Expectations vs. Realities: The Cost of MSE-Optimal Forecasting Under Conditional Uncertainty

ArXi:2606.04342v1 Announce Type: cross Multi-step time series forecasting (MSF) is commonly evaluated using point-wise error metrics such as mean squared error (MSE), implicitly treating the conditional mean as a sufficient target. We show that this can be misleading under conditional uncertainty, where the conditional expectation becomes unrepresentative of typical realized values at longer horizons.