A FURTHER EXAMINATION OF STOCK PRICE CHANGES AND TRANSACTION VOLUME

This study provides a further test of whether the price change-volume relationship is asymmetric as Epps' theoretical model and empirical evidence indicate. Testing during periods of known information arrival supports his hypothesis that the ratio of volume to absolute price change on price increases is higher than that ratio on equivalent price decreases. There is some contrary evidence when the testing occurs over trading days for which there is no known information arrival. This reversal of results could be due to the combined effect of positive transaction costs and no information arrival. There is evidence in support of this explanation.     

Sequential information arrival in the Finnish stock index derivatives markets

This paper investigates the hypothesis of sequential information arrival in the Finnish stock index futures and options markets. With no short selling restrictions in the derivatives markets, no causality relationships between returns and trading volume are observed. However, by using the so-called call-put signal, based on call and put volumes, causality between returns and volume is found supporting the hypothesis of sequential information arrival. In addition, it is discovered that the increased volume in stock index options relative to index futures has significantly increased their importance in the intermarket price discovery process.     

Differences of opinion make a horse race

A model of trading in speculative markets is based on differencesof opinion among traders. Our purpose is to explain some ofthe empirical regularities that have been documented concerningthe relationship between volume and price and the time-seriesproperties of price and volume. We assume that traders sharecommon prior beliefs and receive common information but differin the way in which they interpret this information. Some resultsare that absolute price changes and volume are positively correlated,consecutive price changes exhibit negative serial correlation,and volume is positively autocorrelated.     

THE EMPIRICAL RELATIONSHIP BETWEEN TRADING VOLUME,RETURNS AND VOLATILITY

This paper presents an empirical analysis of the relationship between trading volume, returns and volatility in the Australian stock market. The initial analysis centres upon the volume-price change relationship. The relationship between trading volume and returns, irrespective of the direction of the price change, is significant across three alternative measures of daily trading volume for the aggregate market. This finding also provides basic support for a positive relationship between trading volume and volatility. Furthermore, evidence is found supporting the hypothesis that the volume-price change slope for negative returns is smaller than the slope for non-negative returns, thereby supporting an asymmetric relationship which is hypothesised to exist because of differential costs of taking long and short positions. Analysis at the individual stock level shows weaker support for the relationship. A second related hypothesis is tested in which the formation of returns is conditional upon information arrival which similarly affects trading volume. The hypothesis is tested by using the US overnight return to proxy for expected “news” and trading volume to proxy for news arrival during the day. The results show a reduction in the significance and magnitude of persistence in volatility and hence are consistent with explaining non-normality in returns (and ARCH effects) through the rate of arrival of information. The findings in this paper help explain how returns are generated and have implications for inferring return behaviour from trading volume data.     

Trading volume,heterogeneity of expectations,and the disperson of volatilities implied by option prices

Trading volume studies have traditionally emphasized the correlation between volume and price movements or between volume changes and the arrival of information. This article explores the relationship between volume and the heterogeneity of underlying asset volatility expectations implied by option prices. An index of aggregate trading volume of the S&P 100 index is constructed and shown to be significantly positively related to a measure of heterogeneity of risk expectations. We discuss possible explanations for this phenomenon and its implications for previously-reported volume relationships.     

Price Discovery and Dissemination of Private Information by Loan Syndicate Participants

We delineate key channels through which flows of confidential information to loan syndicate participants impact the dynamics of information arrival in prices. We isolate the timing of private information flows by estimating the speed of price discovery over quarterly earnings cycles in both secondary syndicated loan and equity markets. We identify borrowers disseminating private information to lenders relatively early in the cycle with firms exhibiting relatively early price discovery in the secondary loan market, documenting that price discovery is faster for loans subject to financial covenants, particularly earnings‐based covenants; for borrowers who experience covenant violations; for borrowers with high credit risk; and for loans syndicated by relationship‐based lenders or highly reputable lead arrangers. We then ask whether early access to private information in the loan market accelerates the speed of information arrival in stock prices. We document that the stock returns of firms identified with earlier private information dissemination to lenders indeed exhibit faster price discovery in the stock market, but only when institutional investors are involved in the firm's syndicated loans. Further, the positive relation between institutional lending and the speed of stock price discovery is more pronounced in relatively weak public disclosure environments. These results are consistent with institutional lenders systematically exploiting confidential syndicate information via trading in the equity market.     

