Impact of False Information from Spoofing Strategies: An ABM Model of Market Dynamics

Haohang Li, Steve Y. Yang

Abstract:

Spoofing has been identified a form of market
manipulation, and it is harmful to the stability of the financial
market. However, the effect of spoofing activity is hard to analyze
due to its complex interactions within the market and lack of
data. This paper presents an agent-based simulation model of
the continuous double auction market to replicate and analyze
the market dynamics under spoofing conditions. The simulated
market consists of fundamentalist, chartists, zero intelligence
agents, and spoofing agents where several existing market stylized
facts are validated. The results show that in the presence of
the spoofing agents and their market manipulation activities, the
market volatility would increase, and spoofing activities would
exacerbate the price variations. The fundamentalist agents would
suffer a loss during the spoofing period but would be able to make
profit during the price recovery phase. The chartist agents would
suffer a loss when the spoofing agent realized its profit and the
price recovery process start, at which they falsely believed the
price movement trend would continue. The Sharpe ratio analysis
also indicates the market manipulation activities of the spoofing
agent would give themselves an unfair advantage resulting in a
significantly higher Sharpe ratio than the other agents.