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Reverse Engineering Financial Markets with Majority and Minority Games Using Genetic Algorithms

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  • J. Wiesinger
  • D. Sornette
  • J. Satinover

Abstract

Using virtual stock markets with artificial interacting software investors, aka agent-based models, we present a method to reverse engineer real-world financial time series. We model financial markets as made of a large number of interacting boundedly rational agents. By optimizing the similarity between the actual data and that generated by the reconstructed virtual stock market, we obtain parameters and strategies, which reveal some of the inner workings of the target stock market. We validate our approach by out-of-sample predictions of directional moves of the Nasdaq Composite Index. Copyright Springer Science+Business Media, LLC. 2013

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  • J. Wiesinger & D. Sornette & J. Satinover, 2013. "Reverse Engineering Financial Markets with Majority and Minority Games Using Genetic Algorithms," Computational Economics, Springer;Society for Computational Economics, vol. 41(4), pages 475-492, April.
    • Handle: RePEc:kap:compec:v:41:y:2013:i:4:p:475-492
    DOI: 10.1007/s10614-011-9312-9
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    3. Li-Xin Zhong & Wen-Juan Xu & Ping Huang & Chen-Yang Zhong & Tian Qiu, 2013. "Self-organization and phase transition in financial markets with multiple choices," Papers 1312.0690, arXiv.org, revised Jun 2014.
    4. Wen-Juan Xu & Chen-Yang Zhong & Fei Ren & Tian Qiu & Rong-Da Chen & Yun-Xin He & Li-Xin Zhong, 2020. "Evolutionary dynamics in financial markets with heterogeneities in strategies and risk tolerance," Papers 2010.08962, arXiv.org.
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    6. Tai Vo-Van & Ha Che-Ngoc & Nghiep Le-Dai & Thao Nguyen-Trang, 2022. "A New Strategy for Short-Term Stock Investment Using Bayesian Approach," Computational Economics, Springer;Society for Computational Economics, vol. 59(2), pages 887-911, February.

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