Analysis of Contagion in China's Stock Market: A Hawkes Process Perspective

TL;DR

This paper uses Hawkes processes to analyze contagion, autocorrelation, and sector influence in China's stock market, revealing how market activity levels affect trend persistence and sector rotation.

Contribution

It introduces a novel application of spatiotemporal Hawkes processes to model and understand contagion and sector dynamics in Chinese stock markets.

Findings

High trading activity sustains sector trends.

Low activity periods show strong sector rotation.

Long-term dependencies and trending patterns are identified.

Abstract

This study explores contagion in the Chinese stock market using Hawkes processes to analyze autocorrelation and cross-correlation in multivariate time series data. We examine whether market indices exhibit trending behavior and whether sector indices influence one another. By fitting self-exciting and inhibitory Hawkes processes to daily returns of indices like the Shanghai Composite, Shenzhen Component, and ChiNext, as well as sector indices (CSI Consumer, Healthcare, and Financial), we identify long-term dependencies and trending patterns, including upward, downward, and oversold rebound trends. Results show that during high trading activity, sector indices tend to sustain their trends, while low activity periods exhibit strong sector rotation. This research models stock price movements using spatiotemporal Hawkes processes, leveraging conditional intensity functions to explain sector rotation, advancing the understanding of financial contagion.