Modeling market fluctuations under investor sentiment with a Hawkes-Contact process

Abstract

We present a new Hawkes-Contact model that combines a Hawkes process and a finite-range contact process to model the stock price movements, especially under the impact of news and other information flows that could lead to contagious effects. To fully capture the underlying price process, we take the Hawkes process to track the full pathway of historical prices on their future movements and the contact process to capture the impact from news/investment sentiment. We compare this full model to a univariate Hawkes process that works as a benchmark model through analyzing their statistical properties using both simulated returns and the real 5-min returns of the crude oil index (Wind CZCE-TA). The statistical properties include probability density function, complementary cumulative distribution function, and Lempel-Ziv Complex. Our results show that the real returns' distribution is often far from normal, but the simulated returns through the Hawkes or Hawke-Contact model can achieve close fit to the real returns and exhibit similar statistical properties. More importantly, the Hawkes-Contact model performs better than the simple Hawkes model in capturing characteristics in the return movements, which indicates that the price evolution is also driven by the news sentiment created after them.