Forecasting stock volatility during the stock market crash period: The role of Hawkes process

Lina Fan, Hao Yang, Jia Zhai, Xiaotao Zhang*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

We use a heterogeneous autoregressive model with Hawkes process (HAR-RV-H) to forecast the volatility of 300 major individual stocks in the Chinese stock market during the 2015 market crash period. The Hawkes intensity process is calculated with the tick-by-tick data of individual stocks. We show that the Hawkes indicator has predictive power for most individual stocks in the market crash period. We compare the in- and out-of-sample forecast results for the HAR type models and conclude that the Hawkes indicator can improve both in- and out-of-sample forecasting abilities.

Original languageEnglish
Article number103839
JournalFinance Research Letters
Volume55
DOIs
Publication statusPublished - Jul 2023

Keywords

  • Forecast
  • HAR model
  • Hawkes process
  • Realized volatility

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