Analyzing the chaotic behavior of an ACO based artificial stock market

An evolution model based on the ant colony optimization algorithm for investment behavior in the stock market is formulated. The largest Lyapunov exponents of the stock price time series created from the model are calculated. The simulation results show that this model can not only create stock price trends rather similar to the real stock market, but also show the chaotic behavior like the real stock market. We observed that the more speculators among the investors the bigger the largest Lyapunov exponent and the stronger the chaotic behavior in stock markets.