Exogenous and endogenous factors affecting stock market transactions: A Hawkes process analysis of the Tokyo Stock Exchange during the COVID-19 pandemic

PLoS One. 2024 Apr 17;19(4):e0301462. doi: 10.1371/journal.pone.0301462. eCollection 2024.

Abstract

Transactions in financial markets are not evenly spaced but can be concentrated within a short period of time. In this study, we investigated the factors that determine the transaction frequency in financial markets. Specifically, we employed the Hawkes process model to identify exogenous and endogenous forces governing transactions of individual stocks in the Tokyo Stock Exchange during the COVID-19 pandemic. To enhance the accuracy of our analysis, we introduced a novel EM algorithm for the estimation of exogenous and endogenous factors that specifically addresses the interdependence of the values of these factors over time. We detected a substantial change in the transaction frequency in response to policy change announcements. Moreover, there is significant heterogeneity in the transaction frequency among individual stocks. We also found a tendency where stocks with high market capitalization tend to significantly respond to external news, while their excitation relationship between transactions is weak. This suggests the capability of quantifying the market state from the viewpoint of the exogenous and endogenous factors generating transactions for various stocks.

MeSH terms

  • Algorithms
  • COVID-19*
  • Humans
  • Pandemics
  • Policy
  • Tokyo

Grants and funding

This work was supported by Project Fund for Center for Social Complex Systems, Institute of Industrial Science, the University of Tokyo (https://www.iis.u-tokyo.ac.jp/en/) (Y.H.), and partially supported by JSPS KAKENHI (https://www.jsps.go.jp/english/e-grants/index.html) Grant Numbers JP22H01719 (T.O. and M.I.I.), JP23K17005 (M.I.I.), JP20H05921 (K.A.), JST Moonshot R&D (https://www.jst.go.jp/moonshot/en/) Grant Number JPMJMS2021 (K.A.), AMED (https://www.amed.go.jp/en/index.html) under Grant Number JP22dm0307009 (K.A.) and Institute of AI and Beyond of UTokyo (https://beyondai.jp/?lang=en) (K.A.). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.