Implementation of an ITB-capable Double Auction Market Simulation Platform

Abstract

Research in the field of agent-based financial markets requires a significant amount of computer science knowledge in order to successfully build the complex simulations required. However, the researchers interested in the field vary across many different disciplines, including economists, financial engineers, statisticians, and mathematicians, who may not have this experience. This thesis serves to help bridge this gap by showing the process of developing an accurate, efficient, and modular double auction market simulation. In addition, this thesis analyzes certain properties of the double auction market models implemented in the simulation platform and runs a simple Integrated Test Bed (ITB) experiment that analyzes a market with humans and computational agents interacting together.