A Broad-Spectrum Computational Approach for Market Efficiency
The Efficient Market Hypothesis (EMH) is one of the most investigated questions in Finance. Nevertheless, it is still a puzzle, despite the enormous amount of research it has provoked. For instance, it is still discussed that market cannot be outperformed in the long run (Detry and Gregoire, 2001), persistent market anomalies cannot be easily explained in this theoretical framework (Shiller, 2003) and some talented hedge-fund managers keep earning excess risk-adjusted rates of returns regularly. We concentrate in this paper on the weak form of efficiency(Fama, 1970). We focus on the efficacity of simple technical trading rules, following a large research stream presented in Park and Irwin (2004). Nevertheless, we depart from previous works in many ways : we first have a large population of technical investment rules (more than 260.000) exploiting real-world data to manage a financial portfolio. Very few researches have used such a large amount of calculus to examine the EMH. Our experimental design allows for strategy selection based on past absolute performance. We take into account the data-snooping risk, which is an unavoidable problem in such broad-spectrum researches, using a rigorous Bootstrap Reality Check procedure. While market inefficiencies, after including transaction costs, cannot clearly be successfully exploited, our experiments present troubling outcomes inviting close re-consideration of the weak-form EMH.
|Date of creation:||04 Jul 2006|
|Date of revision:|
|Contact details of provider:|| Web page: http://comp-econ.org/|
More information through EDIRC
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.:
- Brock, William & Lakonishok, Josef & LeBaron, Blake, 1992.
" Simple Technical Trading Rules and the Stochastic Properties of Stock Returns,"
Journal of Finance,
American Finance Association, vol. 47(5), pages 1731-64, December.
- Brock, W. & Lakonishok, J. & Lebaron, B., 1991. "Simple Technical Trading Rules And The Stochastic Properties Of Stock Returns," Working papers 90-22, Wisconsin Madison - Social Systems.
- Halbert White, 2000. "A Reality Check for Data Snooping," Econometrica, Econometric Society, vol. 68(5), pages 1097-1126, September.
- Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Journal of Economic Perspectives, American Economic Association, vol. 17(1), pages 59-82, Winter.
- Robert J. Shiller, 2002.
"From Efficient Market Theory to Behavioral Finance,"
Cowles Foundation Discussion Papers
1385, Cowles Foundation for Research in Economics, Yale University.
- Robert J. Shiller, 2003. "From Efficient Markets Theory to Behavioral Finance," Journal of Economic Perspectives, American Economic Association, vol. 17(1), pages 83-104, Winter.
- Park, Cheol-Ho & Irwin, Scott H., 2004. "The Profitability of Technical Analysis: A Review," AgMAS Project Research Reports 37487, University of Illinois at Urbana-Champaign, Department of Agricultural and Consumer Economics.
- Jensen, Michael C & Bennington, George A, 1970. "Random Walks and Technical Theories: Some Additional Evidence," Journal of Finance, American Finance Association, vol. 25(2), pages 469-82, May.
- Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
- S. Illeris & G. Akehurst, 2002. "Introduction," The Service Industries Journal, Taylor & Francis Journals, vol. 22(1), pages 1-3, January.
When requesting a correction, please mention this item's handle: RePEc:sce:scecfa:492. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum)
If references are entirely missing, you can add them using this form.