Intelligence Update · edition 2026-09-12 · September 2026 Past editions · Methodology · Independence
sx1 Hardware Shortage Intelligence Research Data & methodology
FORECAST PIPELINE · Q+1..Q+3 · no client-side modelling
as of — Holt damped ETS · backtest-selected · monthly refit

The model that stops where the evidence stops.

This page shows the raw statistical output: three quarterly series, each with 80% and 95% bands and a regime flag. Everything lives in static JSON (forecast/forecast-output.json), generated by forecast/forecast.py. The browser computes nothing — it only displays.

REGIME All three series carry regime_flag: true: the latest observations deviate structurally from the training regime. The bands are deliberately wide; treat point values as anchors, not promises.
01
Outcomes

Three series, three horizon steps

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02
Track record

How the published claims have done

Every forecast this page publishes is frozen in an append-only ledger and later scored against realised values: absolute error, pinball loss across the published band quantiles, and empirical coverage of the 80% and 95% bands against their nominal rates. The honest state today: nothing has matured yet. Realised-value ingestion is curated manually — until a target quarter closes and its value is recorded, every step below reads awaiting resolution. The scorer is proven against fixed fixtures (tests/) before real outcomes accrue.

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03
Claims archive

Every edition we ever published

Forecasts cannot be quietly rewritten here. Each published edition is frozen as an immutable, content-addressed claim (id HSF-…) in forecast/ledger.json, rebuilt from the repository's git history. A newer edition supersedes an older one — it never erases it. Superseded claims stay on this page and stay in the scorecard.

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04
Methodology

What sits under the hood

A

Holt, damped (phi=0.8)

For series with 3–4 quarterly points, the full ETS/SARIMA + exogenous specification (forecasting-methods.md item 5) is not executable. The card recipe falls back to Holt with a damped trend — the most conservative smoother that still holds a direction.

B

Backtest selection, rolling origin

Alpha per series via one-step rolling-origin backtest. Sigma from residuals; 95% band = 1.96·sigma, 80% band = 1.2816·sigma, with a z-fallback when n_resid<5. Backtest MAE is shown next to every outcome.

C

Static JSON, monthly refit

No client-side modelling: forecast.py runs in the nightly pipeline and writes forecast-output.json. The page is a rendering, not a simulator. Beyond Q+3 the scenario outlook takes over — see Outlook 2027–2029.

05
Transparency

What the model refused

77 series delivered, 3 forecast, 74 skipped. A series with fewer than three dated numeric points is not extrapolated — the reason per series is listed below. Refusal is a result.

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