Delayed Majority Game with Heterogeneous Learning Speeds for Financial Markets

Abstract

There are two famous statistical laws, so-called stylized facts, in financial markets. One is fat tail where the tail of price returns obeys a power law. The other is volatility clustering in which the autocorrelation function of absolute price returns decays with a power law. In order to understand relationships between the stylized facts and dealers' behaviors, we constructed a new agent-based model based on the grand canonical minority game (GCMG) and the Giardina-Bouchaud (GB) model. The recovery of stylized facts by GCMG and GB lacks of robustness. Therefore, based on the GCMG and GB model, we develop a new model that can reproduce stylized facts robustly. Furthermore, we find that heterogeneity of learning speeds of agents is important to reproduce the stylized facts.