Crossing-Free Probabilistic K-Line Forecasts Without Retraining
Probabilistic K-line forecasting describes uncertainty in four complementary prices, namely open--high--low--close (OHLC). However, it introduces two consistency problems: quantile crossing and K-line crossing. Quantile crossing occurs when a higher-quantile forecast falls below a lower-quantile forecast, while K-line crossing occurs when the forecast low exceeds the open or close, or the forecast high falls below the open or close. Existing solutions generally address only one problem through output reordering, specialized architectures, or penalized training objectives. We propose K-line--Quantile Sequential Projection (KQSP), a parameter-free and training-free reconciliation method app...
| Authors | Runyao Yu, Yuchen Tao, Yujie Chen et al. |
|---|---|
| Primary category | stat.ML |
| Published | 29 July 2026 |
| Last updated at source | 29 July 2026 |
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