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A Computational View of Market Efficiency Author info | Abstract | Publisher info | Download info | Related research | Statistics Jasmina Hasanhodzic
Andrew W. Lo
Emanuele Viola
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We propose to study market efficiency from a computational viewpoint. Borrowing from theoretical computer science, we define a market to be \emph{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 bubbles 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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Paper provided by arXiv.org in its series Quantitative Finance Papers with number
0908.4580.
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Date of creation: Aug 2009Date of revision:
Handle: RePEc:arx:papers:0908.4580Contact details of provider: Web page: http://arxiv.org/
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