Efficient Calibration of a Financial Agent-Based Model Using the Method of Simulated Moments

Abstract

We propose a new efficient method of calibrating agent-based models using the Method of Simulated Moments. It utilizes the Filtered Neighborhoods optimization algorithm, gradually narrowing down the search area by examining local neighborhoods of promising solutions. The new method obtains better calibration accuracy for a benchmark financial agent-based model in comparison to a broad selection of other methods, while using just a tiny fraction of their computational budget.