How does news sentiment affect the states of Japanese stock return volatility?

Lingbing Feng, Tong Fu, Yanlin Shi

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

This paper examines the impact of public news sentiment on the volatility states of firm-level returns on the Japanese Stock market. We firstly adopt a novel Markov Regime Switching Long Memory GARCH (MRS-LMGARCH), which is employed to estimate the latent volatility states of intraday stock return. By using the RavenPack Dow Jones News Analytics database, we fit discrete choice models to investigate the impact of news sentiment on changes of volatility states of the constituent stocks in the TOPIX Core 30 Index. Our findings suggest that news occurrence and sentiment, especially those of macro-economic news, are a key factor that significantly drives the volatility state of Japanese stock returns. This provides essential information for traders of the Japanese stock market to optimize their trading strategies and risk management plans to combat volatility.
Original languageEnglish
Article number102267
Pages (from-to)1-11
Number of pages11
JournalInternational Review of Financial Analysis
Volume84
Early online date25 Oct 2022
DOIs
Publication statusPublished - Nov 2022

Keywords

  • Public information arrival
  • Asset volatility
  • Japanese stock market
  • News sentiment
  • Regime-switching
  • Multinomial model

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