| This study investigates, both analytically and empirically, the effects of prior beliefs on trading volume. This study extends Varian (1989) and develops a two-period model of trading volume based on the assumption of heterogeneous prior beliefs. The model provides several insights into how heterogeneity of prior beliefs affects trading volume: (1) the degree of heterogeneity can be decomposed into two components, "bias differential" and "precision differential"; (2) trading volume is a function of bias differential and precision differential; and (3) bias differential and precision differential affect trading volume differently. Bias differential affects trading volume only in period 1, while precision differential affects trading volume in both periods.;Experimental results indicate that trading volume is affected by the heterogeneity of prior beliefs. In the first sub-period, trading volume is greater under heterogeneous prior beliefs than under homogeneous prior beliefs. In the second sub-period, trading volume under prior beliefs with zero bias differential (but with positive precision differential) is greater than trading volume under either homogeneous prior beliefs or under heterogeneous prior beliefs with zero precision differential. However, there is no significant difference between trading volume under homogeneous prior beliefs and that under heterogeneous prior beliefs with zero precision differential, in the second sub-period.;To summarize, with other things being equal, (1) when traders have homogeneous prior beliefs, trading volume is likely to be relatively light both before and after public announcement (e.g., earnings announcement or management forecast); (2) when traders have heterogeneous prior beliefs with precision differential (but with zero bias differential), trading volume is likely to be heavy both before and after public announcement; and (3) when traders have heterogeneous prior beliefs with bias differential (but with zero precision differential), trading volume is likely to be relatively heavy before public announcement and be relatively light after public announcement. Therefore, by observing trading volume before and after public announcement, we can make inferences about the information structure of an asset market which is not directly observable. |
