COVID-19 Sentiments and Impact on Stock Market Prices
| Autor: | Krishna Devulapalli, Lakshmi Prayaga, Chandra Prayaga, Aaron Wade |
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| Rok vydání: | 2021 |
| Předmět: | |
| Zdroj: | International Journal of Data Analytics. 2:40-58 |
| ISSN: | 2644-1713 2644-1705 |
| DOI: | 10.4018/ijda.2021070103 |
| Popis: | This paper studies the impact of sentiments expressed by tweets from Twitter on the stock market associated with COVID-19 during the critical period from December 1, 2019 to May 31, 2020. The stock prices of 30 companies on the Dow Jones Index were collected for this period. Twitter tweets were also collected, using the search phrases “COVID-19” and “Corona Virus” for the same period, and their sentiment scores were calculated. The three time series, open and close stock values, and the corresponding sentiment scores from tweets were sorted by date and combined. Multivariate time series models based on vector error correction (VEC) models were applied to this data. Forecasts for these 30 companies were made for the time series open, for the 30 days of June 2020, following the data collection period. Stock market data for the month of June was for all the companies was compared with the forecast from the model. These were found to be in excellent agreement, implying that sentiment had a significant impact or was significantly impacted by the stock market prices. |
| Databáze: | OpenAIRE |
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