Multi-assets artificial stock market with heterogeneous interacting agents

In this paper, an information-based multi-assets arti¯cial stock market is presented. The market is populated by heterogeneous agents that are seen as nodes of sparsely connected graphs. The market is characterized by di®erent types of stocks and agents trade risky assets in exchange for cash. Beside the amount of cash and of stocks owned, each agent is characterized by sentiments. Moreover, agents share their sentiments by means of interactions that are determined by graphs. A central market maker (clearing house mechanism) determines the price processes for each stock at the intersection of the demand and the supply curves. Within this frame- work, stock price processes exhibit volatility clustering and fat-tailed distribution of returns. Moreover, the cross-correlations between returns of di®erent stocks is studied using methods of random matrix theory. The probability distribution of eigenvalues of the cross-correlation matrix shows the presence of outliers, similar to those recently observed on real data for business sectors. These results suggest a signi¯cant structural in°uence on statistical properties of multi-assets stock market.