Digital Sentiment Analysis for Quantitative Bitcoin Trading

Abstract

The Bitcoin market is defined by extreme price swings, often driven by investor sentiment rather than clear fundamentals. Standard quantitative trading strategies struggle in this environment. While many studies confirm a link between social media mood and Bitcoin's price, a gap exists in developing and testing practical trading models based on this data . This thesis aims to close that gap by building and evaluating such a strategy to determine if it can deliver superior risk-adjusted returns.