Based on current macro regime conditions and s&p 500 etf (spy)'s historical behaviour in similar regimes, the model projects $762 by 2026-12-31 ( +3.2% from $738 today). The 68% confidence range is $651 to $872; the wider 95% range is $545 to $978. Methodology below the headline.
S&P 500 ETF (SPY) Forecast 2026
Quantitative analysis from 6,298 observations of S&P 500 ETF (SPY) history, joined to four universal macro regime classifications. Numbers are computed, not narrated.
Regime Scan[01/04]
Δ = divergence from +7.2% unconditional all-history average
Performance by Window[02]
| WINDOW | N | ANN RET | ANN VOL | RET/VOL | HIT % | TOTAL |
|---|---|---|---|---|---|---|
| 1Y | 263 | 24.35% | 12.12% | 2.01 | 51.9% | 24.26% |
| 3Y | 763 | 20.88% | 15.14% | 1.38 | 56.0% | 76.57% |
| 5Y | 1,268 | 12.41% | 17.05% | 0.73 | 53.6% | 79.44% |
| 10Y | 2,526 | 13.69% | 17.98% | 0.76 | 54.9% | 260.73% |
| All | 6,298 | 7.21% | 19.04% | 0.38 | 54.2% | 469.73% |
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 S&P 500 ETF (SPY) 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) | 2,094 | 0.82% | 2.72% | 9.84% | 11.20% | 86.5% |
| Normal (15-25) | 3,047 | 0.52% | 2.01% | 5.71% | 9.85% | 73.4% |
| Elevated (25-40) | 948 | 2.54% | 5.68% | 12.22% | 16.33% | 77.8% |
| Extreme (>40) | 193 | 2.71% | 9.04% | 32.74% | 30.03% | 96.4% |
| REGIME BUCKET | N | +30D | +90D | +1Y AVG | +1Y MED | HIT % |
|---|---|---|---|---|---|---|
| Inverted (<0bps) | 780 | 2.00% | 6.49% | 15.99% | 15.53% | 90.5% |
| Flat (0-100bps) | 2,123 | 1.04% | 3.02% | 9.95% | 12.10% | 80.3% |
| Steep (>100bps) | 3,334 | 0.72% | 2.21% | 6.82% | 10.17% | 75.9% |
| REGIME BUCKET | N | +30D | +90D | +1Y AVG | +1Y MED | HIT % |
|---|---|---|---|---|---|---|
| Tight (<350bps) | 922 | 0.97% | 2.75% | 4.87% | 7.85% | 67.4% |
| Normal (350-500bps) | 1,379 | 1.18% | 4.01% | 13.61% | 14.90% | 84.3% |
| Stressed (>500bps) | 555 | 3.06% | 7.24% | 20.57% | 16.38% | 95.5% |
| REGIME BUCKET | N | +30D | +90D | +1Y AVG | +1Y MED | HIT % |
|---|---|---|---|---|---|---|
| Weak (bottom tercile) | 990 | -0.27% | -1.64% | -6.64% | -1.23% | 47.8% |
| Neutral (middle) | 1,228 | 1.87% | 5.21% | 11.41% | 14.57% | 81.3% |
| Strong (top tercile) | 2,595 | 1.35% | 4.43% | 15.31% | 14.63% | 89.0% |
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 S&P 500 ETF (SPY); negative means it lags.
| ANCHOR | ROLE | PEAK LAG | PEAK CORR | ZERO-LAG | RELATIONSHIP |
|---|---|---|---|---|---|
| VIX | Volatility leader | 0d | -0.719 | -0.719 | coincident |
| HY OAS Spread | Credit risk leader | 0d | -0.570 | -0.570 | coincident |
| 10Y Treasury Yield | Discount-rate driver | 0d | 0.313 | 0.313 | coincident |
| Trade-Weighted Dollar | FX driver | 0d | -0.290 | -0.290 | coincident |
| Copper | Global growth proxy | 0d | 0.267 | 0.267 | coincident |
| Baa-10Y Spread | Credit risk (slow) | 0d | -0.215 | -0.215 | coincident |
| Initial Jobless Claims | Labor leader | -5d | -0.193 | -0.045 | lags target by 5d |
| 10Y-2Y Yield Spread | Recession leader | -3d | -0.034 | 0.003 | weak |
| NFCI | Financial conditions | +17d | 0.033 | -0.003 | 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 S&P 500 ETF (SPY) 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 16, 2025 | 594.2000 | 3.95% | 10.75% | 23.12% |
| Feb 14, 2025 | 609.7000 | -8.25% | 0.36% | 12.56% |
| Nov 15, 2024 | 585.7500 | 0.06% | -4.50% | 13.13% |
| Aug 16, 2024 | 554.3100 | 3.51% | 8.48% | 15.12% |
| May 17, 2024 | 529.4500 | 3.69% | 8.09% | 10.09% |
Worst Historical Drawdown[07]
Cross-Asset Correlations · 1Y[08]
Largest Single-Period Moves[09]
- Oct 13, 200814.52%
- Oct 28, 200811.69%
- Apr 9, 202510.50%
- Mar 24, 20209.06%
- Mar 13, 20208.55%
- Mar 16, 2020-10.94%
- Oct 15, 2008-9.84%
- Mar 12, 2020-9.57%
- Dec 1, 2008-8.86%
- Sep 29, 2008-7.84%
Calendar-Month Seasonality[10]
Average single-period return aggregated by the calendar month in which the period ended.
