Updated: Dec 22, 2021
We conducted simple linear regression and statistical analysis for the research question, 'How much does Elon Musk's number of tweets per day affect Tesla's stock price change?'. The R-squared in our model is 0.259, meaning that 25.9% of the variability in the response - stock price change is explained by the number of tweets through the linear regression model; in other words, the remaining 74.1% of the variability is due to characteristics that are not the number of tweets.
The predicted stock price change (%) equals 1.8928 plus 0.0704 times the number of tweets. If there is no tweeting, we would expect the stock price to have about 1.8928% change on average. For every one-unit increase in the number of tweets, we would predict that the stock price would change by 0.0704%. For example, if Elon tweets 20 times a day, it may trigger the stock price change about 1.8928 + 0.0704 x 20, or 3.30% on average in the 50-day moving average.
We also researched what a good R-squared value is. According to Investopedia, "What qualifies as a "good" R-Squared value will depend on the context. In some fields, such as the social sciences, even a relatively low R-Squared such as 0.5 could be considered relatively strong." Therefore, our R-squared analysis is worth considering because a person's tweeting trend is more closely related to the finance vs. social sciences than stock market indexes.