Conformal prediction for time series and forecasting

Creating reliable PIs for time series forecasting has been a longstanding, intricate challenge that remained unsolved for years until conformal prediction emerged.

This problem was underscored during the 2018 M4 Forecasting Competition, which necessitated participants to supply PIs and point estimates.

In the research paper titled Combining Prediction Intervals in the M4 Competition, (https://www.sciencedirect.com/science/article/abs/pii/S0169207019301141), Yael Grushka-Cockayne from the Darden School of Business and Victor Richmond R. Jose from Harvard Business School scrutinized 20 interval submissions. They assessed both the calibration and precision of the predictions and gauged their performances across different time horizons. Their analysis concluded that the submissions were ineffective in accurately estimating uncertainty.

Ensemble batch PIs (EnbPIs)

Conformal Prediction Intervals for Dynamic Time-Series (http...