Systematically analyze SEC filings to feed insights into portfolio and risk management models using Natural language processing (NLP) for a UK based Buy-side Firm
Sucess Dialog
This is added to your favourites.
Warning Dialog
This is already added to your favourites.
sorry something went wrong.
Objective
Client, a UK Based buy-side firm, was starting to incorporate quantitative overlay to the investment process
They wanted to implement quantitative process based on a paper called ‘Lazy Prices’ published by Harvard
Systematically analyze SEC filings of Russell 3,000 firms to feed insights into portfolio and risk management models
Platforms used
Python, Apache Spark, NLP Algorithms
Client impact
Strengthened portfolio and risk management models by generating complementary and uncorrelated signals
Scored firms based on changes in text structure and content, sentiment analysis. Z-scores helped comparison within sectors and broader market
Used advanced NLP algorithms to undertake period on period analysis and quantify change in structure and content of the text
Request for services
Questions
Looking for high-end research and risk services? Reach out to us at:
