Applying BERT to analyze investor sentiment in stock market

This paper is an analysis of investor sentiment in the stock market based on the bidirectional encoder representations from transformers (BERT) model. First, we extracted the sentiment value from online information published by stock investor, using the Bert model. Second, these sentiment values were weighted by attention for computing the investor sentiment indicator. Finally, the relationship between investor sentiment and stock yield was analyzed through a two-step cross-sectional regression validation model. The experiments found that investor sentiment in online reviews had a significant impact on stock yield. The experiments show that the Bert model used in this paper can achieve an accuracy of 97.35% for the analysis of investor sentiment, which is better than both LSTM and SVM methods.

Automated summary

This study analyzed investor sentiment in the stock market using the BERT model and found that sentiment in online reviews significantly affects stock yield. Experimental results showed that the BERT model has high accuracy in analyzing investor sentiment.