A heterogeneous artificial stock market model can benefit people against another financial crisis

Abstract

This paper presents results of an artificial stock market and tries to make it more consistent with the statistical features of real stock data. Based on the SFI-ASM, a novel model is proposed to make agents more close to the real world. Agents are divided into four kinds in terms of different learning speeds, strategy-sizes, utility functions, and level of intelligence; and a crucial parameter has been found to ensure system stability. So, some parameters are appended to make the model which contains zero-intelligent and less-intelligent agents run steadily. Moreover, considering real stock markets change violently due to the financial crisis; the real stock markets are divided into two segments, before the financial crisis and after it. The optimal modified model before the financial crisis fails to replicate the statistical features of the real market after the financial crisis. Then, the optimal model after the financial crisis is shown. The experiments indicate that the optimal model after the financial crisis is able to replicate several of real market phenomena, including the first-order autocorrelation, kurtosis, standard deviation of yield series and first-order autocorrelation of yield square. We point out that there is a structural change in stock markets after the financial crisis, which can benefit people forecast the financial crisis.

Investor Behavior and Risk Contagion in an Information-Based Artificial Stock Market

“…Because agents can buy and sell stocks in the stock market, the time series of stock price reflects the dynamic behavioral characteristics of agents [43][44]. In recent years, many scholars have built artificial stock market models to study investor behavior and risk contagion, such as Duarte et al [45], Wu and Duan [46], Bertella et al [47], Krichene and Elaroui [48], Tsao and Huang [49], Yang and Chen [50], and Prates et al [51].…”