests that volatility is far less persistent and smooth than the conventional GARCH or stochastic volatility. Persistent short regimes are more likely to occur when volatility is low, while far less persistence is likely to be observed in high volatility regimes. Comparison with different classes of volatility supports the SVMRS as an appropriate proxy volatility measure. Our results indicate that volatility could be far more difficult to estimate and forecast than is generally believed.     

Trading Volume and Market Volatility: Developed versus Emerging Stock Markets

We investigate the relation between volatility and volume in 22 developed markets and 27 emerging markets. Compared to developed markets, emerging markets show a greater response to large information shocks and exhibit greater sensitivity to unexpected volume. We find a negative relation between expected volume and volatility in several emerging markets, which can be attributed to the relative inefficiency in those markets. Previous research reports that the persistence in volatility is not eliminated when lagged or contemporaneous trading volume is considered. Our findings show that, when volume is decomposed into expected and unexpected components, volatility persistence decreases.     

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.     

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.     

Volatility Information Trading in the Option Market

This paper investigates informed trading on stock volatility in the option market. We construct non-market maker net demand for volatility from the trading volume of individual equity options and find that this demand is informative about the future realized volatility of underlying stocks. We also find that the impact of volatility demand on option prices is positive. More importantly, the price impact increases by 40% as informational asymmetry about stock volatility intensifies in the days leading up to earnings announcements and diminishes to its normal level soon after the volatility uncertainty is resolved.     

Information of Unusual Trading Volume

This article investigates the information content of stock unusual trading volume from the aspect of firm fundamental information revealed by both earnings formal announcements and preannouncements. By using the stock market data of China from the second quarter of 2003 to the end of 2015, this article provides evidence that, in general, stocks that experience unusually low trading volume over the week prior to earnings announcements have more unfavorable earnings surprises. However, because of the feature of mandatory pre-disclosure policy in China, this article further finds that the relation between unusually low trading volume and unfavorable earnings surprises only exists in the stocks without earnings preannouncements, because fundamental information is incorporated in the stock prices timely around preannouncements date. In addition, unusually low trading volume signals negative fundamental changes revealed by preannouncements, and this effect is more pronounced among stocks with higher short-selling constraints, but unusually high trading volume is value-irrelevant.     

Information, Trading, and Volatility: Evidence from Weather-Sensitive Markets

We find that trading‐ versus nontrading‐period variance ratios in weather‐sensitive markets are lower than those in the equity market and higher than those in the currency market. The variance ratios are also substantially lower during periods of the year when prices are most sensitive to the weather. Moreover, the comovement of returns and volatilities for related commodities is stronger during the weather‐sensitive season, largely due to stronger comovement during nontrading periods. These results are consistent with a strong link between prices and public information flow and cannot be explained by pricing errors or changes in trading activity.     

Information, Trading Demand, and Futures Price Volatility

We examine the relation between futures price volatility and trading demand by type of trader in the Standard & Poor's (S&P) 500-stock index futures market. We find that volatility covaries negatively with signed speculative demand shocks but is positively related to signed hedging demand shocks. No significant relation between volatility and demand shocks for small traders is found. Our results suggest that changes in positions of large hedgers destabilize the market, whereas changes in positions of large speculators stabilize volatility. Consistent with models with asymmetrically informed traders, we find that large speculators are likely to possess superior forecasting ability, large hedgers behave like positive feedback traders, and small traders are liquidity traders.     

Volume,Volatility, and New York Stock Exchange Trading Halts

Trading halts increase, rather than reduce, both volume and volatility. Volume (volatility) in the first full trading day after a trading halt is 230 percent (50 to 115 percent) higher than following “pseudohalts”: nonhalt control periods matched on time of day, duration, and absolute net-of-market returns. These results are robust over different halt types and news categories. Higher posthalt volume is observed into the third day while higher posthalt volatility decays within hours. The extent of media coverage is a partial determinant of volume and volatility following both halts and pseudohalts, but a separate halt effect remains after controlling for the media effect.     

