ORCID
Kamil Polak 0000-0002-9897-8431
Keywords
sentiment analysis; natural language processing; machine learning; financial forecasting; behavioral finance
Abstract
The purpose of this research is to examine the impact of sentiment derived from news headlines on the direction of stock price changes. The study examines stocks listed on the WIG-banking sub-sector index on the Warsaw Stock Exchange. Two types of data were used: textual and market data. The research period covers the years 2015–2018. Through the research, 7,074 observations were investigated, of which 3,390 with positive sentiment, 2,665 neutral, and 1,019 negative. In order to examine the predictive power of sentiment, six machine learning models were used: Decision Tree Classifier, Random Forest Classifier, XGBoost Classifier, KNN Classifier, SVC and Gaussian Naive Bayes Classifier. Empirical results show that the sentiment of news headlines has no significant explanatory power for the direction of stock price changes in one-day time frame.
Recommended Citation
Polak, K. (2024). The Impact of Investor Sentiment on Direction of Stock Price Changes: Evidence from the Polish Stock Market. Journal of Banking and Financial Economics, 2021(16), 72-90. https://doi.org/10.7172/2353-6845.jbfe.2021.2.4
First Page
72
Last Page
90
Page Count
90
Received Date
13 September 2021
Revised Date
8 December 2021
Accept Date
18 December 2021
Online Available Date
30 December 2021
DOI
10.7172/2353-6845.jbfe.2021.2.4
JEL Code
G14; G17; G41
Publisher
University of Warsaw