Algometrics: Forecasting Under Algorithmic Feedback

This paper introduces algometrics, a framework for time series whose evolution depends on the predictive algorithms forecasting them. It distinguishes historical risk from deployment risk, proving that deployment risk is not identifiable from passive historical data alone and that historical model rankings can invert under crowding.