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Be Wary of Black-Box Trading Algorithms

Author

Listed:
  • Smith, Gary

    (Pomona College)

Abstract

Black-box algorithms now account for nearly a third of all U. S. stock trades. It is a mistake to think that these algorithms possess superhuman intelligence. In reality, computers do not have the common sense and wisdom that humans have accumulated by living. Trading algorithms are particularly dangerous because they are so efficient at discovering statistical patterns—but so utterly useless in judging whether the discovered patterns are meaningful.

Suggested Citation

  • Smith, Gary, 2019. "Be Wary of Black-Box Trading Algorithms," Economics Department, Working Paper Series 1007, Economics Department, Pomona College, revised 04 Jun 2019.
    • Handle: RePEc:clm:pomwps:1007
    as

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    File URL: https://scholarship.claremont.edu/cgi/viewcontent.cgi?article=1007&context=pomona_fac_econ
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    References listed on IDEAS

    as
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    2. Michael J. Cooper & Orlin Dimitrov & P. Raghavendra Rau, 2001. "A Rose.com by Any Other Name," Journal of Finance, American Finance Association, vol. 56(6), pages 2371-2388, December.
    3. Krueger, Thomas M & Kennedy, William F, 1990. "An Examination of the Super Bowl Stock Market Predictor," Journal of Finance, American Finance Association, vol. 45(2), pages 691-697, June.
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    Cited by:

    1. Downen, Tom & Kim, Sarah & Lee, Lorraine, 2024. "Algorithm aversion, emotions, and investor reaction: Does disclosing the use of AI influence investment decisions?," International Journal of Accounting Information Systems, Elsevier, vol. 52(C).

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    Keywords

    algorithmic trading; black box trading; quants; artificial intelligence;
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