Author
Listed:
- Oleksii Ivanov
(Kherson State University, Department of Computer Science and Software Engineering)
- Vitaliy Kobets
(Kherson State University, Department of Computer Science and Software Engineering)
Abstract
The identification of risk classes is accomplished by utilizing the financial indicators outlined in 10-Q filings. However, we do not know of any studies that examine both financial indicators and textual sentiments in 10-Q filings concerning stock price trends. The study’s findings indicate a statistically significant positive association between news sentiments and the S&P 500 market index. During periods of market instability, stock prices respond significantly more to news. Promoting unstructured data processing is crucial, since technology does not always replace intellectuals. In the opposite, their work is growing, and the decision-making support system offers more in-depth task analysis. This paper aims to identify a relationship between the stock prices, the financial indicators in the quarterly report, and the outcomes of the sentiment analysis of the report. This article examines various models for forecasting stock prices and explores how continuing research is closing the gap in price prediction. Our advanced method integrates numerical and textual data to evaluate the effects of reports on the company’s stock price. The offered approach may benefit the client’s investment asset manager by assisting with decision-making regarding rebalancing the investment portfolio.
Suggested Citation
Oleksii Ivanov & Vitaliy Kobets, 2025.
"Future Financial Impact Analysis from Sentiment and Indicators Analysis,"
Computational Economics, Springer;Society for Computational Economics, vol. 66(6), pages 4959-4985, December.
Handle:
RePEc:kap:compec:v:66:y:2025:i:6:d:10.1007_s10614-025-10891-7
DOI: 10.1007/s10614-025-10891-7
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