Generating Alpha from Pharmaceutical Events using ML & NLP
The stock market reaction to a single pharmaceutical event, such as a drug approval, repositioning, or adverse event, can have a spillover effect. Beyond the effect on the associated company’s stock price, an event may trigger a latent movement in the stock price of other publicly traded pharmaceutical companies. Research suggests that these sympathetic price movements may be a result of common attributes shared by the companies (beyond economic fundamentals), which are embedded in human language. In this piece, we explore how investors could leverage NLP to detect these ‘hidden relationships’ and generate alpha from pharmaceutical stocks.
Any investor in the healthcare sector knows the significant impact a catalytic event can have on a pharmaceutical company’s stock price. From drug approvals and clinical phase transitions to drug adverse events, there are various events to keep track of, with many investors utilising predictive analytics to anticipate the likelihood of these events (see here and here for our intelligence pieces on predicting clinical trial outcomes).
While it is clear that the announcement of a Pfizer drug approval would have an impact on Pfizer’s share price, it is less clear which other stocks might be affected by such an announcement.
This idea of spillover effect is