Cirrus Case Study – Big Data Sentiment as a Portfolio Factor

Cirrus’ quantitative modeling identifies stocks that are likely to outperform based on fundamental variables such as growth, earnings expectations and valuations. Specifically, four stock selection pillars comprise the various Cirrus models, with the Capital Appreciation model allocating more exposure to Price and Business Momentum, and placing less emphasis on the Valuation and Quality pillars. Cirrus tested Stocksnips Big Data AI based News Sentiment to take the modeling one step further to improve Alpha generation.