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Cowboying Stock Market Herds with Robot Traders

Author

Listed:
  • Jaqueson K. Galimberti

    (ETH Zurich)

  • Nicolas Suhadolnik

    (BRDE Regional Development Bank of the Extreme South)

  • Sergio Silva

    (Federal University of Santa Catarina)

Abstract

One explanation for large stock market fluctuations is its tendency to herd behavior. We put forward an agent-based model where instabilities are the result of liquidity imbalances amplified by local interactions through imitation, and calibrate the model to match some key statistics of actual daily returns. We show that an “aggregate market-maker” type of liquidity injection is not successful in stabilizing prices due to the complex nature of the stock market. To offset liquidity shortages, we propose the use of locally triggered contrarian rules, and show that these mechanisms are effective in preventing extreme returns in our artificial stock market.

Suggested Citation

  • Jaqueson K. Galimberti & Nicolas Suhadolnik & Sergio Silva, 2017. "Cowboying Stock Market Herds with Robot Traders," Computational Economics, Springer;Society for Computational Economics, vol. 50(3), pages 393-423, October.
    • Handle: RePEc:kap:compec:v:50:y:2017:i:3:d:10.1007_s10614-016-9591-2
    DOI: 10.1007/s10614-016-9591-2
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    More about this item

    Keywords

    Herding; Robot trading; Financial regulation; Agent-based model;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • G02 - Financial Economics - - General - - - Behavioral Finance: Underlying Principles

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