Based on current macro regime conditions and crypto fear & greed index's historical behaviour in similar regimes, the model projects 31.14 by 2026-12-31 ( +11.2% from 28 today). The 68% confidence range is -51.82 to 114.1; the wider 95% range is -131.47 to 193.75. Methodology below the headline.
Crypto Fear & Greed Index Forecast 2026
Quantitative analysis from 3,024 observations of Crypto Fear & Greed Index history, joined to four universal macro regime classifications. Numbers are computed, not narrated.
Regime Scan[01/04]
Δ = divergence from -1.3% unconditional all-history average
Performance by Window[02]
| WINDOW | N | ANN RET | ANN VOL | RET/VOL | HIT % | TOTAL |
|---|---|---|---|---|---|---|
| 1Y | 366 | -63.54% | 355.75% | -0.18 | 45.5% | -63.51% |
| 3Y | 1,095 | -19.11% | 289.11% | -0.07 | 44.3% | -47.06% |
| 5Y | 1,826 | 0.00% | 304.42% | 0.00 | 44.2% | 0.00% |
| 10Y | 3,024 | -1.26% | 375.38% | -0.00 | 44.8% | -10.00% |
| All | 3,024 | -1.26% | 375.38% | -0.00 | 44.8% | -10.00% |
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 Crypto Fear & Greed Index 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) | 526 | 0.81% | -6.58% | 22.14% | 0.00% | 48.7% |
| Normal (15-25) | 1,215 | 13.14% | 22.65% | 8.46% | -9.68% | 41.8% |
| Elevated (25-40) | 330 | 37.40% | 57.30% | 86.27% | 57.69% | 66.6% |
| Extreme (>40) | 39 | 108.92% | 198.56% | 478.29% | 535.71% | 89.7% |
| REGIME BUCKET | N | +30D | +90D | +1Y AVG | +1Y MED | HIT % |
|---|---|---|---|---|---|---|
| Inverted (<0bps) | 544 | 6.72% | 19.97% | 33.82% | 22.64% | 69.3% |
| Flat (0-100bps) | 1,318 | 19.79% | 26.11% | 44.25% | -7.69% | 44.0% |
| Steep (>100bps) | 209 | 15.25% | 20.12% | -21.81% | -46.15% | 19.1% |
| REGIME BUCKET | N | +30D | +90D | +1Y AVG | +1Y MED | HIT % |
|---|---|---|---|---|---|---|
| Tight (<350bps) | 930 | 11.31% | 9.74% | -1.03% | -17.24% | 33.3% |
| Normal (350-500bps) | 1,006 | 13.10% | 24.44% | 33.24% | 7.35% | 54.3% |
| Stressed (>500bps) | 229 | 47.22% | 73.41% | 151.22% | 83.33% | 73.4% |
| REGIME BUCKET | N | +30D | +90D | +1Y AVG | +1Y MED | HIT % |
|---|---|---|---|---|---|---|
| Weak (bottom tercile) | 173 | 5.72% | 55.95% | -12.73% | -23.91% | 18.5% |
| Neutral (middle) | 460 | 20.45% | -8.52% | -33.79% | -51.47% | 18.3% |
| Strong (top tercile) | 1,429 | 15.83% | 30.82% | 54.91% | 12.31% | 58.6% |
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 Crypto Fear & Greed Index; negative means it lags.
| ANCHOR | ROLE | PEAK LAG | PEAK CORR | ZERO-LAG | RELATIONSHIP |
|---|---|---|---|---|---|
| 10Y-2Y Yield Spread | Recession leader | +8d | 0.139 | 0.002 | weak |
| VIX | Volatility leader | +1d | -0.082 | -0.032 | weak |
| HY OAS Spread | Credit risk leader | 0d | -0.063 | -0.063 | weak |
| Baa-10Y Spread | Credit risk (slow) | +20d | 0.060 | -0.050 | weak |
| Initial Jobless Claims | Labor leader | +40d | 0.058 | -0.007 | weak |
| 10Y Treasury Yield | Discount-rate driver | -4d | -0.051 | 0.011 | weak |
| NFCI | Financial conditions | +18d | 0.049 | -0.026 | weak |
| Trade-Weighted Dollar | FX driver | +6d | 0.047 | -0.039 | weak |
| Copper | Global growth proxy | +17d | -0.042 | 0.030 | 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 Crypto Fear & Greed Index 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 |
|---|---|---|---|---|
| Apr 17, 2025 | 30.0000 | 146.67% | 133.33% | -23.33% |
| Sep 9, 2024 | 26.0000 | 88.46% | 200.00% | 173.08% |
| Jan 11, 2023 | 26.0000 | 84.62% | 161.54% | 80.77% |
| Oct 11, 2022 | 24.0000 | -8.33% | 4.17% | 104.17% |
| Jul 10, 2022 | 24.0000 | 75.00% | 0.00% | 162.50% |
Worst Historical Drawdown[07]
Cross-Asset Correlations · 1Y[08]
Largest Single-Period Moves[09]
- Aug 23, 2019560.00%
- Feb 7, 2018350.00%
- Feb 3, 2018166.67%
- Mar 1, 2022155.00%
- Aug 9, 2024140.00%
- Aug 14, 2019-75.56%
- Jul 15, 2019-73.77%
- Aug 21, 2019-71.79%
- Jul 28, 2019-65.96%
- Sep 25, 2019-61.54%
Calendar-Month Seasonality[10]
Average single-period return aggregated by the calendar month in which the period ended.
| MONTH | AVG RETURN | HIT % | N |
|---|---|---|---|
| January | 1.78% | 44.4% | 248 |
| February | 2.65% | 41.9% | 253 |
| March | 2.36% | 45.2% | 279 |
| April | 2.78% | 45.3% | 267 |
| May | 1.09% | 44.2% | 265 |
| June | 1.88% | 47.9% | 240 |
| July | 3.45% | 47.2% | 248 |
| August | 2.67% | 41.1% | 248 |
| September | 1.46% | 45.4% | 240 |
| October | 2.35% | 45.3% | 247 |
| November | 0.93% | 48.8% | 240 |
| December | 1.01% | 41.5% | 248 |
N = 3,024 OBS · GENERATED 2026-05-17 18:30Z
Forecast Approach
trend extrapolation: Near-term trajectory extrapolation adjusted for mean-reversion tendencies and overhead resistance levels from technical analysis.
Key Drivers & Risks
- •Price momentum
- •Institutional flows
- •Retail sentiment
- •Contrarian signals
Historical Volatility
Moderate: sentiment oscillates around extremes
Frequently Asked Questions
What factors could push Crypto Fear & Greed Index higher?▾
The primary drivers that tend to lift Crypto Fear & Greed Index depend on the current macro regime. Positioning data reveals what the market is actually doing, as opposed to what it says it is doing. FINRA margin debt peaked ahead of every major bear market cycle of the last 40 years, while extreme readings in the AAII bull-bear spread are classic contrarian signals. CFTC commitments of traders separates speculative from commercial flow, identifying when large specs are overextended in either direction. Convex tracks these drivers live across the Sentiment & Positioning 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 Crypto Fear & Greed Index lower?▾
The same transmission channels that drive Crypto Fear & Greed Index 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 Crypto Fear & Greed Index 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 Crypto Fear & Greed Index?▾
Historical ranges for Crypto Fear & Greed Index 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 Crypto Fear & Greed Index chart page, which includes selectable time ranges up to five years and downloadable data.
How often is the Crypto Fear & Greed Index 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 Crypto Fear & Greed Index 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.