The Evolution of Semantics and its Effect on Asset Prices - Matoušek, Martin; Fičura, Milan; Vyletelka, Michal; Vysoká škola ekonomická v Praze. Fakulta financí a účetnictví (2021)
Advances in natural language processing culminated in the advent of language models based on transformers that surpass even humans in certain language benchmarking tasks. Their domain-specific derivatives show promising results also when applied to financial texts. But research in this domain is sparse. Prior research works with former models, simple features and open-source data. This thesis proposes an approach of applying a language model on a large-scale custom-made dataset of financial news articles. This approach combines progress in machine learning, natural language processing and model interpretability to help better understand and estimate the effect of investor sentiment with regards to stock price forecasting. The proposed end-to-end approach can be utilized in a trading strategy that outperforms the market but suffers from high volatility. Experimental results show that sentiment extracted from articles influences next day returns, a relationship that is amplified by the length of the article.
Vedoucí práce: Milan Fičura
Diplomová práce (Ing.)—Vysoká škola ekonomická v Praze. Fakulta financí a účetnictví, 2021
Obsahuje bibliografii
Textový (vysokoškolská kvalifikační práce)
Rok obhajoby 2021
Způsob přístupu: Internet
Keywords: finance [obor dipl. práce]; diplomové práce; master's theses