Volume and Price Patterns Around a Stock's 52-Week Highs and Lows: Theory and Evidence

Steven Huddart, Mark Lang () and Michelle H. Yetman ()
Additional contact information
Mark Lang: Kenan-Flagler Business School, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599
Michelle H. Yetman: Graduate School of Management, University of California at Davis, Davis, California 95616

Management Science, 2009, vol. 55, issue 1, 16-31

Abstract: We provide large sample evidence that past price extremes influence investors' trading decisions. Volume is strikingly higher, in both economic and statistical terms, when the stock price crosses either the upper or lower limit of its past trading range. This increase in volume is more pronounced the longer the time since the stock price last achieved the price extreme, the smaller the firm, the higher the individual investor interest in the stock, and the greater the ambiguity regarding valuation. These results are robust across model specifications and controls for past returns and news arrival. Volume spikes when price crosses either the upper or lower limit of the past trading range, then gradually subsides. After either event, returns are reliably positive and, among small investors, trades classified as buyer-initiated are elevated. Overall, results are more consistent with bounded rationality than with other candidate explanations.

Keywords: decision analysis; prospect theory; value function; reference point; behavioral finance; attention (search for similar items in EconPapers)
Date: 2009
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (50)

Downloads: (external link)
http://dx.doi.org/10.1287/mnsc.1080.0920 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:55:y:2009:i:1:p:16-31

Access Statistics for this article

More articles in Management Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().