Swiss Journal of Economics and Statistics (Aug 2024)
Sentiment-semantic word vectors: A new method to estimate management sentiment
Abstract
Abstract This paper introduces a novel method to extract the sentiment embedded in the Management’s Discussion and Analysis (MD &A) section of 10-K filings. The proposed method outperforms traditional approaches in terms of sentiment classification accuracy. Utilizing this method, the MD &A sentiment is found to be a strong negative predictor of future stock returns, demonstrating consistency in both in-sample and out-of-sample settings. By contrast, if traditional sentiment extraction methods are used, the MD &A sentiment exhibits no predictive ability for stock markets. Additionally, the MD &A sentiment is associated with dividend-related macroeconomic channels regarding future stock return prediction.
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