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.