, Using genetic algorithms to find technical trading rules1Helpful comments were made by Adam Dunsby, Lawrence Fisher, Steven Kimbrough, Paul Kleindorfer, Michele Kreisler, James Laing, Josef Lakonishok, George Mailath, and seminar participants at Institutional Investor, J.P. Morgan, the NBER Asset Pricing Program, Ohio State University, Purdue University, the Santa Fe Institute, Rutgers University, Stanford University, University of California, Berkeley, University of Michigan, University of Pennsylvania, University of Utah, Washington University (St. Louis), and the 1995 AFA Meetings in Washington, D.C. We are particularly grateful to Kenneth R. French (the referee), and G. William Schwert (the editor) for their suggestions. Financial support from the National Science Foundation is gratefully acknowledged by the first author and from the Academy of Finland by the second and from the Geewax-Terker Program in Financial Instruments by both. Correspondence should be addressed to Franklin Allen, The Wharton School, University of Pennsylvania, Philadelphia, PA 19104-6367.1, Journal of Financial Economics, vol.51, issue.2, pp.245-271, 1999.
DOI : 10.1016/S0304-405X(98)00052-X
, Making Financial Trading by Recurrent Reinforcement Learning, Lecture Notes in Computer Science, vol.17, issue.2, pp.619-626, 2007.
DOI : 10.1002/(SICI)1099-131X(1998090)17:5/6<441::AID-FOR707>3.0.CO;2-#
, ON ESTIMATING THRESHOLDS IN AUTOREGRESSIVE MODELS, Journal of Time Series Analysis, vol.37, issue.3, pp.179-190, 1986.
DOI : 10.1007/BF00533299
, Model calibration and automated trading agent for Euro futures, Quantitative Finance, vol.11, issue.2, pp.531-545, 2012.
DOI : 10.1080/14697688.2012.664921
, An automated FX trading system using adaptive reinforcement learning, Expert Systems with Applications, vol.30, issue.3, pp.543-552, 2006.
DOI : 10.1016/j.eswa.2005.10.012
, FX trading via recurrent reinforcement learning, 2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings., pp.363-370, 2003.
DOI : 10.1109/CIFER.2003.1196283
, Application of stochastic recurrent reinforcement learning to index trading, European Symposium on Artificial Neural Networks, 2011.
, The Intelligent Investor: The Definitive Book on Value Investing. HarperCollins, 2003.
, Regime-switching recurrent reinforcement learning for investment decision making, Computational Management Science, vol.84, issue.408, pp.89-107, 2012.
DOI : 10.1007/s10287-011-0131-1
, Regime-Switching Recurrent Reinforcement Learning in Automated Trading, Natural Computing in Computational Finance, pp.93-121, 2012.
DOI : 10.1007/978-3-642-23336-4_6
, Transition variable selection for regime switching recurrent reinforcement learning, 2014 IEEE Conference on Computational Intelligence for Financial Engineering & Economics (CIFEr), pp.407-412, 2014.
DOI : 10.1109/CIFEr.2014.6924102
, Performance functions and reinforcement learning for trading systems and portfolios, Journal of Forecasting, vol.17, issue.5-6, pp.441-470, 1998.
DOI : 10.1002/(SICI)1099-131X(1998090)17:5/6<441::AID-FOR707>3.0.CO;2-#
, Technical analysis of the financial markets : a comprehensive guide to trading methods and applications, 1999.
, Portfolio optimization using fundamental indicators based on multi-objective ea, Proceedings of the 2014 IEEE Conference on Computational Intelligence for Financial Engineering and Economics, pp.158-165, 2014.
, On a threshold model Pattern recognition and signal processing, NATO ASI Series E: Applied Sc. (29). Sijthoff & Noordhoff, 1978.