Sentiment in Big Tech’s Investor Relations: Does the Discourse Predict Future Stock Movements?
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Date
2024-01-03
Authors
Goldberg, David
Hong, Sukhwa
Villacis Calderon, Eduardo
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1130
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Financial disclosures are crucial for understanding a firm's status and future performance. While previous research has focused on written disclosures like press releases and reports, these documents have limitations in that they are carefully crafted one-way communication from firms to the public. Our study explores the predictive possibility of communications during investor relations calls. These calls capture unscripted narratives from between firms’ senior leadership and industry analysts. By examining the interplay between the tone of public questions and senior leadership's responses, we investigate to what extent this interaction predicts a firm's future performance. We find that average question sentiment has a persistent positive association with average stock price in the successive quarter, but answer sentiment was not a significant predictor. Our study offers a fresh perspective on financial disclosures and highlights the value of oral communications and their tones in gaining insights into firms' prospects.
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Data Science and Machine Learning to Support Business Decisions, investor relations, sentiment analysis, stock returns, text mining
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7 pages
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Proceedings of the 57th Hawaii International Conference on System Sciences
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Attribution-NonCommercial-NoDerivatives 4.0 International
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