Based on current macro regime conditions and mfg unfilled orders-to-shipments's historical behaviour in similar regimes, the model projects 670,935.73 by 2026-12-31 ( +2.1% from 657,044 today). The 68% confidence range is 548,491.22 to 793,380.25; the wider 95% range is 430,944.48 to 910,926.99. Methodology below the headline.
Mfg Unfilled Orders-to-Shipments Forecast 2026
Quantitative analysis from 298 observations of Mfg Unfilled Orders-to-Shipments history, joined to four universal macro regime classifications. Numbers are computed, not narrated.
Performance by Window[02]
| WINDOW | N | ANN RET | ANN VOL | RET/VOL | HIT % | TOTAL |
|---|---|---|---|---|---|---|
| 1Y | 13 | 7.79% | 21.74% | 0.36 | 58.3% | 7.78% |
| 3Y | 36 | 2.60% | 19.62% | 0.13 | 51.4% | 7.79% |
| 5Y | 61 | 5.27% | 21.15% | 0.25 | 51.7% | 29.27% |
Forecast Approach
regime implied: The current macro regime classification (Goldilocks, Reflation, Stagflation, or Deflation) dictates the expected direction and magnitude of movement, calibrated against historical regime performance.
Consensus source: Atlanta Fed GDPNow and Blue Chip consensus
Key Drivers & Risks
- •Consumer spending
- •Business investment
- •Government spending
- •Net exports
- •Inventory cycles
Historical Volatility
Moderate: 2-4% GDP growth range typical
Frequently Asked Questions
What factors could push Mfg Unfilled Orders-to-Shipments higher?▾
The primary drivers that tend to lift Mfg Unfilled Orders-to-Shipments depend on the current macro regime. Economic activity indicators reveal whether the economy is expanding or contracting in real time. ISM PMI readings above 50 signal expansion, while GDP growth tells the definitive story each quarter. Leading indicators like the Conference Board LEI can flag downturns months in advance, giving traders a head start on positioning. Convex tracks these drivers live across the Economic Activity category and flags when multiple forces align in the same direction. See the "Key Drivers & Risks" section on this page for the current list, and check the regime dashboard for how the macro backdrop is currently tilted.
What factors could push Mfg Unfilled Orders-to-Shipments lower?▾
The same transmission channels that drive Mfg Unfilled Orders-to-Shipments higher operate in reverse when conditions flip. The risk drivers listed above map directly to scenarios that, if triggered, would pull this metric in the opposite direction. Convex aggregates these into a scenario-weighted probability distribution rather than a point forecast, so the magnitude depends on which scenarios activate.
Where does consensus see Mfg Unfilled Orders-to-Shipments heading?▾
Rather than publish a point target that goes stale the day after release, Convex assembles consensus from the macro regime classification, active scenario probabilities, and historical base rates. Point forecasts from banks and strategists are worth reading for context, but they typically cluster around the consensus and miss the tail events that actually move markets. The scenario-weighted approach here captures that tail risk explicitly.
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Forecasts are model-based projections derived from current regime classification, scenario probabilities, and historical patterns. They are not investment advice. All investments involve risk.