Information Asymmetry,Trade Size,and the Dynamic Volume‐Return Relation: Evidence from the Australian Securities Exchange

This paper investigates the influence of information asymmetry on the cross‐sectional variation of volume‐return relation. We find that the dynamic volume‐return relation within medium‐size trades has the most significant response to the degree of information asymmetry. We also show that the effect of information asymmetry on the volume‐return dynamics migrates to small‐size trades in recent years, especially in larger stocks. These results are consistent with the notion that informed traders prefer medium‐size trades and this preference has shifted to small‐size trades. Our findings highlight the importance of incorporating informed traders’ trade‐size decision in the examination of the dynamic volume‐return relation.     

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.     

Individual Investor Trading and Stock Returns

This paper investigates the dynamic relation between net individual investor trading and short‐horizon returns for a large cross‐section of NYSE stocks. The evidence indicates that individuals tend to buy stocks following declines in the previous month and sell following price increases. We document positive excess returns in the month following intense buying by individuals and negative excess returns after individuals sell, which we show is distinct from the previously shown past return or volume effects. The patterns we document are consistent with the notion that risk‐averse individuals provide liquidity to meet institutional demand for immediacy.     

Unpredicted costly dividends and temporary short squeezes

We argue that cash dividend is a type of arbitraging cost that short sellers tend to avoid. We find that dividend announcements lead to temporary short squeezes, causing the prices of highly shorted stocks to overshoot and fully revert over time. These stocks also experience excessive buy-initiated trades and abnormal trading volume in response to dividend announcements. These results are driven mainly by stocks with unpredicted dividends, low lending fees, and high dividend yields. Overall, results suggest that news of a dividend distribution is magnified by short squeezes due to increased short costs and generates excessive nonfundamentals-driven price fluctuations.     

Strategic trading in the wrong direction by a large institutional insider

Many theoretical papers suggest that large informed traders should make misleading or random trades to disguise their trading. Alternatively, informed traders may trade purely on their estimate of stock value. This paper examines the trading behavior of a large institutional insider that periodically trades in the wrong direction, i.e., makes occasional sell (buy) trades within packages of buy (sell) trades. Using a hand-collected data set, we find that three quarters of the trade packages include wrong-direction trades. Wrong trades appear to be used mostly to disguise right-direction trades. We find that the wrong-trade stocks are larger and have less noisy returns, hence, they lack natural disguise. Wrong trades are relatively small, used to accentuate return volatility, distributed evenly during a package of trades, and are not consistently profitable.     

An empirical analysis of the role of the trading intensity in information dissemination on the NYSE

In this paper, we use high-frequency data on five frequently traded stocks listed on the New York Stock Exchange (NYSE) in the year 1999 to examine the price impact of trades and its relation to the trading intensity. We show that the distribution of the absolute price change with fast trading first-order stochastically dominates the distribution of the absolute price change with slow trading. Moreover, we find significant causality from the trade characteristics to the trading intensity. Large trades significantly increase the speed of trading, while large returns tend to decrease the trading intensity. We show that this feedback has little impact on the distribution of the price impact of trades.     

Are extreme returns priced in the stock market? European evidence

This paper revisits some recently found evidence in the literature on the cross-section of stock returns for a carefully constructed dataset of euro area stocks. First, we confirm recent results for US data and find evidence of a negative cross-sectional relation between extreme positive returns and average returns after controlling for characteristics such as momentum, book-to-market, size, liquidity and short term return reversal. We argue that this is the case because these stocks have lottery-like characteristics, which is attractive to certain investors. Also, these stocks tend to be very volatile so that arbitrageurs are discouraged from correcting potential mispricing. As a consequence, these stocks are often overpriced and hence face lower expected returns. Second, when we control for extreme returns, the recently found negative relationship between idiosyncratic risk and future returns is less robust. In our models, after adding maximum returns, the relationship is insignificant and sometimes even positive. We also find that idiosyncratic skewness and coskewness play an important role for asset pricing, as predicted by several theoretical models.     

