Why investors should not be cautious about the academic approach to testing for stock market anomalies
Brian Lucey and
Angel Pardo
Applied Financial Economics, 2005, vol. 15, issue 3, 165-171
Abstract:
The ability of investors to implement seasonal strategies implied by academic papers has been widely criticized, most recently by Hudson et al. (Applied Financial Economics, 12, 681-86, 2002). This paper addresses these concerns, and provides an example of a strategy derived from academic papers that indicates how and to what profitability such a strategy can be implemented. In particular, the pre-holiday anomaly is examined, where returns tend to be higher on the day before a holiday. After checking that the pre-holiday return compensates market frictions, the existence and the changing nature of such anomaly is tested. Finally, the profitability of the pre-holiday trading strategy in an out-of-the-sample period is assessed by checking that the pre-holiday profit is clearly different from the result an investor would obtain on a set of randomly selected days. This evidence is provided for three large stocks and an index in two different markets, Spain and Ireland.
Date: 2005
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (13)
Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/0960310042000313213 (text/html)
Access to full text is restricted to subscribers.
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:taf:apfiec:v:15:y:2005:i:3:p:165-171
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAFE20
DOI: 10.1080/0960310042000313213
Access Statistics for this article
Applied Financial Economics is currently edited by Anita Phillips
More articles in Applied Financial Economics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().