Based on current macro regime conditions and 10y-2y yield spread's historical behaviour in similar regimes, the model projects 106 bps by 2026-12-31 ( +111.8% from 50 bps today). The 68% confidence range is -32 bps to 244 bps; the wider 95% range is -165 bps to 377 bps. Methodology below the headline.
10Y-2Y Yield Spread Forecast 2026
Quantitative analysis from 6,250 observations of 10Y-2Y Yield Spread history, joined to four universal macro regime classifications. Numbers are computed, not narrated.
Regime Scan[01/03]
Δ = divergence from -2.9% unconditional all-history average
Performance by Window[02]
| WINDOW | N | ANN RET | ANN VOL | RET/VOL | HIT % | TOTAL |
|---|---|---|---|---|---|---|
| 1Y | 251 | 2.04% | 79.39% | 0.03 | 37.2% | 2.04% |
| 3Y | 750 | 43.64% | 455.53% | 0.10 | 42.2% | 196.15% |
| 5Y | 1,250 | -19.53% | 478.62% | -0.04 | 41.8% | -66.22% |
| 10Y | 2,501 | -6.32% | 374.82% | -0.02 | 40.8% | -47.92% |
| All | 6,250 | -2.89% | 347.69% | -0.01 | 41.7% | -51.92% |
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 10Y-2Y Yield Spread 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) | 2,082 | 11.53% | 55.51% | 263.11% | -24.14% | 39.0% |
| Normal (15-25) | 3,026 | 9.85% | 16.24% | 73.50% | -2.50% | 46.4% |
| Elevated (25-40) | 939 | -13.55% | -19.80% | -23.51% | 6.64% | 61.2% |
| Extreme (>40) | 191 | 4.68% | 18.52% | 76.52% | 46.99% | 90.1% |
| REGIME BUCKET | N | +30D | +90D | +1Y AVG | +1Y MED | HIT % |
|---|---|---|---|---|---|---|
| Tight (<350bps) | 918 | 29.72% | 43.62% | 90.09% | -51.16% | 45.6% |
| Normal (350-500bps) | 1,369 | 4.91% | 6.31% | 48.85% | -7.14% | 46.5% |
| Stressed (>500bps) | 552 | -20.23% | -25.07% | -11.27% | 5.13% | 59.5% |
| REGIME BUCKET | N | +30D | +90D | +1Y AVG | +1Y MED | HIT % |
|---|---|---|---|---|---|---|
| Weak (bottom tercile) | 992 | 36.11% | 163.70% | 574.14% | -2.48% | 45.0% |
| Neutral (middle) | 1,230 | 2.55% | -8.71% | -10.21% | -8.17% | 38.6% |
| Strong (top tercile) | 2,596 | 7.47% | 17.17% | 64.97% | 8.54% | 54.2% |
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 10Y-2Y Yield Spread; negative means it lags.
| ANCHOR | ROLE | PEAK LAG | PEAK CORR | ZERO-LAG | RELATIONSHIP |
|---|---|---|---|---|---|
| 10Y Treasury Yield | Discount-rate driver | 0d | 0.108 | 0.108 | weak |
| Baa-10Y Spread | Credit risk (slow) | 0d | 0.097 | 0.097 | weak |
| HY OAS Spread | Credit risk leader | +3d | 0.070 | 0.045 | weak |
| Initial Jobless Claims | Labor leader | -9d | 0.057 | -0.014 | weak |
| VIX | Volatility leader | +20d | -0.051 | 0.015 | weak |
| Copper | Global growth proxy | +47d | -0.044 | -0.004 | weak |
| Trade-Weighted Dollar | FX driver | +19d | -0.035 | -0.020 | weak |
| NFCI | Financial conditions | -59d | 0.029 | 0.005 | weak |
| U-Mich Consumer Sentiment | Survey leader | 0d | 0.000 | 0.000 | 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 10Y-2Y Yield Spread 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 |
|---|---|---|---|---|
| May 14, 2025 | 0.4800 | 16.67% | 22.92% | n/a |
| Feb 4, 2025 | 0.3100 | -16.13% | 45.16% | 138.71% |
| Jan 26, 2022 | 0.7200 | -63.89% | -56.94% | -195.83% |
| Aug 23, 2021 | 1.0200 | 23.53% | -16.67% | -131.37% |
| Feb 1, 2021 | 0.9800 | 50.00% | 36.73% | -35.71% |
Worst Historical Drawdown[07]
Cross-Asset Correlations · 1Y[08]
Largest Single-Period Moves[09]
- Apr 5, 2022400.00%
- Sep 6, 2024400.00%
- Mar 30, 2006300.00%
- Aug 15, 2019300.00%
- Apr 6, 2022266.67%
- Jul 17, 2006-400.00%
- Mar 22, 2006-300.00%
- Sep 5, 2024-300.00%
- Apr 1, 2022-225.00%
- Jul 13, 2022-214.29%
Calendar-Month Seasonality[10]
Average single-period return aggregated by the calendar month in which the period ended.
