Based on current macro regime conditions and cpi (all urban)'s historical behaviour in similar regimes, the model projects 338.77 by 2026-12-31 ( +1.9% from 332.41 today). The 68% confidence range is 335.71 to 341.84; the wider 95% range is 332.76 to 344.78. Methodology below the headline.
CPI (All Urban) Forecast 2026
Quantitative analysis from 298 observations of CPI (All Urban) 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 | 12 | 3.78% | 0.77% | 4.94 | 100.0% | 3.78% |
| 3Y | 35 | 3.19% | 0.59% | 5.36 | 97.1% | 9.58% |
| 5Y | 60 | 4.51% | 0.99% | 4.56 | 96.6% | 24.68% |
| 10Y | 120 | 3.35% | 0.95% | 3.53 | 90.8% | 39.09% |
| All | 298 | 2.55% | 1.07% | 2.40 | 82.5% | 87.06% |
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 CPI (All Urban) 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 | 0.21% | 0.75% | 2.36% | 2.33% | 98.5% |
| Normal (15-25) | 90 | 0.27% | 0.96% | 2.80% | 2.55% | 95.2% |
| Elevated (25-40) | 32 | 0.16% | 1.01% | 3.02% | 2.25% | 96.9% |
| 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 | 0.27% | 1.10% | 3.24% | 2.97% | 100.0% |
| Flat (0-100bps) | 62 | 0.28% | 1.09% | 3.04% | 2.64% | 100.0% |
| Steep (>100bps) | 100 | 0.19% | 0.73% | 2.34% | 2.05% | 94.0% |
| REGIME BUCKET | N | +30D | +90D | +1Y AVG | +1Y MED | HIT % |
|---|---|---|---|---|---|---|
| Tight (<350bps) | 24 | 0.33% | 1.39% | 4.28% | 2.94% | 100.0% |
| Normal (350-500bps) | 45 | 0.26% | 1.04% | 2.88% | 2.61% | 100.0% |
| Stressed (>500bps) | 18 | 0.23% | 0.91% | 3.06% | 2.44% | 100.0% |
| REGIME BUCKET | N | +30D | +90D | +1Y AVG | +1Y MED | HIT % |
|---|---|---|---|---|---|---|
| Weak (bottom tercile) | 34 | 0.31% | 0.88% | 2.68% | 2.58% | 82.4% |
| Neutral (middle) | 38 | 0.18% | 1.00% | 2.82% | 1.88% | 97.1% |
| Strong (top tercile) | 77 | 0.20% | 0.82% | 2.44% | 2.33% | 98.7% |
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 CPI (All Urban); negative means it lags.
| ANCHOR | ROLE | PEAK LAG | PEAK CORR | ZERO-LAG | RELATIONSHIP |
|---|---|---|---|---|---|
| NFCI | Financial conditions | +11d | -0.381 | 0.013 | leads target by 11d |
| Initial Jobless Claims | Labor leader | 0d | -0.350 | -0.350 | coincident |
| Trade-Weighted Dollar | FX driver | 0d | -0.339 | -0.339 | coincident |
| Baa-10Y Spread | Credit risk (slow) | 0d | -0.319 | -0.319 | coincident |
| HY OAS Spread | Credit risk leader | 0d | -0.300 | -0.300 | coincident |
| Copper | Global growth proxy | 0d | 0.281 | 0.281 | coincident |
| 10Y Treasury Yield | Discount-rate driver | 0d | 0.266 | 0.266 | coincident |
| 10Y-2Y Yield Spread | Recession leader | -6d | -0.183 | 0.097 | lags target by 6d |
| VIX | Volatility leader | +1d | -0.176 | -0.168 | coincident |
| U-Mich Consumer Sentiment | Survey leader | -38d | -0.168 | -0.101 | lags target by 38d |
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 CPI (All Urban) 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 |
|---|---|---|---|---|
| Mar 1, 2025 | 319.7850 | 0.16% | 0.75% | 3.95% |
| Dec 1, 2024 | 317.6040 | 0.43% | 0.85% | 2.83% |
| Sep 1, 2024 | 314.7320 | 0.29% | 1.34% | 3.02% |
| Jun 1, 2024 | 313.0440 | 0.17% | 0.83% | 2.68% |
| Mar 1, 2024 | 312.3450 | 0.22% | 0.39% | 2.38% |
Worst Historical Drawdown[07]
Largest Single-Period Moves[09]
- Sep 1, 20051.38%
- Jun 1, 20221.26%
- Mar 1, 20221.12%
- Jun 1, 20081.05%
- Oct 1, 20210.96%
- Nov 1, 2008-1.77%
- Oct 1, 2008-0.86%
- Dec 1, 2008-0.82%
- Apr 1, 2020-0.79%
- Jan 1, 2015-0.64%
Calendar-Month Seasonality[10]
Average single-period return aggregated by the calendar month in which the period ended.
