Predicting Tesla Stock Return Using Twitter Data - An Intraday View on the Relation between Twitter Dimensions and the Tesla Stock Return
In this thesis, Twitter data is used to predict the intraday stock return for Tesla, Inc. We present two different methods to extract the tweets’ sentiment: A dictionary-based approach (VADER) and a machine learning approach (SVM). Additionally, we control for other dimensions as the user and discussion dimension. Then a Granger causality test and a lasso regression are conducted on a one- and fiv