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 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.     

Testing the bivariate mixture hypothesis using German Stock market data

According to the bivariate mixture hypothesis (BMH) as proposed by Tauchen and Pitts (1983) and Harris (1986, 1987) the daily price changes and the corresponding trading volume on speculative markets follow a joint mixture of distributions with the unobservable number of daily information events serving as the mixing variable. Using German stock market data of 15 major companies the distributional properties of the BMH is tested employing maximum-likelihood as well as generalised method of moments estimation techniques. In addition to providing a new approach for the pointwise estimation of the latent information arrival rate based on the maximum-likelihood method, we investigate the time-series properties of the BMH. the major results can be summarised as follows: (i) the distributional characteristics of the data (especially leptokurtosis and skewness in the distribution of price changes and volume respectively) cannot be explained satisfactorily by the BMH; univariate mixture models for price changes and trading volume separately reveal a possible specification error in the model; (ii) a univariate normal mixture model can account for the observed distributional characteristics of price changes; (iii) the estimated process of the latent information rate cannot fully explain the time-series characteristics of the data (especially the volatility clustering or ARCH-effects).     

Public Information Arrival

We develop a measure of public information flow to financial markets and use it to document the patterns of information arrival, with an emphasis on the intraday flows. The measure is the number of news releases by Reuter's News Service per unit of time. We find that public information arrival is nonconstant, displaying seasonalities and distinct intraday patterns. Next we relate our measure of public information to aggregate measures of intraday market activity. Our results suggest a positive, moderate relationship between public information and trading volume, but an insignificant relationship with price volatility.     

Price Volatility and Investor Behavior in an Overlapping Generations Model with Information Asymmetry

This paper studies an overlapping generations model with multiple securities and heterogeneously informed agents. The model produces multiple equilibria, including highly volatile equilibria that can exhibit strong or weak correlations between asset returns—even when asset supplies and future dividends are uncorrelated across assets. Less informed agents rationally behave like trend‐followers, while better informed agents follow contrarian strategies. Trading volume has a hump‐shaped relation with information precision and is positively correlated with absolute price changes. Finally, accurate information increases the volatility and correlation of stock returns in the highly volatile, strongly correlated equilibrium.     

EARNINGS ANNOUNCEMENTS,QUALITY AND QUANTITY OF INFORMATION,AND STOCK PRICE CHANGES

We analyze the informational effect of earnings announcements on stock price changes. Although prior studies postulate that the direction and magnitude of earnings surprises contribute to abnormal stock price changes, we attribute earnings surprises and subsequent stock price changes to the quality and quantity of available information. If a stock is followed by many financial analysts, the amount of information available to investors contributes to higher quality information, which in turn is reflected by a small earnings surprise. Furthermore, we demonstrate that as the quality and quantity of information increase, stock prices adjust more quickly, which sheds additional light on the post-earnings-announcement drift issue. Finally, cross-sectional analysis reveals that the flow of information, as measured by the rate of trading volume changes, and the stock of information, as measured by the number of financial analysts, contributes significantly to the variations in excess returns and return volatility. Traditional variables, such as earnings surprises, earnings reporting lag, and firm size, do not perform well.     

Inferring Information Frequency and Quality

We develop a microstructure model that, in contrast to previousmodels, allows one to estimate the frequency and quality ofprivate information. In addition, the model produces stationaryasset price and trading volume series. We find evidence thatinformation arrives frequently within a day and that this informationis of high quality. The frequent arrival of information, whilein contrast to previous microstructure model estimates, accordswith nonmodel-based estimates and the related literature testingthe mixture-of-distributions hypothesis. To determine if theestimates are correctly reflecting the arrival of latent information,we estimate the parameters over half-hour intervals within theday. Comparison of the parameter estimates with measures ofpersistent price changes reveals that the estimates reflectthe arrival of latent information.     

