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.
In our studies discussed below, we populate our IABS with hundreds of simple agents, referred to as Zero Intelligence'' or ZI agents. The term agent was coined by @cite_4 to describe a family of automated market participants that submit random bid and ask orders. In this seminal work, two types of agents were considered: ZI-U (unconstrained) agents which place orders entirely at random within fixed extents, and ZI-C (constrained) agents which are prohibited from placing orders that result in an immediate loss. These ZI agents were initially used to demonstrate that the allocative efficiency of a market arises from its structure and not the particular strategy or intelligence of its participants, i.e., individual strategies are subsumed by the market as whole.
@cite_4
2018567859
We report market experiments in which human traders are replaced by "zero-intelligence" programs that submit random bids and offers. Imposing a budget constraint (i.e., not permitting traders to sell below their costs or buy above their values) is sufficient to raise the allocative efficiency of these auctions close to 100 percent. Allocative efficiency of a double auction derives largely from its structure, independent of traders' motivation, intelligence, or learning. Adam Smith's invisible hand may be more powerful than some may have thought; it can generate aggregate rationality not only from individual rationality but also from individual irrationality.