The Spectrum Is Not Enough: When Context Helps Time-Series Forecasting
A growing family of indices scores how predictable a series is from its spectrum. Practitioners increasingly read these scores as answering a different question: whether \emph{adding context}, a longer lookback, a retrieval plug-in, or a pretrained model, will help. These are not the same question. The value of context is a property of the operating point, not of the series. Any index built from the power spectrum is invariant under phase randomization, whereas the beyond-second-order value that retrieval and foundation models supply is not, because a phase-randomized series is asymptotically Gaussian. We state this as an impossibility result and isolate it with surrogate pairs that fix t...
| Authors | Mert Onur Cakiroglu, Mehmet Dalkilic, Hasan Kurban |
|---|---|
| Primary category | cs.LG |
| Published | 14 July 2026 |
| Last updated at source | 15 July 2026 |
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