Intraday Price Change and Trading Volume Relations in the Stock and Stock Option Markets

This study investigates intraday relations between price changes and trading volume of options and stocks for a sample of firms whose options traded on the CBOE during the first quarter of 1986. After purging the price change series of the effects of bid/ask spreads, multivariate time-series analysis is used to estimate the lead/lag relation between the price changes in the option and stock markets. The results indicate that price changes in the stock market lead the option market by as much as fifteen minutes. The analysis of trading volume indicates that the stock market lead may be even longer.     

信息披露考核降低了股价崩盘风险吗？

深交所自2001年起对于上市公司的信息披露工作进行考核。本文从信息透明度的 角度,利用深交所上市公司信息披露考核数据,考察信息披露质量对股价崩盘风险的影响。研 究发现：（1）深圳证券交易所的信息披露考核对于股价崩盘风险有显著影响,整体来看上市 公司的信息披露质量与股价崩盘风险存在显著的负向关系;（2）对于经营业绩较差的公司而 言,信息披露质量与股价崩盘风险的负向关系更加显著;（3）相对于非主板公司而言,信息披 露质量对主板公司的股价崩盘风险的抑制作用更加显著。     

Volume,volatility and information linkages in the stock and option markets

This paper examines the relationship between option trading activity and stock market volatility. Although the option market is uniquely suited for trading on volatility information, there is little analysis on how trading activity in this market is linked to stock price volatility. The bulk of the discussion tends to focus on whether trading activity in the stock market is informative about stock volatility. To analyze the information in option trading activity for stock market volatility, a sample of 15 stocks with the highest option trading volume is selected. For each stock, it is noted that the trading activities in the put and call option markets have significant explanatory power for stock market volatility. In addition, the results indicate that the call option trading activity has a stronger impact on stock volatility compared with that of the put options. Our results demonstrate that information and sentiment in the option market is useful for the estimation of stock market volatility. Also, the significance of the effects of option trading activity on stock price volatility is observed to be comparable to that of stock market trading activity. Furthermore, the persistence and asymmetric effects in the volatility of some stocks tend to disappear once option trading activity is taken into account.     

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.     

Information content of volume: An investigation of Tokyo commodity futures markets

This study examines the relationship between volume and price changes for Tokyo commodity futures contracts by focusing on the predictive power of volume. The findings indicate a positive simultaneous relation between volume and absolute returns. The relation is not entirely contemporaneous since lagged volume contains predictive power for absolute returns. However, linear and nonlinear causality tests show that volume does not forecast returns. The results are qualitatively the same for contracts traded with different methods.     

Internet search intensity,liquidity and returns in emerging markets

Using a sample of listed companies in the Vietnam stock market from 2013 to 2018, this paper investigates the linkage between Internet search intenseness and stock returns and trading volume. The empirical results confirm the “price pressure hypothesis” that search intensity is positively associated with subsequent stock returns and trading volume. It also finds that the positive effects on stock returns are not temporary but remain for the long term although some reversals occur. The results show that the effects of search intensity on stock returns are higher for large stocks than for small stocks. The findings also reveal that stocks that attract more attention from the public are exposed to higher market risk. These findings have not been documented in the literature so they enrich the information on the relationship between Internet search intenseness and stock market returns, especially for emerging markets where Internet user numbers are sharply increasing.     

Trading volume,time-varying conditional volatility,and asymmetric volatility spillover in the Saudi stock market

Despite the well known importance of volatility–volume relationship, there is a paucity of research on this topic in emerging markets. We attempt to partially fill this gap by investigating volatility–volume relationship in the most important exchange market in the Middle East. We test the effect of trading volume on the persistence of the time-varying conditional volatility of returns in the Saudi stock market. Overall our results support the mixture of distribution hypothesis at the firm level. We also use two different proxies for information arrival, intra-day volatility, and overnight indicators. We find that these are good proxies for information and are important as contemporaneous volume in explaining conditional volatility. We also test for the volatility spillover direction between large- and small-cap portfolios. Our results show that the spillover effect is larger and statistically significant from large to small companies.