voidly
Atlas · 1d / 7d / 30d forecasts

Multi-horizon forecast index

Three honest forecast horizons per country — each with its own XGBoost model, its own SHAP attribution, and its own 90% conformal interval. Click a country for per-horizon detail.

Trained 2026-05-21 · Recommendation: ship_all_three · model info

1d LOCO AUC
0.907
inflated — see scope note
7d LOCO AUC
0.883
inflated — see scope note
30d LOCO AUC
0.845
inflated — see scope note

20 spotlight countries · ranked by 30-day risk

#Country1d7d30d30d range (90%)Cons.
1Iran IR22%36%95%
[45, 100]
ok
2China CN22%59%95%
[45, 100]
ok
3Azerbaijan AZ15%59%91%
[41, 100]
ok
4Kazakhstan KZ15%59%91%
[41, 100]
ok
5Bangladesh BD15%59%91%
[41, 100]
ok
6India IN15%59%91%
[41, 100]
ok
7Egypt EG15%59%83%
[33, 100]
ok
8Venezuela VE15%59%83%
[33, 100]
ok
9Myanmar MM22%59%83%
[42, 100]
ok
10Pakistan PK15%59%83%
[33, 100]
ok
11Turkey TR15%59%83%
[33, 100]
ok
12Russia RU22%36%70%
[20, 100]
ok
13Belarus BY15%59%70%
[29, 100]
ok
14Cuba CU15%36%70%
[20, 100]
ok
15Ethiopia ET15%59%70%
[20, 100]
ok
16Turkmenistan TM15%36%70%
[20, 100]
ok
17TJ TJ15%59%70%
[20, 100]
ok
18Uzbekistan UZ15%59%70%
[28, 100]
ok
19AF AF15%36%70%
[20, 100]
ok
20Saudi Arabia SA15%59%70%
[20, 100]
ok

Cons. = monotonicity (P(1d) ≤ P(7d) ≤ P(30d)). 30d range = 90% conformal interval.

Why three horizons?

A single 7-day number is what most journalists ask for, but it hides two important things: the current-regime risk level tomorrow, and the operational ceiling over the next month. We train three independent XGBoost models and publish all three with LOCO AUC numbers and per-horizon SHAP attribution. Note: each horizon uses the same target_Nday sliding-window label as the production v1 forecast, so the LOCO AUCs are inflated by label autocorrelation the same way — these are current-regime risk signals, not shutdown-onset predictors. See the onset-skill finding.

The monotonicity check is a free honesty signal: longer windows must contain shorter windows, so if P(1d) > P(30d) the three models are disagreeing and you should treat the headline numbers with caution. See /atlas/models for the full registry, or /methodology for the full pipeline.

Related