Based on current macro regime conditions and core cpi (ex food/energy)'s historical behaviour in similar regimes, the model projects 341.47 by 2026-12-31 ( +1.8% from 335.42 today). The 68% confidence range is 340.08 to 342.86; the wider 95% range is 338.74 to 344.19. Methodology below the headline.
Core CPI (ex Food/Energy) Forecast 2026
Quantitative analysis from 298 observations of Core CPI (ex Food/Energy) 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 | 2.75% | 0.24% | 11.32 | 100.0% | 2.74% |
| 3Y | 35 | 3.01% | 0.29% | 10.30 | 100.0% | 9.03% |
| 5Y | 60 | 4.15% | 0.56% | 7.41 | 100.0% | 22.57% |
| 10Y | 120 | 3.13% | 0.63% | 4.99 | 96.6% | 36.05% |
| All | 298 | 2.40% | 0.48% | 5.02 | 97.0% | 80.33% |
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 Core CPI (ex Food/Energy) 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 | 0.19% | 0.74% | 2.21% | 2.20% | 100.0% |
| Normal (15-25) | 90 | 0.21% | 0.88% | 2.61% | 2.11% | 100.0% |
| Elevated (25-40) | 32 | 0.24% | 0.90% | 2.71% | 2.01% | 100.0% |
| 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 | 0.29% | 1.11% | 3.19% | 3.14% | 100.0% |
| Flat (0-100bps) | 62 | 0.22% | 0.93% | 2.77% | 2.30% | 100.0% |
| Steep (>100bps) | 100 | 0.17% | 0.70% | 2.11% | 1.90% | 100.0% |
| REGIME BUCKET | N | +30D | +90D | +1Y AVG | +1Y MED | HIT % |
|---|---|---|---|---|---|---|
| Tight (<350bps) | 24 | 0.31% | 1.23% | 3.87% | 2.89% | 100.0% |
| Normal (350-500bps) | 45 | 0.25% | 1.07% | 3.09% | 2.35% | 100.0% |
| Stressed (>500bps) | 18 | 0.23% | 0.90% | 2.78% | 2.24% | 100.0% |
| REGIME BUCKET | N | +30D | +90D | +1Y AVG | +1Y MED | HIT % |
|---|---|---|---|---|---|---|
| Weak (bottom tercile) | 34 | 0.18% | 0.79% | 2.43% | 2.14% | 100.0% |
| Neutral (middle) | 38 | 0.21% | 0.85% | 2.48% | 1.83% | 100.0% |
| Strong (top tercile) | 77 | 0.23% | 0.91% | 2.68% | 2.26% | 100.0% |
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 Core CPI (ex Food/Energy); negative means it lags.
| ANCHOR | ROLE | PEAK LAG | PEAK CORR | ZERO-LAG | RELATIONSHIP |
|---|---|---|---|---|---|
| Initial Jobless Claims | Labor leader | 0d | -0.379 | -0.379 | coincident |
| 10Y-2Y Yield Spread | Recession leader | -28d | 0.303 | -0.012 | lags target by 28d |
| HY OAS Spread | Credit risk leader | +17d | -0.258 | -0.201 | leads target by 17d |
| U-Mich Consumer Sentiment | Survey leader | -45d | -0.242 | 0.057 | lags target by 45d |
| 10Y Treasury Yield | Discount-rate driver | 0d | 0.241 | 0.241 | coincident |
| Baa-10Y Spread | Credit risk (slow) | 0d | -0.197 | -0.197 | coincident |
| Trade-Weighted Dollar | FX driver | -57d | -0.144 | -0.071 | weak |
| NFCI | Financial conditions | +25d | -0.136 | 0.018 | weak |
| Copper | Global growth proxy | -8d | -0.128 | 0.039 | weak |
| VIX | Volatility leader | +14d | 0.128 | -0.029 | 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 Core CPI (ex Food/Energy) 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 | 325.6900 | 0.24% | 0.92% | 2.99% |
| Dec 1, 2024 | 323.2590 | 0.43% | 0.99% | 2.95% |
| Sep 1, 2024 | 320.7320 | 0.31% | 1.22% | 3.02% |
| Jun 1, 2024 | 318.3900 | 0.17% | 1.05% | 2.91% |
| Mar 1, 2024 | 316.7920 | 0.27% | 0.68% | 2.81% |
Worst Historical Drawdown[07]
Largest Single-Period Moves[09]
- Apr 1, 20210.81%
- Jun 1, 20210.79%
- Oct 1, 20210.70%
- Jun 1, 20220.68%
- May 1, 20210.66%
- Apr 1, 2020-0.49%
- May 1, 2020-0.13%
- Mar 1, 2020-0.12%
- Jan 1, 2010-0.11%
- Mar 1, 2017-0.02%
Calendar-Month Seasonality[10]
Average single-period return aggregated by the calendar month in which the period ended.