Correlation and return dispersion dynamics in Chinese markets

This paper studies the relation between firm-level return dispersions and correlations among Chinese stocks during periods of unusually large upward and downward swings. We analyze individual stock returns across 18 sectors and test if return dispersions and stock correlations show asymmetric patterns for extreme up and down markets. Evidence from studies on U.S. stocks suggests that equity return correlations tend to be much greater on the downside than on the upside and that the degree of comovement gets even stronger during extreme market states. However, in the case of Chinese stock market, we find that higher downside correlations apply to only stocks within the Financial sector. With the exception of Financial stocks, we find that stock correlations are significantly higher during up markets, rather than down markets. Regarding firm-level return dispersions, our findings are consistent with rational asset pricing model predictions. We find that equity return dispersions are significantly higher during periods of large price changes.     

Decimals And Liquidity: A Study Of The Nyse

Using a carefully constructed matched sample of control (nondecimal) stocks, we isolate the effects of decimalization for a sample of NYSE‐listed common stocks trading in decimals. We find that the quoted depth as well as the quoted and effective bid‐ask spreads declined significantly following decimalization. Additionally, both the number of trades and trading volume declined significantly. Stock return volatilities display an initial increase but a decline over the longer term, probably as traders become more comfortable in their new milieu.     

Intraday return spillovers and its variations across trading sessions

The main purpose of this paper is to study the intraday return spillovers and their real time variations amongst selected technology stocks. Based upon randomly selected technology stocks in terms of multilateral analysis, we find the following evidence. Firstly, we find that positive spillover effects are discernible amongst medium- and large-sized stocks, with the effects being directionally asymmetric between different size groups. Secondly, we find that for most stocks, the full effects of the firm-specific shocks over other stocks are realized within approximately 30 min to 2 h. Finally, we show that the spillover effects tend to follow an M-shaped intraday pattern. Our results suggest that during the opening and closing sessions, trades motivated by information spilled over from other firms are relatively subordinated, with the trading at these times being largely dominated by those based upon common market factor or firm-specific fundamental information.     

Volume autocorrelation,information, and investor trading

This study investigates whether the widely documented daily correlated trading volume of stocks is driven by individual investor trading, institutional trading, or both. We find that at least 95% of NYSE and AMEX stocks exhibit statistically significant, positive serial correlation. Volume autocorrelation decreases with the level of institutional ownership of a stock. We also show that the rate of arrivals of new information to the market contributes to the clustering of trades. When there is high information flow to the market, institutional trading generates a more pronounced effect on volume autocorrelation than individual investor trading. Our results are broadly consistent with the predictions of trading volume patterns suggested by most theoretical models of stock trading and by empirical research on investor trading.     

Individual Investors and Volatility

We show that retail trading activity has a positive effect on the volatility of stock returns, which suggests that retail investors behave as noise traders. To identify this effect, we use a reform of the French stock market that raises the relative cost of speculative trading for retail investors. The daily return volatility of the stocks affected by the reform falls by 20 basis points (a quarter of the sample standard deviation of the return volatility) relative to other stocks. For affected stocks, we also find a significant decrease in the magnitude of return reversals and the price impact of trades.     

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.     

CEO age and the riskiness of corporate policies

Prior theoretical work generates conflicting predictions with respect to how CEO age impacts risk-taking behavior. Consistent with the prediction that risk-taking behavior decreases as CEOs become older, I document a negative relation between CEO age and stock return volatility. Further analyses reveal that older CEOs reduce firm risk through less risky investment policies. Specifically, older CEOs invest less in research and development, make more diversifying acquisitions, manage firms with more diversified operations, and maintain lower operating leverage. Further, firm risk and the riskiness of corporate policies are lowest when both the CEO and the next most influential executive are older and highest when both of these managers are younger. Although older CEOs prefer less risky investment policies, I document results suggesting that CEO and firm risk preferences tend to be aligned. Lastly, I find that a trading strategy that goes long in a portfolio of stocks consisting of firms managed by younger CEOs and short in a portfolio of stocks comprised of firms led by older CEOs would generate positive risk-adjusted returns. Overall, my results imply that CEO age can have a significant impact on risk-taking behavior and firm performance.     

