Abstract
Textual analysis of news articles is increasingly important in predicting stock prices. Previous research has intensively utilized the textual analysis of news and other firm-related documents in volatility prediction models. It has been demonstrated that the news may be related to abnormal stock price behavior subsequent to their dissemination. However, previous studies to date have tended to focus on linear regression methods in predicting volatility. Here, we show that non-linear models can be effectively employed to explain the residual variance of the stock price. Moreover, we use meta-learning approach to simulate the decision-making process of various investors. The results suggest that this approach significantly improves the prediction accuracy of abnormal stock return volatility. The fact that the length of news articles is more important than news sentiment in predicting stock return volatility is another important finding. Notably, we show that Rotation forest performs particularly well in terms of both the accuracy of abnormal stock return volatility and the performance on imbalanced volatility data.
Highlights
Key investment decisions are based on the assumption that the theoretical stock price, expressed by its intrinsic value, is different from the current stock market price for which it is traded on organized markets
Prior literature reported an important role of text analysis in predicting stock market indicators such as stock prices, trading volumes and volatility
The present study was designed to develop a novel meta-learning model for predicting abnormal stock return volatility. Both the financial indicators of stock market and the textual analysis of news articles were included in this model
Summary
Key investment decisions are based on the assumption that the theoretical stock price, expressed by its intrinsic value, is different from the current stock market price for which it is traded on organized markets. Investors’ expectations, including the technical analysis of the stocks and their subjective reactions, form market stock prices. Changes in the prices are related to psychological analysis, based on the assumption that stock prices are strongly influenced by the psychological response of investors, especially in the short-term. What is crucial from the point of view of firm-related text news: when investors’ expectations change, the intrinsic values of stocks change in their mindset too and, as a result, their willingness to buy or sell stocks is affected. This is reflected in the stock price. Recent studies suggest that public information diffuses gradually through the investor population (DellaVigna and Pollet, 2009)
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
