Based on current macro regime conditions and mfg unfilled orders-to-shipments's historical behaviour in similar regimes, the model projects 685,590.41 by 2026-12-31 ( +2.2% from 670,894 today). The 68% confidence range is 544,521.4 to 826,659.42; the wider 95% range is 409,095.15 to 962,085.67. 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 | 7.00% | 21.86% | 0.32 | 58.3% | 7.00% |
| 3Y | 36 | 5.89% | 19.65% | 0.30 | 54.3% | 18.17% |
| 5Y | 61 | 5.07% | 21.18% | 0.24 | 51.7% | 28.06% |
| 10Y | 121 | 3.56% | 22.56% | 0.16 | 52.5% | 41.83% |
| All | 298 | 2.63% | 23.03% | 0.11 | 51.9% | 90.05% |
Annualized total return = (1 + total)^(1/years) - 1. Ret/Vol is the annualized return divided by annualized volatility (Sharpe-equivalent without risk-free subtraction). Hit % = pct of single periods that were positive.
Where We Are Now[03]
Forward Returns by Macro Regime[04]
How Mfg Unfilled Orders-to-Shipments has performed historically conditional on the prevailing macro regime. The current bucket is highlighted; +1Y averages drive the headline signal above.
| REGIME BUCKET | N | +30D | +90D | +1Y AVG | +1Y MED | HIT % |
|---|---|---|---|---|---|---|
| Low (<15) | 65 | -0.36% | -0.06% | 1.69% | 2.42% | 72.3% |
| Normal (15-25) | 90 | -0.07% | 0.01% | 1.79% | 1.94% | 63.9% |
| Elevated (25-40) | 32 | -0.29% | 0.22% | 6.76% | 3.92% | 78.1% |
| Extreme (>40) | 3 | n/a | n/a | n/a | n/a | n/a |
| REGIME BUCKET | N | +30D | +90D | +1Y AVG | +1Y MED | HIT % |
|---|---|---|---|---|---|---|
| Inverted (<0bps) | 27 | -0.08% | 0.45% | 2.17% | 0.80% | 63.0% |
| Flat (0-100bps) | 62 | -0.27% | 0.44% | 3.05% | 3.02% | 67.9% |
| Steep (>100bps) | 100 | -0.27% | -0.02% | 2.96% | 3.47% | 73.0% |
| REGIME BUCKET | N | +30D | +90D | +1Y AVG | +1Y MED | HIT % |
|---|---|---|---|---|---|---|
| Tight (<350bps) | 24 | 0.10% | 0.04% | 3.98% | 2.10% | 78.9% |
| Normal (350-500bps) | 45 | -0.48% | 0.18% | 0.18% | -0.51% | 44.2% |
| Stressed (>500bps) | 18 | 0.71% | 0.97% | 7.70% | 3.06% | 72.2% |
| REGIME BUCKET | N | +30D | +90D | +1Y AVG | +1Y MED | HIT % |
|---|---|---|---|---|---|---|
| Weak (bottom tercile) | 34 | 0.37% | 0.65% | 0.22% | 3.63% | 67.6% |
| Neutral (middle) | 38 | 0.22% | 0.57% | 5.23% | 3.08% | 85.3% |
| Strong (top tercile) | 77 | -0.61% | -0.41% | 1.04% | 0.31% | 52.0% |
Forward returns are forward-looking from each historical observation in the bucket; +252d corresponds to one trading year. Buckets with fewer than 5 forward-return observations are reported as n/a. These are conditional historical averages, not forecasts.
Lead-Lag Relationships[05]
For each universally-recognised leading indicator, the lag at which the daily-return correlation peaks. Positive lag means the anchor leads Mfg Unfilled Orders-to-Shipments; negative means it lags.
