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Regime-switching recurrent reinforcement learning for investment decision making

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  • Dietmar Maringer
  • Tikesh Ramtohul

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  • Dietmar Maringer & Tikesh Ramtohul, 2012. "Regime-switching recurrent reinforcement learning for investment decision making," Computational Management Science, Springer, vol. 9(1), pages 89-107, February.
    • Handle: RePEc:spr:comgts:v:9:y:2012:i:1:p:89-107
    DOI: 10.1007/s10287-011-0131-1
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    References listed on IDEAS

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    1. Sentana, Enrique & Wadhwani, Sushil B, 1992. "Feedback Traders and Stock Return Autocorrelations: Evidence from a Century of Daily Data," Economic Journal, Royal Economic Society, vol. 102(411), pages 415-425, March.
    2. John Moody & Lizhong Wu, "undated". "Optimization of Trading Systems and Portfolios," Computing in Economics and Finance 1997 55, Society for Computational Economics.
    3. LeBaron, Blake, 1992. "Some Relations between Volatility and Serial Correlations in Stock Market Returns," The Journal of Business, University of Chicago Press, vol. 65(2), pages 199-219, April.
    4. Koutmos, Gregory, 1997. "Feedback trading and the autocorrelation pattern of stock returns: further empirical evidence," Journal of International Money and Finance, Elsevier, vol. 16(4), pages 625-636, August.
    5. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    6. Michael D. McKenzie & Robert W. Faff, 2003. "The Determinants of Conditional Autocorrelation in Stock Returns," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 26(2), pages 259-274, June.
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    Cited by:

    1. Wu, Bo & Li, Lingfei, 2024. "Reinforcement learning for continuous-time mean-variance portfolio selection in a regime-switching market," Journal of Economic Dynamics and Control, Elsevier, vol. 158(C).
    2. Jin Zhang & Dietmar Maringer, 2016. "Using a Genetic Algorithm to Improve Recurrent Reinforcement Learning for Equity Trading," Computational Economics, Springer;Society for Computational Economics, vol. 47(4), pages 551-567, April.
    3. L.-F. Pau, 2014. "Discovering the dynamics of smart business networks," Computational Management Science, Springer, vol. 11(4), pages 445-458, October.
    4. Xiangyu Cui & Xun Li & Yun Shi & Si Zhao, 2023. "Discrete-Time Mean-Variance Strategy Based on Reinforcement Learning," Papers 2312.15385, arXiv.org.

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