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Return Anomalies, Disagreement, and Trading Volume

Sankarshan Basu, Srinivasan Rangan and Nikhil Vidhani
2023
Working Paper No
680
Body

We propose a new measure of investor disagreement based on thirty-nine factors from the return-predicting anomaly literature. Consistent with theoretical work on volume, we show that a one standard deviation change in anomaly-based disagreement is associated with a 16.7% higher turnover in the next period. Disagreement effects on volume are stronger for firms with more complex information releases and weaken after the exogenous introduction of the SEC EDGAR filing system. Anomaly-based disagreement also relates positively to analysts’ forecast dispersion and absolute forecast errors in earnings and target prices suggesting that it influences their behavior.

Key words
Disagreement, Return Anomalies, Trading Volume
WP No. 680.pdf (1.15 MB)

Return Anomalies, Disagreement, and Trading Volume

Author(s) Name: Sankarshan Basu, Srinivasan Rangan and Nikhil Vidhani, 2023
Working Paper No : 680
Abstract:

We propose a new measure of investor disagreement based on thirty-nine factors from the return-predicting anomaly literature. Consistent with theoretical work on volume, we show that a one standard deviation change in anomaly-based disagreement is associated with a 16.7% higher turnover in the next period. Disagreement effects on volume are stronger for firms with more complex information releases and weaken after the exogenous introduction of the SEC EDGAR filing system. Anomaly-based disagreement also relates positively to analysts’ forecast dispersion and absolute forecast errors in earnings and target prices suggesting that it influences their behavior.

Keywords: Disagreement, Return Anomalies, Trading Volume
WP No. 680.pdf (1.15 MB)