| MONTH | AVG RETURN | HIT % | N |
|---|---|---|---|
| January | 0.24% | 84.0% | 25 |
| February | 0.27% | 92.0% | 25 |
| March | 0.25% | 84.0% | 25 |
| April | 0.20% | 88.0% | 25 |
| May | 0.19% | 75.0% | 24 |
| June | 0.29% | 79.2% | 24 |
| July | 0.21% | 84.0% | 25 |
| August | 0.23% | 84.0% | 25 |
| September | 0.27% | 92.0% | 25 |
| October | 0.15% | 79.2% | 24 |
| November | 0.10% | 76.0% | 25 |
| December | 0.14% | 72.0% | 25 |
N = 298 OBS · GENERATED 2026-05-18 09:00Z
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: Cleveland Fed nowcast and breakeven inflation
Key Drivers & Risks
- •Energy prices
- •Shelter costs
- •Wage growth
- •Supply chains
- •Monetary policy
Historical Volatility
Low-moderate: 1-3% annual range under normal conditions
Scenarios That Affect This Forecast
How Headline CPI Forecasts Have Held Up Historically
Headline CPI forecasts have a poor track record because food and energy prices dominate the print and are themselves hard to forecast. The 2021-2022 inflation surge was missed by every major forecaster; consensus end-2021 CPI was near 2.5%, realized was 7.0%; consensus mid-2022 was near 5%, realized peaked at 9.1% in June 2022.
Regime-conditional models on CPI achieve roughly 60% directional accuracy on monthly windows but materially better on the trend (12-month direction). The Cleveland Fed nowcast and the BLS-published monthly print itself have been the most-reliable real-time signals.
Regime Sensitivity for Headline CPI
Headline CPI is itself a regime variable. The Inflation regime classifier reads back from CPI plus PCE plus breakevens to label the macro regime; the regime conditional on CPI is therefore partly tautological. Goldilocks regimes typically map to CPI prints in 2-3% range; stagflation maps to 4%+; deflation maps to sub-2%.
The April 2026 setup has CPI at 3.3% headline, well above the Fed's 2% target but below the 9.1% June 2022 peak. The trend has been disinflationary from peak but the path has stalled in the 3-3.5% range since mid-2024. Iran war WTI premium ($95.85 vs pre-Iran $73 baseline) plus Trump tariffs adding roughly 0.7pp to headline are the two specific risk factors keeping CPI elevated.
What Drives Headline CPI Forecast Errors
Three structural issues drive headline CPI forecast errors. First, energy is roughly 7% of CPI weight but produces outsized variance. Oil shocks (1973, 1979, 2007-2008, 2022) dominate the headline print in their windows. The 2026 Iran premium adds 0.3-0.4pp to headline that no model could have predicted ex-ante.
Second, shelter is roughly 33% of CPI weight and follows owners-equivalent-rent methodology that lags actual rents by 12-18 months. The 2024-2025 disinflation has been delayed by shelter lag; the 2021-2022 acceleration was similarly delayed.
Third, tariff pass-through is uncertain. The 2025-2026 Trump tariff regime has produced first-order price level effects but the pass-through rate (how much importers absorb versus how much consumers pay) varies by sector.
How to Use This Forecast in Practice
For headline CPI, watch the Cleveland Fed nowcast as the highest-frequency real-time signal. Energy prices and shelter components are the two most-volatile inputs; sustained moves in either re-anchor the trajectory.
The cleanest cross-check is the relationship between CPI and core PCE (the Fed's preferred measure). When CPI runs hot but core PCE softens, the headline noise dominates; when both run hot, the disinflation regime is in question. The 68% band on headline CPI should be treated as 25%+ wider than the historical bootstrap implies because of the energy-and-tariff tail risks.
Frequently Asked Questions
What factors could push CPI (All Urban) higher?▾
The primary drivers that tend to lift CPI (All Urban) depend on the current macro regime. Inflation erodes purchasing power and forces central banks to tighten, squeezing equity multiples and increasing credit stress. Breakeven rates reveal what the bond market expects for future inflation, while CPI and PCE measure what consumers actually experience. Divergences between market expectations and realized prints create some of the highest-impact trading events of the year. Convex tracks these drivers live across the Inflation 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 CPI (All Urban) lower?▾
The same transmission channels that drive CPI (All Urban) 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 CPI (All Urban) 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 CPI (All Urban)?▾
Historical ranges for CPI (All Urban) 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 CPI (All Urban) chart page, which includes selectable time ranges up to five years and downloadable data.
How often is the CPI (All Urban) 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 CPI (All Urban) 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.