Naslov
The Use of Natural Language Processing for Stock Market Prediction

Autori
Puh, Karlo

Vrsta, podvrsta i kategorija rada
Ocjenski radovi, diplomski rad, diplomski

Fakultet
Fakultet elektrotehnike i računarstva

Mjesto
Zagreb

Datum
06.07

Godina
2022

Stranica
41

Mentor
Bagić Babac, Marina

Ključne riječi
stock market prediction ; machine learning ; time-series analysis ; recurrent neural network ; BERT

Sažetak
Predicting the stock market’s prices has always been an interesting topic since its closely related to making money. The use of natural language processing has opened new perspectives for solving this task. In this paper, the conventional statistical models for time-series prediction are implemented as a benchmark. Then, for methodological comparison, various state-of- the-art natural language models ranging from the baseline CNN and RNN to the most advanced BERT models are implemented and tested. Experimental results show that there is a correlation between the textual information in the news headlines and stock price prediction. The model based on the GRU cell with one linear layer which takes pairs of the historical prices and the sentiment score calculated using BERT achieved the best results.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo

POVEZANOST RADA