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
Predictability: a way to characterize complexity, Physics Reports, vol.356, issue.6, p.367, 2002. ,
DOI : 10.1016/S0370-1573(01)00025-4
Overfitting or poor learning: a critique of current financial applications of GP, Proceedings of the sixth European conference on genetic programming, pp.34-46, 2003. ,
Genetic Programming and Financial Trading: How Much About "What We Know", Handbook of financial engineering, 2007. ,
DOI : 10.1007/978-0-387-76682-9_5
Forecast accuracy after pretesting with an application to the stock market, Journal of Forecasting, vol.23, issue.4, pp.251-274, 2004. ,
DOI : 10.1002/for.916
Forecasting Time Series by Means of Evolutionary Algorithms, pp.1061-1070, 2004. ,
DOI : 10.1007/978-3-540-30217-9_107
Open BEAGLE, ACM SIGEVOlution, vol.1, issue.1, pp.161-168, 2002. ,
DOI : 10.1145/1138470.1138473
Genetic Programming, Validation Sets, and Parsimony Pressure, Proceedings of the 9th European conference on genetic programming, pp.109-120, 2006. ,
DOI : 10.1007/11729976_10
PRE-TEST ESTIMATION AND TESTING IN ECONOMETRICS: RECENT DEVELOPMENTS, Journal of Economic Surveys, vol.14, issue.2, pp.145-197, 1993. ,
DOI : 10.2307/2289234
Are the directions of stock price changes predictable? Statistical theory and evidence, 2003. ,
A measure of time series' predictability using genetic programming applied to stock returns, Journal of Forecasting, vol.21, issue.5, pp.345-357, 1999. ,
DOI : 10.1002/(SICI)1099-131X(199909)18:5<345::AID-FOR744>3.0.CO;2-7
Evaluation of forecasts produced by genetically evolved models In: Computing in economics and finance, 2000. ,
Foundations of genetic programming, 2002. ,
DOI : 10.1007/978-3-662-04726-2
Reducing failures in investment recommendations using genetic programming, 6th international conference on computing in economics and finance, 2000. ,
Is Technical Analysis in the Foreign Exchange Market Profitable? A Genetic Programming Approach, The Journal of Financial and Quantitative Analysis, vol.32, issue.4, pp.405-427, 1997. ,
DOI : 10.2307/2331231
Estimating predictability: redundancy and surrogate data method. Working Paper 95-07-060, Santa Fe Institute, 1995. ,
Genetic Programming for Financial Time Series Prediction, Proceedings of the fourth European conference on genetic programming, pp.361-370, 2001. ,
DOI : 10.1007/3-540-45355-5_29
Surrogate time series, Physica D: Nonlinear Phenomena, vol.142, issue.3-4, pp.3-4346, 2000. ,
DOI : 10.1016/S0167-2789(00)00043-9
Methods and techniques of complex systems science: an overview Complex systems science in biomedicine, pp.33-114, 2006. ,
Data-Snooping, Technical Trading Rule Performance, and the Bootstrap, The Journal of Finance, vol.64, issue.1997, pp.1647-1692, 1999. ,
DOI : 10.1111/0022-1082.00163
Genetic programming with syntactic restrictions applied to financial volatility forecasting, 2001. ,