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Failure of Genetic-Programming Induced Trading Strategies:
Distinguishing between Eﬃcient Markets and Ineﬃcient Algorithms
Shu-Heng Chen1 and Nicolas Navet1,2     AI-ECON Research Center,
Department of Economics, National Chengchi     University,
Taipei, Taiwan 11623, chchen@nccu.edu.tw     LORIA-INRIA,
Campus-Scientiﬁque, BP239, F-54506 Vandoeuvre, France,  Summary.
Over the last decade, numerous papers have investigated the use
of Ge- netic Programming (GP) for creating ﬁnancial trading
strategies. Typically, in the literature, the results are
inconclusive but the investigators always suggest the pos-
sibility of further improvements, leaving the conclusion
regarding the eﬀectiveness of GP undecided. In this paper, we
discuss a series of pretests aimed at giving more clear-cut
answers as to whether GP can be eﬀective with the training data
at hand. Precisely, pretesting allows us to distinguish between
a failure due to the market being eﬃcient or due to GP being