A model for correlations in stock markets

TL;DR

This paper introduces a group-based model to explain the correlation structures observed in stock market data, linking spectral properties of correlation matrices to market groupings.

Contribution

It presents a novel group model that accounts for correlations in stock markets and explains spectral properties of empirical correlation matrices.

Findings

Spectral properties of empirical correlation matrices are consistent with the model.

The model connects correlation matrix spectra to market group structures.

Provides insights into the organization of stock market correlations.

Abstract

We propose a group model for correlations in stock markets. In the group model the markets are composed of several groups, within which the stock price fluctuations are correlated. The spectral properties of empirical correlation matrices reported in [Phys. Rev. Lett. {\bf 83}, 1467 (1999); Phys. Rev. Lett. {\bf 83}, 1471 (1999.)] are well understood from the model. It provides the connection between the spectral properties of the empirical correlation matrix and the structure of correlations in stock markets.