04:00
2026-07-08
arxiv.org
machine-learning
The Granularity Paradox: How Temporal Disaggregation Inflates In-Sample Fit and Compounds Out-of-Sample Error
A study on the 'Granularity Paradox' in time-series forecasting finds that finer temporal disaggregation improves in-sample fit but degrades out-of-sample accuracy due to recursive error compounding. …