Information and Price Dynamics brings Natural Language Processing (NLP) to financial news and social media. We capture business news headlines and Twitter conversations to gain leverage on events affecting stock prices and investor sentiment. These text features are transformed into indicators which are combined with and improve forecasts of high and low stock prices through machine learning algorithms.
- diverse data feeds can measure both opinion and events,
- cutting edge methods can more efficiently extract textual information from financial news sources
- machine learning techniques can integrate news/sentiment analysis with forecasts of price volatility.
We extract information using topic modelling, identfying event ensembles within the time-shifting content of the news environment.
We combine variables built from text-based features with price forecasts already shown to outperform “no change” predictions. This supports multi-day price range forecasts valuable for options trading.
A current focus of this research is on the market space encompassing nine (9) companies developing vaccines and anti-viral drugs for the COVID-19 virus.
Emergent BioSolutions Inc. (EBS)
Gilead Sciences, Inc. (GILD)
Heat Biologics, Inc. (HTBX)
Inovio Pharmaceuticals, Inc. (INO)
Moderna, Inc. (MRNA)
Novavax, Inc. (NVAX)
Regeneron Pharmaceuticals Inc
Takeda Pharmaceutical Company Limited (TAK)
Vir Biotechnology, Inc. (VIR)
For information on this program, please contact firstname.lastname@example.org or call 303-444-6356