Strategic Agent-Based Modeling of Financial Markets

Understanding the implications of algorithmic trading calls for modeling financial markets at a level of fidelity that often precludes analytic solution. We describe how agent-based simulation modeling can be combined with game-theoretic reasoning to examine the effects of market variables on outcomes of interest. The approach is illustrated in a basic model where investors trade a single security through a continuous double auction mechanism. Our results demonstrate the feasibility of the approach, and raise questions about the use of spreads as a proxy for trading cost and welfare.