If you're building time series prediction systems, use the leave-a-window-out jackknife instead of standard jackknife or split conformal methods—it gives you valid confidence intervals without sacrificing accuracy.
This paper fixes a problem with standard statistical methods for time series prediction. The vanilla jackknife method (used to estimate prediction intervals) fails on time series data because it assumes data points are independent, which they're not.