Name
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. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1080/14697688.2010.541487 | QUANTITATIVE FINANCE |
Keywords | DocType | Volume |
Agent based modelling,Bound rationality,Complexity in finance,Behavioral finance | Journal | 11 |
Issue | ISSN | Citations |
7 | 1469-7688 | 0 |
PageRank | References | Authors |
0.34 | 1 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jasmina Hasanhodzic | 1 | 1 | 0.72 |
| Andrew W. Lo | 2 | 68 | 33.01 |
| Emanuele Viola | 3 | 588 | 44.78 |