StarMine quantitative analytics and models provide a rock-solid foundation for your investment research with StarMine quantitative analytics and models, spanning sectors, regions and markets.
Identify opportunities, save time and zero in on the most viable investment ideas. Using StarMine in your investment process is like adding an entire research department of PhD-level experts to your team. Our suite of quantitative analytics and models covers critical areas including value, momentum, ownership, risk and quality.
You can make better, faster investment decisions using StarMine’s quantitatively derived outputs to simplify the stock selection process. For example, SmartEstimates places the most weight on recent forecasts by toprated analysts, helping you predict future earnings and analyst revisions.
In addition, you can introduce new angles to investment strategy and test investment hypotheses with StarMine’s analytics and models, as well as validate and benchmark your own quantitative methods.
An update on the performance of StarMine SmartEstimate from Refinitiv and Predicted Surprise
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Combined Equity Models
What does an entire quant team in a single platform look like?
Forecasting Earning Misses
Using StarMine Signals for Country Selection
Evidence for Tilting Portfolios Toward Quality During Market Downturns
Learn more about StarMine Quantitative Analytics
“Forecasting Earnings Misses”
A Deeper Analysis of the Performance of SmartEstimates and Predicted Surprise
Celebrating 2018’s best sell-side analysts
StarMine Models Pick Asia Companies for FY 2018 Earnings Beats
StarMine Models Pick Asia Companies for FY 2018 Earnings Misses
StarMine FY17 Asia Earnings Surprise Results
Directionally correct predictions of earnings surprises between 7-8 times / 10 using weighted forecasts from top-rated analysts.
Quantitative models across value, momentum, ownership, risk and quality.
Improve accuracy and stock ranking ability with more robust and reliable equity valuations.
Captures almost 85% of default events in a 12-month horizon and bottom quintile of scored companies.
A unique quantitative signal that systematically analyzes a large body of previously untapped qualitative data to help you better predict credit risk.
Enhanced forecasts of macroeconomic data and FX rates using the historical accuracy of contributors to Reuters polls and applying weightings.