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A computational view of market efficiency

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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.

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Bibliographic Info

Article provided by Taylor & Francis Journals in its journal Quantitative Finance.

Volume (Year): 11 (2011)
Issue (Month): 7 ()
Pages: 1043-1050

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Handle: RePEc:taf:quantf:v:11:y:2011:i:7:p:1043-1050

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Related research

Keywords: Agent based modelling; Bound rationality; Complexity in finance; Behavioral finance;

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References

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Cited by:
  1. D. Sornette, 2014. "Physics and Financial Economics (1776-2014): Puzzles, Ising and Agent-Based models," Papers 1404.0243, arXiv.org.

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