Description

Using high-frequency data from 2017 to 2021 and tweets from nine influential accounts, the course explains how cutting-edge natural language processing (NLP) techniques are used to classify tweet sentiment and analyze its effect on log returns, liquidity, and price jumps for Bitcoin, Ether, Litecoin, and Ripple. The course emphasizes methodological innovation (multi-model sentiment analysis), empirical findings (bidirectional sentiment-market link), and implications for market efficiency in crypto markets.

Participants will gain:

• Insights into the role of sentiment in financial markets,

• Exposure to modern NLP methods in financial applications,

• A clear view of how intraday crypto market features respond to tweet-based sentiment signals