Description
In this paper I defend the argument that public reaction to news headlines correlates with the short-term price direction of Bitcoin. I collected a month's worth of Bitcoin data consisting of news headlines, tweets, and the price of the cryptocurrency. I fed this data into a Long Short-Term Memory Neural Network and built a model that predicted Bitcoin price for a new timeframe. The model correctly predicted 75% of test set price trends on 3.25 hour time intervals. This is higher than the 53.57% accuracy tested with a Bitcoin price model without sentiment data. I concluded public reaction to Bitcoin news headlines has an effect on the short-term price direction of the cryptocurrency. Investors can use my model to help them in their decision-making process when making short-term Bitcoin investment decisions.
Included in this item (2)
Permanent Link
Permanent Link
Permanent Link
Details
Title
- Predicting Bitcoin Price Trend using Sentiment Analysis
Contributors
Agent
- Steinberg, Sam (Author)
- Boscovic, Dragan (Thesis director)
- Davulcu, Hasan (Committee member)
- Computer Science and Engineering Program (Contributor)
- Barrett, The Honors College (Contributor)
Date Created
The date the item was original created (prior to any relationship with the ASU Digital Repositories.)
2020-05
Collections this item is in