Noise traders in an agent-based artificial stock market

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. market contains traders, informed uninformed traders. Informed learn from information using Genetic Programming, while cannot. The system is first calibrated to real replicating several stylized facts. We find that cannot or just transform other kind run, increase volatility, price distortion, trader risk, trading volume market. However, regulation intervention, e.g., limits, transaction tax longer settlement cycle, affect trader’s surviving period their on markets.