Name
Title | ||
|---|---|---|
How to Evaluate Trading Strategies: Single Agent Market Replay or Multiple Agent Interactive Simulation? |
Abstract | ||
|---|---|---|
We show how a multi-agent simulator can support two important but distinct methods for assessing a trading strategy: Market Replay and Interactive Agent-Based Simulation (IABS). Our solution is important because each method offers strengths and weaknesses that expose or conceal flaws in the subject strategy. A key weakness of Market Replay is that the simulated market does not substantially adapt to or respond to the presence of the experimental strategy. IABS methods provide an artificial market for the experimental strategy using a population of background trading agents. Because the background agents attend to market conditions and current price as part of their strategy, the overall market is responsive to the presence of the experimental strategy. Even so, IABS methods have their own weaknesses, primarily that it is unclear if the market environment they provide is realistic. We describe our approach in detail, and illustrate its use in an example application: The evaluation of market impact for various size orders. |
Year | Venue | DocType |
|---|---|---|
2019 | CoRR | Journal |
Volume | ISSN | Citations |
abs/1906.12010 | Presented at the 2019 ICML Workshop on AI in Finance: Applications
and Infrastructure for Multi-Agent Learning. Long Beach, CA | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tucker R. Balch | 1 | 3163 | 429.41 |
| Mahmoud Mahfouz | 2 | 0 | 1.35 |
| Joshua Lockhart | 3 | 0 | 1.69 |
| Maria Hybinette | 4 | 459 | 41.13 |
| David Byrd | 5 | 6 | 2.48 |