| MONTH | AVG RETURN | HIT % | N |
|---|---|---|---|
| January | 0.29% | 40.8% | 507 |
| February | -0.96% | 40.5% | 479 |
| March | 0.79% | 42.4% | 545 |
| April | 1.99% | 42.7% | 524 |
| May | -0.73% | 39.7% | 524 |
| June | -0.65% | 42.5% | 527 |
| July | -1.91% | 40.6% | 527 |
| August | -0.55% | 37.4% | 548 |
| September | 1.44% | 46.3% | 505 |
| October | 0.51% | 46.5% | 529 |
| November | -0.25% | 36.7% | 488 |
| December | 0.35% | 43.5% | 527 |
N = 6,250 OBS · GENERATED 2026-05-18 07:00Z
Forecast Approach
scenario weighted: We aggregate probability-weighted outcomes across active tracked scenarios, each with historical base rates and current heat scores. The projection above is the sample-weighted central estimate across current macro regime anchors; the scenario list below adds qualitative context.
Consensus source: Fed dot plot and futures market
Key Drivers & Risks
- •Federal Reserve policy
- •Inflation expectations
- •Economic growth
- •Global yield differentials
- •Treasury supply
Historical Volatility
Moderate: typically 50-150bps annual range
Scenarios That Affect This Forecast
How 10Y-2Y Curve Forecasts Have Held Up Historically
Yield curve forecasts have historically been better than absolute level forecasts on direction (curves mean-revert from extremes) but poor on magnitude and timing. The 2022-2024 inversion was the deepest (-108bp peak July 2023) and longest (26 months) in modern history; consensus targets in 2022 broadly missed the depth and almost universally missed the timing of the October 2024 re-steepening.
Regime-conditional models on the curve achieve roughly 65% directional accuracy on monthly windows. The curve is itself a regime variable in most classifiers, so the model reads back rather than predicts.
Regime Sensitivity for T10Y2Y
The 10Y-2Y curve is the cleanest single regime indicator. Steep positive curve (+100bp+) anchors goldilocks-and-reflation regimes; flat-to-inverted curve anchors stagflation-and-late-cycle regimes; sharply re-steepening curve after an inversion historically front-runs recession by 6-12 months.
The April 2026 setup has the curve at +52bp, re-steepened from -108bp peak inversion. The regime conditional reads the re-steepening as recession-flagging but the timing is uncertain (historical lead times vary from 6 to 18 months). The bull case (cuts arrive, growth holds) keeps the curve modestly positive without a hard recession; the bear case (cuts arrive but too late) takes the curve to bull-steepener territory as the long end rallies into a recession.
What Drives T10Y2Y Forecast Errors
Three structural issues drive curve forecast errors. First, term premium decomposition isn't typically in the regime classifier. The 10Y-2Y can steepen because the 10Y rises (bear steepener, hawkish) or because the 2Y falls (bull steepener, dovish). The regime read changes meaningfully depending on which leg drives the move; bull steepeners typically map to dovish regimes, bear steepeners to late-cycle hawkish regimes.
Second, the historical recession-lead-time after re-steepening is unstable. 2007-2008 had a 22-month lead; 2019-2020 had a 6-month lead (compressed by COVID); the 1989-1990 cycle had a 12-month lead. The model uses the average lead time but the realized lead is regime-dependent.
Third, the 10Y-3M curve and the 10Y-2Y curve sometimes give conflicting signals. The 10Y-3M is the academic preference (used by the New York Fed recession model); the 10Y-2Y is the trader preference. When they diverge, the regime read is ambiguous and short-term forecasts should be scaled down.
How to Use This Forecast in Practice
For T10Y2Y, the cleanest signal is the steepening composition. Bull steepener (long-end rallies, short-end falls more) signals dovish regime; bear steepener (long-end rises, short-end stable) signals hawkish-end-of-cycle regime. The 2024-2026 re-steepening has been mixed-character so far, with the 2Y declining as cuts price in while the 10Y has held above 4% on term-premium rebuild.
The 68% band on the curve forecast should be treated as moderately tight because the curve mean-reverts but with regime-shift risk that produces fat tails when the cycle inflects. Watch the 2Y direction first (Fed-driven), then the 10Y (term-premium-driven), then the spread. Cross-check against the 10Y-3M for confirmation; sustained agreement between the two curves raises conviction in either the recession or no-recession regime read.
Frequently Asked Questions
What factors could push 10Y-2Y Yield Spread higher?▾
The primary drivers that tend to lift 10Y-2Y Yield Spread depend on the current macro regime. Interest rates set the price of money and ripple through every asset class. An inverted yield curve has preceded every U.S. recession since the 1960s, making this the single most-watched corner of fixed income. Monitoring rate differentials, real yields, and forward expectations helps traders anticipate risk-on or risk-off regime shifts. Convex tracks these drivers live across the Yield Curve & Rates 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 10Y-2Y Yield Spread lower?▾
The same transmission channels that drive 10Y-2Y Yield Spread 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 10Y-2Y Yield Spread 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 10Y-2Y Yield Spread?▾
Historical ranges for 10Y-2Y Yield Spread 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 10Y-2Y Yield Spread chart page, which includes selectable time ranges up to five years and downloadable data.
How often is the 10Y-2Y Yield Spread 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.
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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.