Transaction tax, heterogeneous traders and market volatility
Authored by Shouyang Wang, Hongquan Li, Gang Cheng
Date Published: 2015
DOI: 10.1108/k-10-2014-0223
Sponsors:
Chinese National Natural Science Foundation
Ministry of Education in China
Platforms:
MATLAB
Model Documentation:
Other Narrative
Mathematical description
Model Code URLs:
Model code not found
Abstract
Purpose - 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.
Design/methodology/approach - 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.
Findings - 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.
Originality/value - 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.
Tags
models
finance
Economics
Stock-market