Explaining Agent-Based Financial Market Simulation

Understand

This paper is intended to explain, in simple terms, some of the mechanisms and agents common to multiagent financial market simulations.

• We first discuss the necessity to include an exogenous price time series ("the fundamental value") for each asset and three methods for generating that series.
• We then illustrate one process by which a Bayesian agent may receive limited observations of the fundamental series and estimate its current and future values.
• Finally, we present two such agents widely examined in the literature, the Zero Intelligence agent and the Heuristic Belief Learning agent, which implement different approaches to order placement.