tailieunhanh - TRADING VOLUME AND CROSS-AUTOCORRELATIONS IN STOCK RETURNS

The rationale for using oil price movements as a factor affecting stock valuations is that, in theory, the value of stock equals the discounted sum of expected future cash flows. These cash flows are affected by macroeconomic events that can be influenced by oil shocks. Indeed, oil exports affect the main economic variables in GCC countries: earnings, government budget revenues and expenditures and aggregate demand. So oil price increases should positively affect corporate output and earnings, and then stock returns in these countries. However, GCC countries are also importers of manufactured goods from developed and emerging countries. . | THE JOURNAL OF FINANCE VOL. LV NO. 2 APRIL 2000 Trading Volume and Cross-Autocorrelations in Stock Returns TARUN CHORDIA and BHASKARAN SWAMINATHAN ABSTRACT This paper finds that trading volume is a significant determinant of the lead-lag patterns observed in stock returns. Daily and weekly returns on high volume portfolios lead returns on low volume portfolios controlling for firm size. Nonsynchro-nous trading or low volume portfolio autocorrelations cannot explain these findings. These patterns arise because returns on low volume portfolios respond more slowly to information in market returns. The speed of adjustment of individual stocks confirms these findings. Overall the results indicate that differential speed of adjustment to information is a significant source of the cross-autocorrelation patterns in short-horizon stock returns. Both academics and practitioners have long been interested in the role played by trading volume in predicting future stock In this paper we examine the interaction between trading volume and the predictability of short horizon stock returns specifically that due to lead-lag cross-autocorrelations in stock returns. Our investigation indicates that trading volume is a sig-nif icant determinant of the cross-autocorrelation patterns in stock We find that daily or weekly returns of stocks with high trading volume lead daily or weekly returns of stocks with low trading volume. Additional tests indicate that this effect is related to the tendency of high volume stocks to respond rapidly and low volume stocks to respond slowly to marketwide information. Chordia is from Vanderbilt University and Swaminathan is from Cornell University. We thank Clifford Ball Doug Foster Roger Huang Charles Lee Craig Lewis Ron Masulis Matt Spiegel Hans Stoll Avanidhar Subrahmanyam two anonymous referees the editor René Stulz and seminar participants at the American Finance Association meetings Eastern Finance Association meetings Southern .