# Conformal Prediction Intervals with Tail-Specific Guarantees

arXiv: https://arxiv.org/abs/2606.18199 · HTML: https://mlsanity.com/paper/2606.18199/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 0 of its 25 references that are in the map.
- First posted on arXiv 16 Jun 2026.

## Abstract (arXiv)

This paper extends classical conformal frameworks for constructing prediction intervals with global marginal coverage 1-α to intervals that provide explicitly calibrated guarantees for the upper and lower tails separately. Focusing on split conformal prediction, we first construct lower and upper one-sided conformal intervals that achieve marginal validity, and then derive the induced two-sided interval by intersection. Theoretical results prove both tail-specific and global marginal coverage of the induced two-sided interval. Results are presented first for the exchangeable setting, where coverage has finite-sample guarantees, and then for non-exchangeable data, where guarantees are asymptotic. Simulation studies show that the proposed approach achieves improved directional calibration relative to classical two-sided intervals, especially relevant in skewed data. Finally, the benefit of the proposed framework is showcased in a financial application, where one aims for return maximization while seeking strict control on the left tail.