Understanding investors behaviors during the COVID-19 outbreak using Twitter sentiment analysis
(1) Heritage Woods Secondary School, (2) Yale Universityhttps://doi.org/10.59720/23-038
The COVID-19 pandemic caused stock price volatility and a market crash in 2020. Such events were an opportunity to gain insights into investor psychology. We sought to examine investors behaviors during the COVID-19 outbreak by analyzing the correlation between COVID-19-related tweet sentiment and stock price movements. The analysis was done at three levels: the stock market, the industry sector, and individual company stocks. We hypothesized that the investors would initially underestimate the health risk associated with the pandemic, but as time progressed, acknowledge the health risk and start panic selling. By analyzing the correlation between tweet sentiment and stock prices, we discovered that after the World Health Organization (WHO) declared the outbreak a Public Health Emergency of International Concern (PHEIC), investors displayed a tendency to disregard the health risk, coinciding with an increase in stock prices. However, the U.S. Centers for Disease Control and Prevention (CDC) warning and the pandemic declaration coincided with a period during which investors may have displayed a sense of apprehension, with the stock prices declining at the same time. To validate the sentiment analysis results, we also identified the most-used words in tweets and analyzed the correlation between tweet features and stock prices. Our work showed that, along with economic variables, behavioral factors like investor sentiment help explain the market’s behavior. Our work also highlighted the value of using a mixed methods approach to study complex processes in the real world.
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