Analyzing the Impact of Financial News Sentiments on Stock Prices—A Wavelet Correlation

Marian Pompiliu Cristescu, Dumitru Alexandru Mara (), Raluca Andreea Nerișanu, Lia Cornelia Culda and Ionela Maniu
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Marian Pompiliu Cristescu: Faculty of Economic Sciences, Lucian Blaga University of Sibiu, 550324 Sibiu, Romania
Dumitru Alexandru Mara: Faculty of Economic Sciences, Lucian Blaga University of Sibiu, 550324 Sibiu, Romania
Raluca Andreea Nerișanu: Faculty of Economic Sciences, Lucian Blaga University of Sibiu, 550324 Sibiu, Romania
Lia Cornelia Culda: Faculty of Economic Sciences, Lucian Blaga University of Sibiu, 550324 Sibiu, Romania
Ionela Maniu: Faculty of Sciences, Lucian Blaga University of Sibiu, 550012 Sibiu, Romania

Mathematics, 2023, vol. 11, issue 23, 1-20

Abstract: This study investigates the complex interplay between public sentiment, as captured through news titles and descriptions, and the stock prices of three major tech companies: Microsoft (MSFT), Tesla (TSLA), and Apple (AAPL). Leveraging advanced analytical methods including Pearson correlation, wavelet coherence, and regression analysis, this research probes the degree to which stock-price fluctuations can be attributed to the polarity of media sentiment. The methodology combines statistical techniques to assess sentiment’s predictive power for stock opening and closing prices, while wavelet coherence analysis unveils the temporal dynamics of these relationships. The results demonstrate a significant correlation between sentiment polarity and stock prices, with description polarity affecting Microsoft’s opening prices, title polarity influencing Tesla’s opening prices, and a positive impact of title polarity on Apple’s closing prices. However, Tesla’s stock showed no significant coherence, indicating a potential divergence in how sentiment affects stock behavior across companies. The study highlights the importance of sentiment analysis in forecasting stock-market trends, revealing not only direct correlations but also lagged influences on stock prices. Despite its focus on large-cap tech firms, this research provides a foundational understanding of sentiment’s financial implications, suggesting further investigation into smaller firms and other market sectors.

Keywords: sentiment analysis; stock-market prediction; wavelet coherence analysis; media influence on stocks (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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