An intriguing new paper, A computational view of Market Efficiency by Jasmina Hasanhodzic, Andrew W. Lo, and Emanuele Viola has just been uploaded to the arXiv.
We propose to study market efficiency from a computational viewpoint. Borrowing from theoretical computer science, we define a market to be efficient with respect to resources (e.g., time, memory) if no strategy using resources can make a profit. As a first step, we consider memory- strategies whose action at time depends only on the previous observations at times . 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 can lead to “market conditions” that were not present initially, such as (1) market bubbles and (2) the possibility for a strategy using memory 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.