| MONTH | AVG RETURN | HIT % | N |
|---|---|---|---|
| January | 0.23% | 96.0% | 25 |
| February | 0.20% | 100.0% | 25 |
| March | 0.18% | 88.0% | 25 |
| April | 0.19% | 92.0% | 25 |
| May | 0.19% | 95.8% | 24 |
| June | 0.20% | 100.0% | 24 |
| July | 0.20% | 100.0% | 25 |
| August | 0.19% | 100.0% | 25 |
| September | 0.20% | 100.0% | 25 |
| October | 0.22% | 100.0% | 24 |
| November | 0.20% | 96.0% | 25 |
| December | 0.18% | 96.0% | 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
How Core CPI Forecasts Have Held Up Historically
Core CPI (excluding food and energy) has a better track record than headline because the volatile components are stripped out. Forecasters have still missed turning points: the 2021-2022 acceleration from 1.6% to 6.6% (September 2022 peak) was under-predicted by every major bank; the 2023-2024 disinflation from peak to 3.2% was correctly captured on direction.
Regime-conditional models on core CPI achieve approximately 65% directional accuracy. The print is highly persistent month-over-month, which makes mean-reversion forecasts work better than turning-point forecasts.
Regime Sensitivity for Core CPI
Core CPI is a slow-moving regime variable. Trends persist for multiple quarters before shifting. Goldilocks regimes anchor core CPI in 2-2.5% range; stagflation maps to 4%+; deflation maps to sub-1%.
The April 2026 setup has core CPI at 2.6% (down from peak but still above 2% target). The supercore measure (services ex-shelter, the Fed's most-watched metric) is at approximately 4%, materially above target. The gap between core CPI and supercore captures the disinflation challenge: shelter is mean-reverting while supercore services prices are sticky.
What Drives Core CPI Forecast Errors
Three structural issues drive core CPI forecast errors. First, supercore services (services ex-shelter) is dominated by wages plus services-margin dynamics. Wage growth above 4% (currently 4.0% on Atlanta Fed Wage Tracker) is inconsistent with 2% inflation; the regime model captures the level but not the persistence. Persistent supercore prints near 4% are the dominant reason core CPI has been stuck above 2.5% since mid-2024 despite shelter normalization.
Second, shelter mean-reversion timing is uncertain. The OER methodology lag means shelter inflation continues falling even after market rents stabilize, which creates a mechanical disinflation that ends abruptly when the lag normalizes. The 2024-2025 shelter glide path was relatively smooth; the next leg (2026 onward) depends on whether market rents have re-accelerated, which the BLS print won't capture for another 12-18 months.
Third, idiosyncratic categories (used cars, airfares, medical services) produce noise that swamps signal in any single month. Core CPI ex-volatile-categories (the trimmed-mean PCE analogue from the Cleveland Fed) is a cleaner trend indicator but isn't the print the Fed nominally targets.
How to Use This Forecast in Practice
For core CPI, watch the supercore services component (the Fed's primary focus) and the shelter component (the largest weight). Supercore stickiness above 3% argues for delayed cuts; shelter normalization below 4% argues for faster disinflation. The two together form the highest-resolution real-time read on whether the disinflation regime is intact or stalling.
The cleanest cross-check is the gap between core CPI and core PCE. Core PCE typically runs 30-50bp below core CPI because of methodology differences (chain-weighted, hospital weights). When the gap widens above 50bp, core CPI is overstating inflation pressure relative to the Fed's preferred gauge; when it narrows below 30bp, core CPI is more representative.
The 68% band on core CPI is the tightest of any inflation series because of the high persistence and low monthly variance. Treat single-month surprises as noise unless they confirm a multi-month trend.
Frequently Asked Questions
What factors could push Core CPI (ex Food/Energy) higher?▾
The primary drivers that tend to lift Core CPI (ex Food/Energy) 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 Core CPI (ex Food/Energy) lower?▾
The same transmission channels that drive Core CPI (ex Food/Energy) 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 Core CPI (ex Food/Energy) 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 Core CPI (ex Food/Energy)?▾
Historical ranges for Core CPI (ex Food/Energy) 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 Core CPI (ex Food/Energy) chart page, which includes selectable time ranges up to five years and downloadable data.
How often is the Core CPI (ex Food/Energy) 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 Core CPI (ex Food/Energy) 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.