Impacts of trades in an error-correction model of quote prices

In this paper we analyze and interpret the quote price dynamics of 100 NYSE stocks stratified by trade frequency. We specify an error-correction model for the log difference of the bid and the ask price with the spread acting as the error-correction term, and include as regressors the characteristics of the trades occurring between quote observations, if any. From this model we are also able to extract the implied model for the spread and the mid-quote. We find that short duration and medium volume trades have the largest impacts on quote prices for all one hundred stocks. Further, we find that buys have a greater impact on the ask price than on the bid price, while sells have a greater impact on the bid price than on the ask price. Both buys and sells increase spreads in the short run, but in the absence of further trades, the spreads mean revert. Trades have a greater impact on quotes for the infrequently traded stocks than for the more actively traded stocks.     

Daily institutional trades and stock price volatility in a retail investor dominated emerging market

We examine the short-run dynamic relation between daily institutional trading and stock price volatility in a retail investor-dominated emerging market. We find a significantly negative relation between volatility and institutional net trading that is mainly due to the unexpected institutional trading. The price volatility–institutional trade relation differs for institutional buys and institutional sells, and for small and large stocks. Institutional investors herd-trade in large stocks, but do not systematically engage in positive-feedback trading. We argue that the net impact of informational and noninformational institutional trades determines the relation between volatility and institutional trading, and that the relation is negative when informational trading by institutions prevails.     

Informed Trading through the Accounts of Children

This study shows that the guardians behind underaged accounts are successful at picking stocks. Moreover, they tend to channel their best trades through the accounts of children, especially when they trade just before major earnings announcements, large price changes, and takeover announcements. Building on these results, we argue that the proportion of total trading activity through underaged accounts (labeled BABYPIN) should serve as an effective proxy for the probability of information trading in a stock. Consistent with this claim, we show that investors demand a higher return for holding stocks with a greater likelihood of private information, proxied by BABYPIN.     

Small-cap equity mutual fund managers as liquidity providers

This paper examines the relation between the performance of small-cap equity mutual funds and the liquidity characteristics of their asset holdings. We study the trading behavior of fund managers and show that on average, they tend to buy less liquid stocks and sell more liquid stocks. We introduce the notion of net “liquidity creation” by fund managers and examine its role in explaining the cross section of small-cap equity mutual fund returns. Our empirical results show that on average, small-cap mutual fund managers are able to earn an additional 1.5% return per year as compensation for providing such liquidity services to the market.     

An analysis of trade-size clustering and its relation to stealth trading

NYSE and Nasdaq trades increasingly cluster on multiples of 500, 1,000, and 5,000 shares. Such clustering varies over time and across stocks, and tends to increase with the level of trading activity. Furthermore, rounded trades tend to have more persistence both in occurrence and in trade initiation. Finally, medium-sized rounded trades tend to have greater relative price impact than large rounded trades. From these observations we surmise that trade-size clustering is consistent, at least in part, with the actions of stealth traders who tend to use medium-sized rounded transactions in an attempt to disguise their trades.     

Transitions in the stock markets of the US,UK and Germany

In an analysis of the US, the UK and German stock market, we find a change in the behaviour based on the stocks’ beta values. In the years 1995–2006, trades of stocks with high beta and large volume were concentrated in the IT and technology sector, whereas in 2006–2012 those trades are dominated by stocks from the financial sector. We show that an agent-based model can reproduce such a transition. We further show that the initial impulse for the transition might stem from the increase of high-frequency trading at that time.