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A computational view of market efficiency

Author

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  • Jasmina Hasanhodzic
  • Andrew Lo
  • Emanuele Viola

Abstract

We study market efficiency from a computational viewpoint. Borrowing from theoretical computer science, we define a market to be efficient with respect to resources S (e.g., time, memory) if no strategy using resources S can make a profit. As a first step, we consider memory-m strategies whose action at time t depends only on the m previous observations at times t - m, … , t - 1. We introduce and study a simple model of market evolution, where strategies impact the market by their decision to buy or sell. We show that the effect of optimal strategies using memory m can lead to 'market conditions' that were not present initially, such as (1) market spikes and (2) the possibility for a strategy using memory m' > m to make a bigger profit than was initially possible. We suggest ours as a framework to rationalize the technological arms race of quantitative trading firms.

Suggested Citation

  • Jasmina Hasanhodzic & Andrew Lo & Emanuele Viola, 2011. "A computational view of market efficiency," Quantitative Finance, Taylor & Francis Journals, vol. 11(7), pages 1043-1050.
    • Handle: RePEc:taf:quantf:v:11:y:2011:i:7:p:1043-1050
    DOI: 10.1080/14697688.2010.541487
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    3. Brender, Nathalie & Markov, Iliya, 2013. "Risk perception and risk management in cloud computing: Results from a case study of Swiss companies," International Journal of Information Management, Elsevier, vol. 33(5), pages 726-733.
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