New drugs and stock market: a machine learning framework for predicting pharma market reaction to clinical trial announcements.

ABSTRACT: Pharmaceutical companies operate in a strictly regulated and highly risky environment in which a single slip can lead to serious financial implications. Accordingly, the announcements of clinical trial results tend to determine the future course of events, hence being closely monitored by the public. Most works focus on retrospective analysis of announcement impact on company stock prices, bypassing the consideration of the problem in the predictive paradigm. In this work, we aim to close this gap by proposing a framework that allows predicting the numerical values of announcement-induced changes in stock prices. In fact, it is a problem of the impact prediction of the specific event on the corresponding time series. Our framework includes a BERT model for extracting the sentiment polarity

SUBMITTER: Budennyy S 

PROVIDER: S-EPMC10406841 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature