Based on current macro regime conditions and fed reverse repo liabilities's historical behaviour in similar regimes, the model projects 461,197.94 by 2026-12-31 ( +41.3% from 326,347 today). The 68% confidence range is 254,844.52 to 667,551.36; the wider 95% range is 56,745.23 to 865,650.65. Methodology below the headline.
Fed Reverse Repo Liabilities Forecast 2026
Quantitative analysis from 1,222 observations of Fed Reverse Repo Liabilities history, joined to four universal macro regime classifications. Numbers are computed, not narrated.
Regime Scan[01/04]
Δ = divergence from +12.2% unconditional all-history average
Performance by Window[02]
| WINDOW | N | ANN RET | ANN VOL | RET/VOL | HIT % | TOTAL |
|---|---|---|---|---|---|---|
| 1Y | 53 | -37.25% | 61.66% | -0.60 | 46.2% | -37.15% |
| 3Y | 157 | -50.04% | 68.90% | -0.73 | 39.7% | -87.44% |
| 5Y | 261 | -9.00% | 62.01% | -0.15 | 47.7% | -37.50% |
| 10Y | 522 | 0.42% | 69.03% | 0.01 | 48.2% | 4.31% |
| All | 1,222 | 12.24% | 79.35% | 0.15 | 49.9% | 1389.83% |
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 Fed Reverse Repo Liabilities 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) | 431 | 1.92% | 3.89% | 11.84% | 5.92% | 56.0% |
| Normal (15-25) | 586 | 5.07% | 18.90% | 58.76% | 19.18% | 69.6% |
| Elevated (25-40) | 158 | 3.44% | 11.54% | 83.02% | 8.33% | 60.9% |
| Extreme (>40) | 35 | -7.38% | -17.33% | -0.69% | -20.26% | 11.4% |
| REGIME BUCKET | N | +30D | +90D | +1Y AVG | +1Y MED | HIT % |
|---|---|---|---|---|---|---|
| Inverted (<0bps) | 160 | -3.08% | -9.53% | -26.33% | -35.36% | 29.4% |
| Flat (0-100bps) | 436 | 0.21% | 2.76% | 61.38% | 6.50% | 57.6% |
| Steep (>100bps) | 610 | 7.22% | 22.95% | 48.46% | 17.50% | 72.8% |
| REGIME BUCKET | N | +30D | +90D | +1Y AVG | +1Y MED | HIT % |
|---|---|---|---|---|---|---|
| Tight (<350bps) | 196 | 4.88% | 19.36% | 45.22% | -8.92% | 47.9% |
| Normal (350-500bps) | 279 | 0.91% | 8.43% | 42.01% | -24.02% | 31.5% |
| Stressed (>500bps) | 114 | 3.22% | 5.65% | 101.73% | 34.87% | 81.6% |
| REGIME BUCKET | N | +30D | +90D | +1Y AVG | +1Y MED | HIT % |
|---|---|---|---|---|---|---|
| Weak (bottom tercile) | 209 | 8.81% | 40.94% | 109.15% | 51.33% | 85.2% |
| Neutral (middle) | 256 | 4.52% | 15.09% | 71.09% | 12.10% | 70.1% |
| Strong (top tercile) | 529 | 1.21% | 0.36% | 14.26% | -11.12% | 43.7% |
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 Fed Reverse Repo Liabilities; negative means it lags.
| ANCHOR | ROLE | PEAK LAG | PEAK CORR | ZERO-LAG | RELATIONSHIP |
|---|---|---|---|---|---|
| NFCI | Financial conditions | +46d | 0.244 | -0.001 | leads target by 46d |
| Initial Jobless Claims | Labor leader | +53d | 0.207 | 0.206 | leads target by 53d |
| HY OAS Spread | Credit risk leader | +2d | 0.127 | 0.044 | weak |
| VIX | Volatility leader | +2d | 0.099 | -0.010 | weak |
| Baa-10Y Spread | Credit risk (slow) | +2d | 0.097 | 0.013 | weak |
| 10Y Treasury Yield | Discount-rate driver | +44d | -0.085 | -0.037 | weak |
| Trade-Weighted Dollar | FX driver | -9d | -0.083 | 0.005 | weak |
| Copper | Global growth proxy | -9d | 0.069 | 0.014 | weak |
| 10Y-2Y Yield Spread | Recession leader | -55d | -0.054 | -0.022 | 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 Fed Reverse Repo Liabilities 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 24, 2021 | 234444.0000 | 65.63% | 418.83% | 776.36% |
| Jun 10, 2020 | 240814.0000 | -10.86% | -22.17% | 199.37% |
| Mar 11, 2020 | 233275.0000 | 24.01% | -7.98% | -16.94% |
| Mar 27, 2019 | 241600.0000 | 8.02% | 17.61% | 48.64% |
| Dec 26, 2018 | 244820.0000 | 1.39% | 6.60% | 3.54% |
Worst Historical Drawdown[07]
Cross-Asset Correlations · 1Y[08]
Largest Single-Period Moves[09]
- Sep 30, 2015111.02%
- Jan 1, 2014108.87%
- Sep 24, 200894.44%
- Dec 31, 201470.61%
- Jan 1, 202556.87%
- Oct 7, 2015-55.91%
- Jan 7, 2015-52.64%
- Jan 8, 2014-52.29%
- Jan 8, 2025-35.67%
- Apr 8, 2020-32.35%
Calendar-Month Seasonality[10]
Average single-period return aggregated by the calendar month in which the period ended.
| MONTH | AVG RETURN | HIT % | N |
|---|---|---|---|
| January | -1.82% | 33.0% | 106 |
| February | 0.40% | 50.5% | 97 |
| March | 1.68% | 54.7% | 106 |
| April | 0.07% | 50.0% | 104 |
| May | 1.15% | 51.5% | 103 |
| June | 1.61% | 51.5% | 99 |
| July | -0.89% | 42.2% | 102 |
| August | 0.95% | 58.8% | 102 |
| September | 3.48% | 54.1% | 98 |
| October | -1.18% | 45.1% | 102 |
| November | 0.02% | 48.5% | 99 |
| December | 3.84% | 59.2% | 103 |
N = 1,222 OBS · GENERATED 2026-05-18 11:30Z
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.
Key Drivers & Risks
- •Macro regime
- •Monetary policy
- •Risk appetite
Historical Volatility
Moderate
Frequently Asked Questions
What factors could push Fed Reverse Repo Liabilities higher?▾
The primary drivers that tend to lift Fed Reverse Repo Liabilities depend on the current macro regime. The Fed balance sheet and Treasury General Account together determine the volume of reserves circulating in the banking system. Nowcasts from Atlanta, New York, and Cleveland Fed staff provide real-time estimates of GDP and inflation, often weeks ahead of official releases. These operational metrics are what actually moves rates and reserves, as opposed to the policy statements that describe intent. Convex tracks these drivers live across the Fed Balance Sheet Detail 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 Fed Reverse Repo Liabilities lower?▾
The same transmission channels that drive Fed Reverse Repo Liabilities 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 Fed Reverse Repo Liabilities 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 Fed Reverse Repo Liabilities?▾
Historical ranges for Fed Reverse Repo Liabilities 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 Fed Reverse Repo Liabilities chart page, which includes selectable time ranges up to five years and downloadable data.
How often is the Fed Reverse Repo Liabilities 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 Fed Reverse Repo Liabilities 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.