Review of Behavioral Economics > Vol 6 > Issue 3

Abnormal Trading Volumes around Large Stock Price Moves and Subsequent Price Dynamics

Andrey Kudryavtsev, The Max Stern Yezreel Valley Academic College, Israel, andreyk@yvc.ac.il
 
Suggested Citation
Andrey Kudryavtsev (2019), "Abnormal Trading Volumes around Large Stock Price Moves and Subsequent Price Dynamics", Review of Behavioral Economics: Vol. 6: No. 3, pp 283-311. http://dx.doi.org/10.1561/105.00000109

Publication Date: 01 Aug 2019
© 2019 A. Kudryavtsev
 
Subjects
Behavioral finance
 
Keywords
JEL Codes: G11G14G19
Abnormal Trading VolumesBehavioral FinanceLarge Price ChangesStock Price DriftsStock Price Reversals
 

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In this article:
1. Introduction 
2. Literature Review 
3. Research Hypothesis 
4. Data Description and Research Design 
5. Results Description 
6. Concluding Remarks 
Appendix 
References 

Abstract

The study analyzes the correlation between abnormal trading volumes accompanying large stock price changes and subsequent stock price dynamics. Assuming that abnormal trading volume associated with a large price move may serve as an indication for the extent of the immediate stock price reaction to the underlying company-specific shock, I suggest that large price moves accompanied by relatively high (low) abnormal trading volumes may be followed by price reversals (drifts). Analyzing a large sample of major daily stock price moves and defining the latter according to a number of alternative proxies, I document that both large price increases and decreases accompanied by high (low) abnormal trading volumes are followed by significant price reversals (drifts) on each of the next two trading days and over five- and twenty-day intervals following the initial price move, the magnitude of the reversals (drifts) increasing over longer post-event windows. The effect remains significant after accounting for additional companyspecific (size, CAPM beta, historical volatility) and event-specific (stock’s absolute return on the event day) factors, and is robust to different methods of calculating abnormal returns and to different sample filtering criteria.

DOI:10.1561/105.00000109