StarMine Classic Quantitative Models
Quantitative research models that give you robust stock selection factors – used on a standalone basis or as an input into a multi-factor model.
StarMine Classic Quantitative Models output percentile ranks between one and 100, with one representing the lowest rated stocks (bearish views) and 100 indicating the highest rated stocks (bullish views).
The final model signals are generally ranked globally as well as by region, sector, and industry, to further allow the user to tune the factors to their existing model.
Content and features
StarMine ARM is an analyst revisions stock ranking model, designed to predict future changes in analyst sentiment. Incorporates more accurate earnings estimates through the SmartEstimate prediction service.
StarMine Price Mo intelligently acknowledges the tendency of long-term trends in returns to continue, plus the tendency of short-term trends to revert, with an innovative mix of components.
Smart Growth & Intrinsic Valuation (IV)
StarMine IV identifies systematic biases in analyst earnings forecasts and leverages these findings to deliver an intelligent stream of EPS estimates called SmartGrowth earnings projections. SmartGrowth earnings projections significantly improve forecast accuracy and stock ranking ability and lead to more reliable equity valuation analyses.
Relative Valuation (RV)
StarMine’s robust stock-ranking RV model profitably sorts companies by intelligently combining information from six powerful valuation ratios into a single comprehensive measure of relative valuation.
Val-Mo takes advantage of the valuable and complementary information in value and momentum signals. It condenses unique and proprietary information contained in StarMine’s valuation and momentum models.
Earnings Quality (EQ)
StarMine EQ employs a quantitative multi-factor approach to predict the persistence of earnings. It differentially weights the sources of earnings based on analysis of their relative sustainability.
Markets and industries
StarMine Quantitative Models give investors robust stock selection factors that can be used on a standalone basis, or as an input into a multi-factor model.
StarMine Quantitative Models output percentile ranks – globally, and by region, sector, and industry, to allow the user to tune the factors to their existing model.