Memory effect and multifractality of cross-correlations in financial markets

TL;DR

This paper investigates the memory effects and multifractal properties of cross-correlations in American and Chinese stock markets, revealing long-range correlations and multifractality in their interactions over various time scales.

Contribution

It introduces an average instantaneous cross-correlation function and applies multifractal analysis to uncover complex temporal structures in market interactions.

Findings

Long-range time-correlations persist up to a month.

Multifractal characteristics are present in cross-correlations.

Memory effects vary with different price return intervals.

Abstract

An average instantaneous cross-correlation function is introduced to quantify the interaction of the financial market of a specific time. Based on the daily data of the American and Chinese stock markets, memory effect of the average instantaneous cross-correlations is investigated over different price return time intervals. Long-range time-correlations are revealed, and are found to persist up to a month-order magnitude of the price return time interval. Multifractal nature is investigated by a multifractal detrended fluctuation analysis.