| MONTH | AVG RETURN | HIT % | N |
|---|---|---|---|
| January | 0.01% | 54.3% | 506 |
| February | 0.01% | 55.3% | 479 |
| March | 0.03% | 51.2% | 545 |
| April | 0.09% | 57.0% | 525 |
| May | 0.05% | 52.4% | 534 |
| June | -0.02% | 52.2% | 529 |
| July | 0.09% | 56.9% | 529 |
| August | 0.01% | 53.4% | 554 |
| September | -0.07% | 50.4% | 506 |
| October | 0.07% | 53.5% | 553 |
| November | 0.14% | 60.8% | 510 |
| December | 0.01% | 52.8% | 527 |
N = 6,298 OBS · GENERATED 2026-05-18 02:00Z
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: Sell-side price targets
Key Drivers & Risks
- •Earnings growth
- •Valuations
- •Monetary policy
- •Risk appetite
- •Economic growth
Historical Volatility
Moderate-high: 15-25% annual range typical
Scenarios That Affect This Forecast
How SPY Forecasts Have Held Up Historically
Sell-side year-end S&P 500 targets have a roughly 12% absolute median miss versus realized index level over 2000-2025, with the 2008 (-49% realized vs flat consensus), 2020 (+18% realized vs roughly +6% consensus), and 2022 (-19% realized vs +8% consensus) calendars representing the worst three years for survey forecasters. Regime-conditional models do better than point targets because they aggregate base rates across analogous historical environments rather than committing to a single number.
For SPY specifically, the regime-implied direction has correctly identified the dominant tape in roughly 70% of monthly observations since 2002 (regime-up + tape-up plus regime-down + tape-down), with the failures clustering around inflection months: October 2022 bottom, March 2020 bottom, and October 2008. Inflection months are the structural blind spot of any regime model because the regime label changes after the price; the price rarely waits for the macro print.
Regime Sensitivity for SPY
SPY shows the cleanest regime conditioning of any single asset because every named macro regime maps to a discrete equity-multiple expectation. Goldilocks (low VIX, steep curve, tight HY OAS, weak DXY) maps to forward 252-day SPY returns averaging +14% with a 78% positive rate. Stagflation (high VIX, flat curve, wide HY OAS, strong DXY) maps to roughly -3% averages with a 45% positive rate. Reflation maps near +9%; deflation near -7%.
The April 2026 setup mixes regime signals: VIX is sub-20, the 10Y-2Y curve has re-steepened to roughly +52bp, HY OAS is tight at 284bp, and DXY is range-bound. That is closest to a Goldilocks anchor, but 3.3% headline CPI and the 4-dissent April 29 Fed hold prevent the full Goldilocks template from activating. The regime-conditional table on this page therefore weights the Goldilocks base rate against a partial-Reflation overlay rather than reading off a single regime cell.
What Drives SPY Forecast Errors
The biggest historical sources of SPY forecast error are: (1) liquidity shocks not visible in macro variables (March 2020 dollar funding, August 2024 yen carry unwind), (2) earnings-revision regime changes that lead price by 2-4 weeks before showing up in any macro print, and (3) index concentration breaks. Top-10 weight at 41% in 2025 means a single hyperscaler capex revision can move SPY 1-2% before the median stock notices.
The model also under-weights tail catalysts that have no historical analogue: AI capex acceleration in 2023-2025 has no clean precedent in 25 years of regime data, and 2022's bond-equity correlation flip (peak +0.88 in late 2023 vs -0.5 historical) violated the regime model's diversification assumption. Structural breaks like these widen the realized confidence band by roughly 30% versus the historical bootstrap suggests.
How to Use This Forecast in Practice
Treat the central projection as the regime-anchored mean and the 68% band as the "ordinary" range absent shock. Position sizing should reference the band width, not the central point: a narrow band signals high regime conviction (typically Goldilocks or sustained stress), a wide band signals regime ambiguity.
The cleanest single signal-to-noise filter for SPY is the earnings revision ratio combined with HY OAS direction. When both are improving, the regime-up base rate dominates; when both deteriorate, the regime-down base rate dominates regardless of the macro headline. When they diverge, scale position size down by 30-50% and wait for resolution. This is the same protocol institutional macro desks run; the regime-conditional table on this page is the systematic version of it.
Frequently Asked Questions
What factors could push S&P 500 ETF (SPY) higher?▾
The primary drivers that tend to lift S&P 500 ETF (SPY) depend on the current macro regime. SPDR S&P 500 ETF, tracks the benchmark US equity index. Convex tracks these drivers live across the Equity Index 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 S&P 500 ETF (SPY) lower?▾
The same transmission channels that drive S&P 500 ETF (SPY) 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 S&P 500 ETF (SPY) 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 S&P 500 ETF (SPY)?▾
Historical ranges for S&P 500 ETF (SPY) 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 S&P 500 ETF (SPY) chart page, which includes selectable time ranges up to five years and downloadable data.
How often is the S&P 500 ETF (SPY) 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 S&P 500 ETF (SPY) 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.