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Active and Passive Learning in Agent-based Financial Markets

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  • Blake LeBaron

    (International Business School, Brandeis University, 415 South Street, Mailstop 32, Waltham, MA 02453 – 2728, USA. Website: www.brandeis.edu/~blebaron)

Abstract

This short note compares and contrasts two forms of learning which are present in most agent-based financial markets. First, passive learning refers to a form of “as if rationality” where wealth accumulates on strategies which have done relatively well. Second active learning refers to the active switching of agents across strategies. Most heterogeneous agent markets contain some form of both these types of learning. From what we know so far the dynamics of each may be quite different, and may yield a rich and complex joint dynamic.

Suggested Citation

  • Blake LeBaron, 2011. "Active and Passive Learning in Agent-based Financial Markets," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 37(1), pages 35-43.
  • Handle: RePEc:pal:easeco:v:37:y:2011:i:1:p:35-43
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    References listed on IDEAS

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    Cited by:

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    3. Palczewski, Jan & Schenk-Hoppé, Klaus Reiner & Wang, Tongya, 2016. "Itchy feet vs cool heads: Flow of funds in an agent-based financial market," Journal of Economic Dynamics and Control, Elsevier, vol. 63(C), pages 53-68.
    4. Henry Okwo & Charity Ezenwakwelu & Anthony Igwe & Benedict Imhanrenialena, 2019. "Firm Size and Age mediating the Firm Survival-Hedging Effect: Hayes’ 3-Way Parallel Approach," Sustainability, MDPI, vol. 11(3), pages 1-17, February.
    5. Schmitt, Noemi & Westerhoff, Frank, 2021. "Trend followers, contrarians and fundamentalists: Explaining the dynamics of financial markets," Journal of Economic Behavior & Organization, Elsevier, vol. 192(C), pages 117-136.
    6. Colin M. Van Oort & Ethan Ratliff-Crain & Brian F. Tivnan & Safwan Wshah, 2023. "Adaptive Agents and Data Quality in Agent-Based Financial Markets," Papers 2311.15974, arXiv.org.
    7. Marcin Hernes & Jadwiga Sobieska-Karpińska, 2016. "Application of the consensus method in a multiagent financial decision support system," Information Systems and e-Business Management, Springer, vol. 14(1), pages 167-185, February.
    8. Roberto Dieci & Xue-Zhong He, 2018. "Heterogeneous Agent Models in Finance," Research Paper Series 389, Quantitative Finance Research Centre, University of Technology, Sydney.
    9. Kalugala Vidanalage Aruna Shantha, 2019. "Individual Investors’ Learning Behavior and Its Impact on Their Herd Bias: An Integrated Analysis in the Context of Stock Trading," Sustainability, MDPI, vol. 11(5), pages 1-24, March.
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    11. David Byrd & Sruthi Palaparthi & Maria Hybinette & Tucker Hybinette Balch, 2020. "The Importance of Low Latency to Order Book Imbalance Trading Strategies," Papers 2006.08682, arXiv.org.

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