Modelling stock correlations with expected returns from investors

TL;DR

This paper introduces a minority game-based agent model to explain stock correlations, showing how agents' expected returns influence positive or negative correlations, supported by simulations and analytical insights.

Contribution

It presents a novel microscopic agent-based model for stock correlations, incorporating expected returns influenced by historical returns, extending understanding beyond traditional approaches.

Findings

Stock returns are positively or negatively correlated based on agents' expected return correlations.

The model's results hold even with heterogeneous agent expectations and additional factors.

Numerical and analytical methods validate the correlation mechanisms.

Abstract

Stock correlations is crucial to asset pricing, investor decision-making, and financial risk regulations. However, microscopic explanation based on agent-based modeling is still lacking. We here propose a model derived from minority game for modeling stock correlations, in which an agent's expected return for one stock is influenced by the historical return of the other stock. Each agent makes a decision based on his expected return with reference to information dissemination and the historical return of the stock. We find that the returns of the stocks are positively (negatively) correlated when agents' expected returns for one stock are positively (negatively) correlated with the historical return of the other. We provide both numerical simulations and analytical studies and give explanations to stock correlations for cases with agents having either homogeneous or heterogeneous expected returns. The result still holds when other factors such as holding decisions and external events are included which broadens the practicability of the model.