Natural Language Processing – Part II: Stock Selection

Highlights

• Learn how natural language processing can be used to uncover the signal within the signal for stock selection.
• Access the second part of S&P Global Market Intelligence's research report and make stock selection decisions with confidence.

Astute investors have shifted their attention to explore the information content in unstructured data sets to differentiate their alpha. S&P Global Market Intelligence’s earnings call transcripts data is one such example that may offer that differentiated source of alpha.

• Sentiment-based signals: Firms whose executives and analysts exhibited the highest positivity in sentiment during earnings calls outperformed their counterparts by 4.14% annually with significance at the 1% level. Firms with the largest year-over-year positive sentiment change and firms with the strongest positive sentiment trend outperformed their respective counterparts by 3.07% and 3.96% annually with significance at the 1% level. 
• Behavioral-based signals: Firms whose executives provided the most transparency by using the simplest language and by presenting results with numbers outperformed their respective counterparts by 2.11% and 4.43% annually with significance at the 1% level.
• Sentiment- and behavioral-based signals are not subsumed by commonly used alpha and risk signals. After adjustments, the signals generated excess long-short returns ranging from 1.65% to 3.64% annually with significance at the 1% level. The sentiment- and behavioral-based signals had some of the highest information ratios among all considered strategies and are lowly and negatively correlated with each other.
• Positive language from the unscripted responses by the executives during the Q&A drove the overall predictability of the positive sentiment signal. 
• The sentiment of CEOs has historically been more important than the sentiment of other executives. A strategy based on the sentiment of CEOs generated 3.63% per year on a long-short basis with significance at the 1% level. 
• The aggregate sentiment of analysts historically enhanced the predictability of the 3-month FY1 EPS analyst revision signal. A strategy using the aggregate sentiment of analysts from earnings calls yielded 4.24% per year on a long-short basis with significance at the 1% level.