Earnings season brings opportunities for investors to capitalise on market reactions to financial surprises. However, UBS analysis of a decade of share prices indicates the market is reacting more quickly to earnings news, compressing the traditional post-earnings announcement drift. Quantitative strategist James Cameron notes that earnings seasons are becoming more volatile, with the post-earnings announcement drift having “all but disappeared” since 2015. This compression of price drift is contributing to increased volatility during results periods, as prices adjust more rapidly.
The shift is attributed to advancements in technology. Quant funds and algorithmic trading, utilising artificial intelligence and natural language processing (NLP), are increasingly prevalent. RQI Investors, for example, uses NLP to quickly analyse analyst calls and gauge the sentiment of company executives. RQI Investors is an investment fund that employs technology to analyse large datasets and assess sentiment in financial news. They leverage generative AI and large-language models to evaluate the tone of news, filings, and conference calls, enhancing their investment decision-making process.
David Walsh, Head of Investments at RQI, highlights that while NLP has existed for some time, its capabilities have advanced significantly in recent years. He believes quant funds drive the increased speed in factoring earnings surprises into share prices. Daniel Broeren, a portfolio manager at Blackwattle Investment Partners, adds that quant models are becoming more sophisticated, factoring in not only the earnings surprise itself but also earnings momentum.
Broeren suggests that these trends create opportunities for active investors focused on company fundamentals. While acknowledging the market’s increased efficiency in pricing earnings surprises, he believes quant models lack the ability to contextualise news. This limitation, such as the inability to interview CEOs or engage with stakeholders, provides an edge for fundamental investors who can gain a deeper understanding of the underlying factors driving a company’s performance.
