Computational Models of Algorithmic Trading in Financial Markets

In today’s financial markets, algorithmic trading, the use of quantitative algorithms to automate the submission of orders, is responsible for the majority of trading activity. To better understand the societal implications of algorithmic trading, I construct computational agent-based models comprised of investors and algorithmic traders. I examine two overlapping types of algorithmic traders: high-frequency traders, who exploit speed advantages for profit, and market makers, who facilitate trade and supply liquidity by simultaneously maintaining offers to buy and sell. I employ simulation and empirical game-theoretic analysis to study trader behavior in equilibrium, that is, when all traders bestrespond to their environment and other agents’ strategies. I focus on the impact of algorithmic trading on allocative efficiency, or overall gains from trade, and the potential for a call market, in which orders are matched to trade at periodic intervals, to mitigate the latency advant...

• Type: Journal
• Year: 2015
• Where: ATAL
• Authors: Elaine Wah
• Keywords: ATAL 2015, Intelligent Agents