The whole S&P 500, ranked every day.
One score per stock, zero to one hundred, refreshed daily. It combines ORTEX short-interest data, momentum and value rankings, analyst and sentiment moves, fundamentals and technicals, hundreds of data points weighed by machine learning and AI. It is the view a quant desk builds in-house, ready to screen, sort and download.
What the score has done since 2010
Two long-only S&P 500 strategies picked purely by the score, rebalanced monthly, turned $1,000 into $24,596 (Short Momentum) and $16,358 (Balanced) in a 16.3-year historical simulation, against $8,642 for the S&P 500 Total Return Index. Both beat the index on risk-adjusted terms too: Sharpe ratios of 1.14 and 1.12 against 0.90, and the Balanced strategy came through 2020 with a smaller maximum drawdown than the index itself.
Historical backtest, gross of costs. Sharpe vs a ~1.6% 3M T-bill. Past performance is not a reliable indicator of future results.
Feed your own model.
Every score, current and historical, ships over the REST API and Python SDK. Pull the composite or the family sub-scores (momentum, value, quality, growth) and apply your own weights: our inputs, your model.
Stock Scores API reference →See also: Short Interest data, Index Rebalance forecasts and the ORTEX API.