Using AI to extract sentiment from conference calls
The tone or sentiment of management earning call discussions can be an additive and significant source of alpha generation for investors, a study from Realindex finds.
Our ongoing research on extracting alpha from conference calls is moving strongly into the area of natural language processing (NLP) and the use of Artificial Intelligence (AI) tools. Previously, it was revealed that the length and complexity of earnings calls, as well as extracting sentiment could hint at future stock return performance. These alpha signals influenced our portfolio exposures to the banking crisis in March 2023, ensuring we were underweight to Credit Suisse and to US regional banks like SVB Financial, Signature Bank and First Republic.
As we continue to uncover more opportunities to generate alpha in this area of research, we find that AI is a potent tool to enhance contextual awareness in language models, better capturing sentiment in earnings calls transcripts, specifically management’s prepared presentation, analyst questions and management answers.
What we’re doing with this at Realindex
In this short note, we show that implementing FinBERT or a variation of BERT re-trained on financial data can provide meaningful information on future cross-sectional stock price returns. We are looking to implement a variation of this sentiment score for our alpha model as it is both additive and significant in alpha generation.
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