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https://doi.org/10.1016/0304-4076(91)90078-R

has been cited by the following article:

• TITLE: Using TGARCH-M to Model the Impact of Good News and Bad News on Covid-19 Related Stocks’ Volatilities

  AUTHORS: Junqi Chen, Hui Li, Yan Lv

  KEYWORDS: TGARCH, GARCH-M, TGARCH-M, Volatility, Sentiment Analysis

  JOURNAL NAME: Journal of Financial Risk Management, Vol.11 No.2, June 30, 2022

  ABSTRACT: In this paper, we investigate the dynamic relationship between Twitter sentiment related to vaccines and Covid-19 and the volatility of pharmaceutical stock returns. The first step is to construct a time-series Twitter sentiment index by considering the positive, negative, and neutral sentiment of tweets. A TGARCH-M model was then constructed to correlate the stock returns of five pharmaceutical companies with the Twitter sentiment. The results show that Twitter sentiment responds to stock price volatility in the market, especially in three companies, BioTech, Novovax, and Moderna. The relationship between the volatility of the stock returns of the three companies and Twitter sentiment was significant. Stock returns are negatively correlated with their volatility, with an increase in expected risk in the market leading to a corresponding decrease in returns. Positive sentiment is more likely to produce large swings in returns than negative sentiment.