Toward a Computable Approach to the Efficient Market Hypothesis: An Application of Genetic Programming

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@Article{chen:1996:caemh,

• author = "Shu-Heng Chen and Chia-Hsuan Yeh",
• title = "Toward a Computable Approach to the Efficient Market Hypothesis: An Application of Genetic Programming",
• journal = "Journal of Economic Dynamics and Control",
• year = "1997",
• volume = "21",
• number = "6",
• pages = "1043--1063",
• month = "1 " # jun,
• keywords = "genetic algorithms, genetic programming, Evolutionary computation, Minimum description length principle, Mean absolute percentage error, Efficient market hypothesis",
• DOI = "doi:10.1016/S0165-1889(97)82991-0",
• broken = "http://www.sciencedirect.com/science/article/B6V85-3SWYBJD-P/2/d1bb80ffce780c45697f44001e20f672",
• abstract = "From a computation-theoretic standpoint, this paper formalises the notion of unpredictability in the efficient market hypothesis (EMH) by a biological-based search program, i.e., genetic programming (GP). This formalization differs from the traditional notion based on probabilistic independence in its treatment of search. Compared with the traditional notion, a GP-based search provides an explicit and efficient search program upon which an objective measure for predictability can be formalized in terms of search intensity and chance of success in the search. This will be illustrated by an example of applying GP to predict chaotic time series. Then the EMH based on this notion will be exemplified by an application to the Taiwan and US stock market. A short-term sample of TAIEX and S&P 500 with the highest complexity defined by Rissanen's minimum description length principle (MDLP) is chosen and tested. It is found that, while linear models cannot predict better than the random walk, a GP-based search can beat random walk by 50%. It, therefore, confirms the belief that while the short-term nonlinear regularities might still exist, the search costs of discovering them might be too high to make the exploitation of these regularities profitable, hence the efficient market hypothesis is sustained.",
• notes = "Society of Computational Economics Conference JEL classification codes: C63; G14",

}

Genetic Programming entries for Shu-Heng Chen Chia Hsuan Yeh

Citations