Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Modelling market fluctuations under investor sentiment with a Hawkes-contact process

Zhang, Junhuan, Wen, Jiaqi and Chen, Jing ORCID: 2023. Modelling market fluctuations under investor sentiment with a Hawkes-contact process. The European Journal of Finance 29 (1) , pp. 17-32. 10.1080/1351847X.2021.1957699

[thumbnail of sub-Hawkes-20210201-Zhang-9-nore.pdf]
PDF - Accepted Post-Print Version
Available under License Creative Commons Attribution Non-commercial.

Download (3MB) | Preview


We present a new Hawkes-Contact model that combines a Hawkes process and a finite range contact process in order 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 five-minute returns of the crude oil index (Wind CZCE- TA). The statistical properties include probability density function (PDF), complementary cumulative distribution function (CCDF), Lempel-Ziv Complex (LZC). 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 announcements and sentiment created after them.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Mathematics
Subjects: H Social Sciences > HG Finance
Q Science > QA Mathematics
Publisher: Taylor & Francis
ISSN: 1351-847X
Funders: National Natural Science Foundation of China (grant number 71801008), Beihang University (grant numbers KG12113201, ZF202S1876)
Date of First Compliant Deposit: 25 May 2021
Date of Acceptance: 24 May 2021
Last Modified: 06 Feb 2024 16:24

Citation Data

Cited 2 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item


Downloads per month over past year

View more statistics