Trading Volume, Information Asymmetry, and Timing Information

This paper investigates trading volume before scheduled and unscheduled corporate announcements to explore how traders respond to private information. I show that cumulative trading volume decreases inversely to information asymmetry prior to scheduled announcements, while the opposite relation holds for volume after the announcement. In contrast, trading volume before unscheduled announcements increases dramatically and shows little relation to proxies for information asymmetry. I investigate the behavior of market makers and find that they act appropriately by increasing price sensitivity before all announcements, implying that they extract timing information from their order books.     

Cash Flow Volatility, Prices and Price Volatility: An Experimental Study

The value of an asset is equal to the present value of its expected future cash flows. It is affected by the magnitude, timing and riskiness, or volatility, of the cash flows. We hypothesize that if the expected values of two assets?? cash flows are equal, the value of the asset with more volatile cash flows will be lower. Furthermore, we examine the impact of the volatility of cash flows on the volatility of prices. We consider a simple experimental environment where subjects trade in an asset which provides dividends from a known probability distribution. The expected value of the dividends is identical in all experimental treatments. The treatments vary with respect to the volatility of dividends. We find that when dividends are more volatile, transaction prices are lower. We also find that the volatility of prices is lower in the treatment with highly volatile dividends. In addition, as expected, trading volume is lower when cash flows are less volatile.     

The Dynamic Relation Between Stock Returns, Trading Volume, and Volatility

We examine the dynamic relation between returns, volume, and volatility of stock indexes. The data come from nine national markets and cover the period from 1973 to 2000. The results show a positive correlation between trading volume and the absolute value of the stock price change. Granger causality tests demonstrate that for some countries, returns cause volume and volume causes returns. Our results indicate that trading volume contributes some information to the returns process. The results also show persistence in volatility even after we incorporate contemporaneous and lagged volume effects. The results are robust across the nine national markets.     

Stochastic Volatility With an Ornstein-Uhlenbeck Process: An Extension

In this paper, we reexamine and extend the stochastic volatilitymodel of Stein and Stein (S&S) (1991) where volatility followsa mean–reverting Ornstein–Uhlenbeck process. UsingFourier inversion techniques we are able to allow for correlationbetween instantaneous volatilities and the underlying stockreturns. A closed-form pricing solution for European optionsis derived and some numerical examples are given. In addition,we discuss the boundary behaviour of the instantaneous volatilityat v(t) = 0 and show that S&S do not work with an absolutevalue process of volatility. JEL Classification: G13     

The Effect of SEC-Ordered Suspensions on Returns, Volatility, and Trading Volume

This study evaluates the effect of SEC-ordered suspensions on securities' returns, volatility, and trading volume during 1963–1987. It is found that there is a permanent devaluation of these securities during the suspension. This result, however, is sensitive to the announced reason for the suspension. Both the variance and the trading volume are found to be substantially higher than normal in the presuspension period. This trend continues in the immediate postsuspension period. The variance and volume levels return to more normal levels only at a much later date. We conclude that trading suspensions are not associated with the immediate elimination of unusual market activity.     

Bid-ask Spreads, Trading Volume and Volatility: Intra-day Evidence from the London Stock Exchange

This paper examines intra-day variations in the bid-ask spread, volatility and volume for stocks traded on the London Stock Exchange. The data set used consists of quote and transactions data for a large sample of 835 stocks traded during the first quarter of 1991. The focus of the study is twofold; first, is to document a number of stylized facts regarding the intra-day behaviour of spread, trading volume, volatility etc. Second, the paper tests some predictions of two theoretical models of intra-day behaviour: the Admati and Pfleiderer and the Brock and Kleidon models. In addition, the paper also studies qualitatively the intra-day behaviour of several variables of interest including volume per transaction, transactions per fifteen-minute interval and spreads/trading volume for stocks of differing liquidity. The results suggest that the bid-ask spread is wide at the open, constant through the day and rises slightly at the close. Trading volume, in contrast is not highest at the open and the close. Volatility, based on the mid-point of the inside spread, shows a U-shaped pattern. Volume per transaction, in contrast, is fairly constant throughout the day. Further, the intra-day trading volume pattern differs for liquid and illiquid stocks. The results provide mixed support for current theoretical models of intra-day behaviour of spread, volume and volatility on the London Stock Exchange     

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.