Exploring market making strategy for high frequency trading: An agent-based approach

Abstract

This paper utilizes agent-based simulation to explore market making strategy for high frequency traders (HFTs) and tests its performance under competition environments. After proposing a model representing HFTs’ activities in financial market when they act as market makers, we carry out simulations to explore how order price and order quantity affect HFTs’ profits and risks. As the result, we find that offering prices around last trading price, as well as taking advantage of order imbalance, increases HFTs’ returns. On the other hand, our results show utilizing adaptive order size based on previous order execution rate and setting a net threshold based on average trading volume helps to control the risks of end-of-day inventory. In addition, we introduce the competition environments of increased competitors and decreased latency, so as to see how these factors affect the performance of market making strategy.