Transaction tax, heterogeneous traders and market volatility

The securities transaction tax (STT) has been theoretically considered as an important regulation device for decades. However, its role and effectiveness in financial markets is still not well understood both theoretically and empirically. By use of agent-based modeling method, the purpose of this paper is to present a new artificial stock market model with self-adaptive agents, which allows the assessment of the impacts from various levels of STTs in distinctive market environments and thus a comprehensive understanding of the effects of STTs is achieved.

In the model, agents are allowed to employ the strategies used by the following five types of investors: contrarians, random traders, momentum traders, fundamentalists and exit strategy holders. Specifically, the authors start with the investigation of the dynamics of a tax free benchmark market; then the patterns of market behaviors and the behaviors of various types of investors are discussed with different levels of STTs in markets with mild and high fluctuations.

The simulation results consistently show that a moderate transaction tax does contribute to market stabilization in terms of reducing market volatility while with a price of mild decrease of market efficiency and liquidity. The findings suggest that a balance between market stability and efficiency could be reached if regulatory authorities introduce STTs to markets discreetly.

This paper enriches the comprehensive understanding of the effects of STT, and gives good explanation about the controversy between Tobin’s proponents and anti-Tobin group.