ResearchJuly 15, 2026
The 'Granularity Paradox': Why Finer Time-Series Data Can Make Forecasts Worse
A new arXiv paper identifies a 'Granularity Paradox': finer time intervals (e.g., daily vs. monthly) improve in-sample metrics but often worsen real-world forecast accuracy due to recursive error compounding.
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