Behavioral investment strategy matters: a statistical arbitrage approach
AbstractIn this study, we employ a statistical arbitrage approach to demonstrate that momentum investment strategy tend to work better in periods longer than six months, a result different from findings in past literature. Compared with standard parametric tests, the statistical arbitrage method produces more clearly that momentum strategies work only in longer formation and holding periods. Also they yield positive significant returns in an up market, but negative yet insignificant returns in a down market. Disposition and over-confidence effects are important factors contributing to the phenomenon. The over-confidence effect seems to dominate the disposition effect, especially in an up market. Moreover, the over-confidence investment behavior of institutional investors is the main cause for significant momentum returns observed in an up market. In a down market, the institutional investors tend to adopt a contrarian strategy while the individuals are still maintaining momentum behavior within shorter periods. The behavior difference between investor groups explains in part why momentum strategies work differently between up and down market states. Robustness tests confirm that the momentum returns do not come from firm size, overlapping execution periods, market states definition or market frictions.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 37281.
Date of creation: 16 Aug 2011
Date of revision: 16 Jan 2012
Momentum Strategy; Statistical Arbitrage; Market State; Disposition Effect;
Find related papers by JEL classification:
- G12 - Financial Economics - - General Financial Markets - - - Asset Pricing
- L11 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Production, Pricing, and Market Structure; Size Distribution of Firms
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
- D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search, Learning, and Information
This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-03-21 (All new papers)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Kahneman, Daniel & Tversky, Amos, 1979.
"Prospect Theory: An Analysis of Decision under Risk,"
Econometric Society, vol. 47(2), pages 263-91, March.
- Amos Tversky & Daniel Kahneman, 1979. "Prospect Theory: An Analysis of Decision under Risk," Levine's Working Paper Archive 7656, David K. Levine.
- Weber, Martin & Camerer, Colin F., 1998. "The disposition effect in securities trading: an experimental analysis," Journal of Economic Behavior & Organization, Elsevier, vol. 33(2), pages 167-184, January.
- K. Rouwenhorst, 1996.
"International Momentum Strategies,"
Yale School of Management Working Papers
ysm36, Yale School of Management, revised 01 Feb 2008.
- Jegadeesh, Narasimhan & Titman, Sheridan, 1993. " Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency," Journal of Finance, American Finance Association, vol. 48(1), pages 65-91, March.
- Oleg Bondarenko, 2003. "Statistical Arbitrage and Securities Prices," Review of Financial Studies, Society for Financial Studies, vol. 16(3), pages 875-919, July.
- Kostas Triantafyllopoulos & Giovanni Montana, 2008.
"Dynamic modeling of mean-reverting spreads for statistical arbitrage,"
0808.1710, arXiv.org, revised May 2009.
- K. Triantafyllopoulos & G. Montana, 2011. "Dynamic modeling of mean-reverting spreads for statistical arbitrage," Computational Management Science, Springer, vol. 8(1), pages 23-49, April.
- Eugene F. Fama, .
"Market Efficiency, Long-term Returns, and Behavioral Finance,"
CRSP working papers
340, Center for Research in Security Prices, Graduate School of Business, University of Chicago.
- Fama, Eugene F., 1998. "Market efficiency, long-term returns, and behavioral finance," Journal of Financial Economics, Elsevier, vol. 49(3), pages 283-306, September.
- Eugene F Fama, . "Market Efficiency, Long-Term Returns, and Behavioral Finance," CRSP working papers 448, Center for Research in Security Prices, Graduate School of Business, University of Chicago.
- Mitchell A. Petersen, 2005.
"Estimating Standard Errors in Finance Panel Data Sets: Comparing Approaches,"
NBER Working Papers
11280, National Bureau of Economic Research, Inc.
- Mitchell A. Petersen, 2009. "Estimating Standard Errors in Finance Panel Data Sets: Comparing Approaches," Review of Financial Studies, Society for Financial Studies, vol. 22(1), pages 435-480, January.
- Hogan, Steve & Jarrow, Robert & Teo, Melvyn & Warachka, Mitch, 2004. "Testing market efficiency using statistical arbitrage with applications to momentum and value strategies," Journal of Financial Economics, Elsevier, vol. 73(3), pages 525-565, September.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Ekkehart Schlicht).
If references are entirely missing, you can add them using this form.