| ANCHOR | ROLE | PEAK LAG | PEAK CORR | ZERO-LAG | RELATIONSHIP |
|---|---|---|---|---|---|
| HY OAS Spread | Credit risk leader | +59d | 0.279 | -0.261 | leads target by 59d |
| Initial Jobless Claims | Labor leader | 0d | -0.264 | -0.264 | coincident |
| Copper | Global growth proxy | 0d | 0.220 | 0.220 | coincident |
| Baa-10Y Spread | Credit risk (slow) | +23d | 0.192 | -0.087 | leads target by 23d |
| U-Mich Consumer Sentiment | Survey leader | -38d | -0.188 | -0.051 | lags target by 38d |
| 10Y-2Y Yield Spread | Recession leader | +46d | 0.181 | -0.087 | leads target by 46d |
| NFCI | Financial conditions | +39d | 0.179 | -0.022 | leads target by 39d |
| Trade-Weighted Dollar | FX driver | +46d | -0.171 | -0.101 | leads target by 46d |
| 10Y Treasury Yield | Discount-rate driver | -20d | 0.140 | 0.006 | weak |
| VIX | Volatility leader | -5d | 0.130 | 0.031 | weak |
Pearson correlation of daily returns over up to 25 years of overlapping history, searched across a ±60-day lag grid. Indicators classified as “weak” don't have meaningful predictive power at daily resolution; many of these (yield curve, NFCI, sentiment) lead at monthly/quarterly horizons instead.
Historical Analogs[06]
Periods where Mfg Unfilled Orders-to-Shipments sat at a similar percentile rank to today, with what happened over the next 30 / 90 / 252 trading days. Analogs are clustered to avoid double-counting nearby dates.
| DATE | VALUE | +30D | +90D | +1Y |
|---|---|---|---|---|
| Oct 1, 2024 | 614300.0000 | -6.34% | -8.96% | 2.25% |
| Jun 1, 2024 | 612870.0000 | -4.79% | 0.23% | 2.63% |
| Mar 1, 2024 | 613300.0000 | -2.78% | -4.86% | 2.24% |
| Nov 1, 2023 | 577377.0000 | -1.41% | 6.22% | -0.35% |
| Aug 1, 2023 | 625055.0000 | -2.44% | -8.93% | -1.35% |
Worst Historical Drawdown[07]
Largest Single-Period Moves[09]
- Mar 1, 201119.04%
- Mar 1, 202217.88%
- Mar 1, 201017.04%
- Jun 1, 202016.61%
- Mar 1, 202116.06%
- Apr 1, 2020-18.66%
- Jul 1, 2001-15.61%
- Nov 1, 2008-14.88%
- Jul 1, 2006-13.18%
- Jul 1, 2005-13.17%
Calendar-Month Seasonality[10]
Average single-period return aggregated by the calendar month in which the period ended.
| MONTH | AVG RETURN | HIT % | N |
|---|---|---|---|
| January | -5.99% | 0.0% | 25 |
| February | 2.21% | 96.0% | 25 |
| March | 12.77% | 100.0% | 25 |
| April | -5.97% | 4.2% | 24 |
| May | 3.32% | 91.7% | 24 |
| June | 3.98% | 87.5% | 24 |
| July | -8.75% | 0.0% | 25 |
| August | 8.31% | 100.0% | 25 |
| September | 0.05% | 48.0% | 25 |
| October | -0.52% | 32.0% | 25 |
| November | -5.23% | 0.0% | 25 |
| December | 1.02% | 64.0% | 25 |
N = 298 OBS · GENERATED 2026-05-18 10:30Z
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.
What is the historical range for Mfg Unfilled Orders-to-Shipments?▾
Historical ranges for Mfg Unfilled Orders-to-Shipments vary dramatically by regime. A level that is extreme in Goldilocks can be routine in Stagflation, and vice versa. The Historical Volatility section on this page describes the typical range and regime-specific behavior. For the full multi-decade history, visit the Mfg Unfilled Orders-to-Shipments chart page, which includes selectable time ranges up to five years and downloadable data.
How often is the Mfg Unfilled Orders-to-Shipments forecast updated?▾
This forecast page recalculates whenever the underlying data or regime classification changes, typically within hours of new data releases. The scenario probabilities refresh daily as the macro state is regenerated. Specific drivers listed on this page reflect the current state of the Convex regime engine, not static historical assumptions.
Is this forecast actionable for trading?▾
Convex forecasts are informational and educational. They describe probability distributions and regime-conditional paths rather than specific entry and exit levels. Traders and portfolio managers use them alongside other inputs including position sizing rules, risk management, and their own conviction calibration. They are not investment advice.
Get forecast updates for Mfg Unfilled Orders-to-Shipments and related indicators.
Forecasts are model-based projections derived from current regime classification, scenario probabilities, and historical patterns. They are not investment advice. All investments involve risk.