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Return predictability and the ‘wisdom of crowds’: Genetic Programming trading algorithms, the Marginal Trader Hypothesis and the Hayek Hypothesis

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  • Manahov, Viktor
  • Hudson, Robert
  • Hoque, Hafiz

Abstract

We develop profitable stock market forecasts for a number of financial instruments and portfolios using a special adaptive form of the Strongly Typed Genetic Programming (STGP)-based trading algorithm. The STGP-based trading algorithm produces one-day-ahead return forecasts for groups of artificial traders with different levels of intelligence and different group sizes. The performance of the algorithm is compared with a number of benchmark forecasts and these comparisons clearly demonstrate the short-term superiority of the STGP-based method in many circumstances. Subsequently we provide detailed analysis of the impact of trader cognitive abilities and trader numbers on the accuracy of forecasting rules which allows us to conduct new experimental tests of the Marginal Trader and the Hayek Hypotheses. We find little support for the Marginal Trader Hypothesis but some evidence for the Hayek Hypothesis.

Suggested Citation

  • Manahov, Viktor & Hudson, Robert & Hoque, Hafiz, 2015. "Return predictability and the ‘wisdom of crowds’: Genetic Programming trading algorithms, the Marginal Trader Hypothesis and the Hayek Hypothesis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 37(C), pages 85-98.
    • Handle: RePEc:eee:intfin:v:37:y:2015:i:c:p:85-98
    DOI: 10.1016/j.intfin.2015.02.009
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    2. Syeda Tayyaba Ijaz & Rabia Komal, 2015. "Role Of Hurst Exponent In Prediction Of Market Efficiency In Kse-100 Index," IBT Journal of Business Studies (JBS), Ilma University, Faculty of Management Science, vol. 11(2), pages 11-14.
    3. Andreas Karathanasopoulos, 2017. "Modelling and trading the London, New York and Frankfurt stock exchanges with a new gene expression programming trader tool," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 24(1), pages 3-11, January.
    4. Katsuya Ito & Kentaro Minami & Kentaro Imajo & Kei Nakagawa, 2020. "Trader-Company Method: A Metaheuristic for Interpretable Stock Price Prediction," Papers 2012.10215, arXiv.org.
    5. Mr. M. Awais Mehmood & Dr. Faisal Aftab & Dr. Hafiz Mushtaq, 2016. "Role Of Social Media Marketing (Smm) In Hei’S Admission," IBT Journal of Business Studies (JBS), Ilma University, Faculty of Management Science, vol. 12(1), pages 12-10.

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