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Behavioral investment strategy matters: a statistical arbitrage approach

  • Sun, David
  • Tsai, Shih-Chuan
  • Wang, Wei

In 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.

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File URL: http://mpra.ub.uni-muenchen.de/37281/1/MPRA_paper_37281.pdf
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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 37281.

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Date of creation: 16 Aug 2011
Date of revision: 16 Jan 2012
Handle: RePEc:pra:mprapa:37281
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  1. K. Geert Rouwenhorst, 1998. "International Momentum Strategies," Journal of Finance, American Finance Association, vol. 53(1), pages 267-284, 02.
  2. Kent Daniel & David Hirshleifer & Avanidhar Subrahmanyam, 1998. "Investor Psychology and Security Market Under- and Overreactions," Journal of Finance, American Finance Association, vol. 53(6), pages 1839-1885, December.
  3. William N. Goetzmann & Evan Geov Gatev & K. Geert Rouwenhorst, 1998. "Pairs Trading: Performance of a Relative Value Arbitrage Rule," Yale School of Management Working Papers ysm109, Yale School of Management.
  4. 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.
  5. 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.
  6. Kostas Triantafyllopoulos & Giovanni Montana, 2008. "Dynamic modeling of mean-reverting spreads for statistical arbitrage," Papers 0808.1710, arXiv.org, revised May 2009.
  7. Fama, Eugene F., 1998. "Market efficiency, long-term returns, and behavioral finance," Journal of Financial Economics, Elsevier, vol. 49(3), pages 283-306, September.
  8. 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.
  9. Oleg Bondarenko, 2003. "Statistical Arbitrage and Securities Prices," Review of Financial Studies, Society for Financial Studies, vol. 16(3), pages 875-919, July.
  10. 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.
  11. Kahneman, Daniel & Tversky, Amos, 1979. "Prospect Theory: An Analysis of Decision under Risk," Econometrica, Econometric Society, vol. 47(2), pages 263-91, March.
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