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AbstractPrevious research identifies a causal relationship between returns and trading volume. But volume has two components: number of trades and number of shares per trade. In this paper the relationship between each of these volume components and returns is examined and the number of trades is found to be the dominant component. Results show that return activity in a period is associated with the level of trading frequency in a subsequent period and also with the number of shares in a subsequent period. This is consistent with small traders reacting to returns while professional traders largely ignore previous returns in their trading.

AbstractThis paper examines intra‐trading‐day and overnight returns constructed from a transactions data base. Day‐of‐the‐week effects are examined for firms classified by level of thin trading. Results indicate that thin trading masks day‐of‐the‐week effects. Day‐of‐the‐week effects are much more pronounced for actively traded stocks. The importance of controlling for thin trading in studies where segmentation of returns into distinct periods is important is illustrated through an examination of day‐of‐the‐week effects for firms classified by size.

AbstractRecent research has shown that thin trading can seriously bias beta estimates. Present techniques for controlling this bias in research designs involve the adjustment of OLS betas. This paper presents a new methodology that controls for this bias by forming portfolios where the level of thin trading is held constant, while the difference of another variable, pertinent to a specific research design, is maximized across the portfolios. Directly controlling the level of thin trading avoids reliance on beta adjustment techniques. Further, the linear programming model permits the control of the mean and higher moments of additional variables across portfolios.

AbstractCross‐listings of equities internationally are becoming more common. Using data for Europe and North America, previous studies reject the order flow diversion hypothesis, which states that international cross‐listings reduce home‐country trading volume. We test this hypothesis using data for equities cross‐listed in Singapore and Malaysia. We find that trading volume in Malaysia fell 42.9% when Singapore markets were closed for holidays. Furthermore, we show that trading volume in Malaysia did not increase following the implementation of regulations that ended the trading of Malaysian equities in Singapore in 1998. Hence, we reject the order flow diversion hypothesis.

AbstractWe test whether an increase either in informed trades or in large liquidity trades leads to greater correlation of trading volume across markets. We confirm that both trading volume and positive returns of target companies are abnormally high before merger announcements. We find a statistically significant increase in the correlation between New York Stock Exchange and Nasdaq/regional trading volume before merger announcements. Furthermore, after merger announcements, we find evidence of both large liquidity trading and a statistically significant increase in the correlation of trading volume across markets.