Researcher ORCID Identifier
https://orcid.org/0000-0002-4981-6102
Graduation Year
2023
Date of Submission
12-2022
Document Type
Open Access Senior Thesis
Degree Name
Bachelor of Arts
Department
Economics
Reader 1
Michael Gelman
Terms of Use & License Information
Rights Information
© 2022 Edward Z Wu
Abstract
This paper examines the effects of social media sentiment relating to Bitcoin on the daily price returns of Bitcoin and other popular cryptocurrencies by utilizing sentiment analysis and machine learning techniques to predict daily price returns. Many investors think that social media sentiment affects cryptocurrency prices. However, the results of this paper find that social media sentiment relating to Bitcoin does not add significant predictive value to forecasting daily price returns for each of the six cryptocurrencies used for analysis and that machine learning models that do not assume linearity between the current day price return and previous daily price returns combined with previous daily sentiment scores were more accurate than machine learning models that assume linearity.
Recommended Citation
Wu, Edward, "Application of Sentiment Analysis and Machine Learning Techniques to Predict Daily Cryptocurrency Price Returns" (2023). CMC Senior Theses. 3220.
https://scholarship.claremont.edu/cmc_theses/3220
Included in
Data Science Commons, Econometrics Commons, Finance Commons, Longitudinal Data Analysis and Time Series Commons, Statistical Models Commons
