Toward a computable approach to the efficient market hypothesis: An application of genetic programming
AbstractFrom a computation-theoretic standpoint, this paper formalizes 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. While search plays an important role in the EMH, tradtional notion does not formalize serach in a way such that it can be implemented, and it turns out that the EMH based on this notion is practically uncomputable. Compared with the traditional notion, a GP-based search provided 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 U.S. stock market. A short-term sample of TAIEX and S\&P 500 with the highest complexity defined by Rissanen's MDLP (Minimum Description Length Principle) 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 efficient market hypothesis can sustain from this perspective.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. 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.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by Elsevier in its journal Journal of Economic Dynamics and Control.
Volume (Year): 21 (1997)
Issue (Month): 6 (June)
Contact details of provider:
Web page: http://www.elsevier.com/locate/jedc
Other versions of this item:
- Shu-Heng Chen & Chia-Hsuan Yeh, . "Toward a Computable Approach to the Efficient Market Hypothesis: An Application of Genetic Programming," Working Papers _011, University of California at Los Angeles, Center for Computable Economics.
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.:
- Makridakis, Spyros, 1993. "Accuracy measures: theoretical and practical concerns," International Journal of Forecasting, Elsevier, vol. 9(4), pages 527-529, December.
- Scheinkman, Jose A & LeBaron, Blake, 1989. "Nonlinear Dynamics and Stock Returns," The Journal of Business, University of Chicago Press, vol. 62(3), pages 311-37, July.
- Diebold, Francis X. & Nason, James A., 1990.
"Nonparametric exchange rate prediction?,"
Journal of International Economics,
Elsevier, vol. 28(3-4), pages 315-332, May.
- Frank, Murray & Gencay, Ramazan & Stengos, Thanasis, 1988. "International chaos?," European Economic Review, Elsevier, vol. 32(8), pages 1569-1584, October.
- Savit, R., 1989. "Nonlinearities And Chaotic Effects In Options Prices," Papers 184, Columbia - Center for Futures Markets.
- Hsieh, David A, 1989. "Testing for Nonlinear Dependence in Daily Foreign Exchange Rates," The Journal of Business, University of Chicago Press, vol. 62(3), pages 339-68, July.
- Willey, Thomas, 1992. "Testing for nonlinear dependence in daily stock indices," Journal of Economics and Business, Elsevier, vol. 44(1), pages 63-76, February.
- repec:fth:guelph:1988-15 is not listed on IDEAS
- Hinich, Melvin J & Patterson, Douglas M, 1985. "Evidence of Nonlinearity in Daily Stock Returns," Journal of Business & Economic Statistics, American Statistical Association, vol. 3(1), pages 69-77, January.
- Xue-Zhong He & Youwei Li, 2008. "Heterogeneity, convergence, and autocorrelations," Quantitative Finance, Taylor & Francis Journals, vol. 8(1), pages 59-79.
- Kozhan, Roman & Salmon, Mark, 2012. "The information content of a limit order book: The case of an FX market," Journal of Financial Markets, Elsevier, vol. 15(1), pages 1-28.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.