Noise traders in an agent-based artificial stock market
通过构建人工股票市场模拟模型，研究噪声交易者能否长期存活及其对市场的影响，发现噪声交易者长期无法存活或转变为其他类型交易者，且会加剧市场波动和价格扭曲。
Abstract This paper investigates whether noise traders can survive in the long run and how they influence financial markets by proposing an agent-based artificial stock market, as one simulation model of computational economics. This market contains noise traders, informed and uninformed traders. Informed and uninformed traders can learn from information by using Genetic Programming, while noise traders cannot. The system is first calibrated to real financial markets by replicating several stylized facts. We find that noise traders cannot survive or they just transform to other kind of traders in the long run, and they increase market volatility, price distortion, noise trader risk, and trading volume in the market. However, regulation intervention, e.g., price limits, transaction tax and longer settlement cycle, can affect noise trader’s surviving period and their influence on markets.