High frequency trading strategies, market fragility and price spikes: an agent based model perspective

Abstract

Given recent requirements for ensuring the robustness of algorithmic trading strategies laid out in the Markets in Financial Instruments Directive II, this paper proposes a novel agent-based simulation for exploring algorithmic trading strategies. Five different types of agents are present in the market. The statistical properties of the simulated market are compared with equity market depth data from the Chi-X exchange and found to be significantly similar. The model is able to reproduce a number of stylised market properties including: clustered volatility, autocorrelation of returns, long memory in order flow, concave price impact and the presence of extreme price events. The results are found to be insensitive to reasonable parameter variations.