This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

Evaluating the performance of adapting trading strategies with different memory lengths

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Andreas Krause
Abstract

We propose a prediction model based on the minority game in which traders continuously evaluate a complete set of trading strategies with different memory lengths using the strategies' past performance. Based on the chosen trading strategy they determine their prediction of the movement for the following time period of a single asset. We find empirically using stocks from the S&P500 that our prediction model yields a high success rate of over 51.5% and produces higher returns than a buy-and-hold strategy. Even when taking into account trading costs we find that using the predictions will generate superior investment portfolios.

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. 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.

File URL: http://arxiv.org/abs/0901.0447
File Format: text/html
File Function: Abstract
Download Restriction: no
File URL: http://arxiv.org/pdf/0901.0447
File Format: application/pdf
File Function: Latest version
Download Restriction: no

Publisher Info
Paper provided by arXiv.org in its series Quantitative Finance Papers with number 0901.0447.

Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Length:
Date of creation: Jan 2009
Date of revision:
Handle: RePEc:arx:papers:0901.0447

Contact details of provider:
Web page: http://arxiv.org/

For technical questions regarding this item, or to correct its listing, contact: (arXiv administrators).

Related research
Keywords:

Other versions of this item:

References listed on IDEAS
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.:
  1. Andrew W. Lo & Harry Mamaysky & Jiang Wang, 2000. "Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation," Journal of Finance, American Finance Association, vol. 55(4), pages 1705-1770, 08. [Downloadable!] (restricted)
    Other versions:
  2. Marshall, Ben R. & Young, Martin R. & Rose, Lawrence C., 2006. "Candlestick technical trading strategies: Can they create value for investors?," Journal of Banking & Finance, Elsevier, vol. 30(8), pages 2303-2323, August. [Downloadable!] (restricted)
  3. Fernandez-Rodriguez, Fernando & Gonzalez-Martel, Christian & Sosvilla-Rivero, Simon, 2000. "On the profitability of technical trading rules based on artificial neural networks:: Evidence from the Madrid stock market," Economics Letters, Elsevier, vol. 69(1), pages 89-94, October. [Downloadable!] (restricted)
    Other versions:
  4. 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. [Downloadable!] (restricted)
    Other versions:
  5. Nam, Kiseok & Washer, Kenneth M. & Chu, Quentin C., 2005. "Asymmetric return dynamics and technical trading strategies," Journal of Banking & Finance, Elsevier, vol. 29(2), pages 391-418, February. [Downloadable!] (restricted)
  6. Allen, Franklin & Karjalainen, Risto, 1999. "Using genetic algorithms to find technical trading rules1," Journal of Financial Economics, Elsevier, vol. 51(2), pages 245-271, February. [Downloadable!] (restricted)
  7. Damien Challet & Matteo Marsili & Yi-Cheng Zhang, 2001. "Stylized facts of financial markets and market crashes in Minority Games," Quantitative Finance Papers cond-mat/0101326, arXiv.org. [Downloadable!]
Full references

Statistics
Access and download statistics

Did you know? All full texts are decentralized with the publishers, none reside on this server, thus making it possible to offer this service for free to all parties.

This page was last updated on 2009-11-30.

This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.