Vacant Housing Units Forecast 2026
Quantitative analysis from 99 observations of Vacant Housing Units 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 | -1.56% | 2.92% | -0.54 | 25.0% | -1.56% |
| 3Y | 12 | 0.63% | 4.26% | 0.15 | 45.5% | 1.74% |
| 5Y | 21 | -0.38% | 4.45% | -0.09 | 50.0% | -1.91% |
| 10Y | 40 | -1.23% | 6.82% | -0.18 | 56.4% | -11.37% |
| All | 99 | 0.37% | 5.30% | 0.07 | 56.1% | 9.42% |
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 Vacant Housing Units 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 |
|---|---|---|---|---|
| Jan 1, 2024 | 15262.0000 | 0.00% | -0.31% | 1.87% |
| Apr 1, 2021 | 15659.0000 | 0.00% | -2.87% | -2.21% |
| Jan 1, 2020 | 15967.0000 | 0.00% | -13.10% | -2.28% |
| Oct 1, 2019 | 16113.0000 | 0.00% | -0.91% | -4.13% |
| Oct 1, 2018 | 16382.0000 | 0.00% | 2.64% | -1.64% |
Worst Historical Drawdown[07]
Largest Single-Period Moves[09]
- Oct 1, 20208.41%
- Jan 1, 20074.91%
- Jan 1, 20084.09%
- Jan 1, 20253.69%
- Jan 1, 20243.50%
- Apr 1, 2020-13.10%
- Oct 1, 2014-6.68%
- Oct 1, 2019-5.43%
- Oct 1, 2017-4.92%
- Oct 1, 2022-4.88%
Calendar-Month Seasonality[10]
Average single-period return aggregated by the calendar month in which the period ended.
| MONTH | AVG RETURN | HIT % | N |
|---|---|---|---|
| January | 2.21% | 96.0% | 25 |
| April | -0.65% | 41.7% | 24 |
| July | 0.05% | 54.2% | 24 |
| October | -1.13% | 32.0% | 25 |
N = 99 OBS · GENERATED 2026-05-03 05:31Z
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
- •Mortgage rates
- •Housing supply
- •Demographics
- •Construction costs
- •Credit availability
Historical Volatility
Moderate: housing cycles are multi-year
Scenarios That Affect This Forecast
Frequently Asked Questions
What factors could push Vacant Housing Units higher?▾
The primary drivers that tend to lift Vacant Housing Units depend on the current macro regime. Housing is the most interest-rate-sensitive sector of the economy and often the first to roll over heading into a downturn. Mortgage rates feed directly into affordability and demand, while building permits signal future supply. Home price indexes like Case-Shiller capture the wealth effect that drives consumer confidence and spending. Convex tracks these drivers live across the Housing 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 Vacant Housing Units lower?▾
The same transmission channels that drive Vacant Housing Units 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 Vacant Housing Units 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 Vacant Housing Units?▾
Historical ranges for Vacant Housing Units 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 Vacant Housing Units chart page, which includes selectable time ranges up to five years and downloadable data.
How often is the Vacant Housing Units 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 Vacant Housing Units 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.