Machine learning and sentiment analysis in behavioural investing – evidence from Poland

The recent popularity of behavioural finance, combined with machine learning, offers an opportunity to challenge the duopoly of fundamental and technical analysis in stock selection. Behavioural analysis – an indirect method of stock evaluation based on the direct analysis of investor behaviour – offers a novel approach to investing. Its most popular instrument, sentiment analysis, has been shown to be useful in investing, although the relation between investor sentiment and stock prices is not yet clear, and behavioural investing is not well described in the literature. Moreover, there are only a few papers concerning investor sentiment in the Polish equity market, which creates a research gap, compared to other developed markets. The goal of this paper is to examine this relation and to test the efficacy of sentiment-based methods in behavioural investing. The relationship between investor sentiment and stock price movements was  examined using Matthews and Pearson correlation coefficients, and the efficacy of sentiment-based investment strategies was compared with the buy-and-hold approach. By leveraging threads from the Bankier. pl forum, this paper confirms a positive but mode