The Downfall of Netflix: Using COVID-19 Cases and Vaccination Data to Predict Netflix’s Stock Price
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This project explores the trend in stock prices of Netflix, COVID-19 case data, and vaccination data from 2019 to 2022. I used Python in order to plot the trends in each of the categories described above and compare them to each other to discover if there is any correlation between them. After discovering that there were, I decided to code a linear regression model to predict Netflix's stock prices given COVID cases and vaccination data. In a linear regression model, there are two variables: an input (x) and an output (y). When evaluating each individually, Netflix's stock price rose as vaccination data and COVID cases increased. After discovering this trend, I decided to combine both factors in a multiple linear regression model. This model is similar to linear regression, except it uses two input values, COVID cases and the vaccination data, to predict an output of Netflix's stock price. To make sure the model works, I split my data into testing and training data. Using the training data for the input values, the model predicted a value that I could compare to that in the testing data. For example, the model predicted a value of $602.4 compared to $546.7, which gives a 10 percent error. The model is decent given that I only used two factors, COVID data and vaccination data, to predict Netflix's stock price. Exploring these trends also explained many misconceptions that people have of COVID. Lockdown restrictions being lifted didn't correlate with the spike in COVID cases in 2022, prompting some of the trends I saw on the graphs to be a bit surprising.
My mentor has been helpful when it comes to conceptualizing the project and also with the coding aspect of it.