Based on current macro regime conditions and credit card delinquency rate's historical behaviour in similar regimes, the model projects 2.92% by 2025-12-31 ( -0.5% from 2.94% today). The 68% confidence range is 2.75% to 3.10%; the wider 95% range is 2.57% to 3.27%. Methodology below the headline.
Credit Card Delinquency Rate Forecast 2026
Quantitative analysis from 98 observations of Credit Card Delinquency Rate 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 | 5 | -4.55% | 1.27% | -3.58 | 0.0% | -4.55% |
| 3Y | 12 | 6.54% | 9.02% | 0.73 | 45.5% | 19.03% |
| 5Y | 21 | 6.96% | 14.44% | 0.48 | 55.0% | 40.00% |
| 10Y | 40 | 3.26% | 12.82% | 0.25 | 64.1% | 36.74% |
| All | 98 | -2.17% | 12.18% | -0.18 | 44.3% | -41.20% |
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]
Historical Analogs[06]
Periods where Credit Card Delinquency Rate 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 1, 2023 | 2.7500 | 0.00% | 6.91% | 17.09% |
Worst Historical Drawdown[07]
Largest Single-Period Moves[09]
- Oct 1, 200817.50%
- Jan 1, 200915.43%
- Jul 1, 202212.02%
- Apr 1, 202311.34%
- Oct 1, 202210.24%
- Jul 1, 2020-18.78%
- Apr 1, 2021-15.43%
- Apr 1, 2010-11.76%
- Jan 1, 2021-10.48%
- Jul 1, 2010-10.20%
Calendar-Month Seasonality[10]
Average single-period return aggregated by the calendar month in which the period ended.
| MONTH | AVG RETURN | HIT % | N |
|---|---|---|---|
| January | 0.05% | 45.8% | 24 |
| April | -0.68% | 45.8% | 24 |
| July | -0.82% | 41.7% | 24 |
| October | -0.01% | 44.0% | 25 |
N = 98 OBS · GENERATED 2026-05-18 09:30Z
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
- •Default rates
- •Monetary policy
- •Economic growth
- •Risk appetite
- •Leverage levels
Historical Volatility
Asymmetric: tight in calm, explosive in stress
Scenarios That Affect This Forecast
Frequently Asked Questions
What factors could push Credit Card Delinquency Rate higher?▾
The primary drivers that tend to lift Credit Card Delinquency Rate depend on the current macro regime. Financial conditions indexes are the Fed's dashboard. The Chicago Fed's NFCI blends over 100 inputs spanning equity volatility, credit spreads, funding stress, and leverage. Real yields across the TIPS curve reveal the true cost of capital after inflation, while liquidity measures (reverse repo, TGA, reserves) show whether the system is flush or stressed. Together they form the transmission belt from policy rate to real economy. Convex tracks these drivers live across the Credit & Financial Stress 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 Credit Card Delinquency Rate lower?▾
The same transmission channels that drive Credit Card Delinquency Rate 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 Credit Card Delinquency Rate 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 Credit Card Delinquency Rate?▾
Historical ranges for Credit Card Delinquency Rate 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 Credit Card Delinquency Rate chart page, which includes selectable time ranges up to five years and downloadable data.
How often is the Credit Card Delinquency Rate 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 Credit Card Delinquency Rate 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.