Vancouver — 6-month directional accuracy

75.0%
Always-DOWN baseline: 67.4%  |  Edge: +7.6 pp
Test window: 2024-01 .. 2025-12 (1848 cells, 77 cohorts × 24 months)  ·  Last refreshed: 2026-05-09 14:22

Honest-edge metrics

MetricValueContext
Directional accuracy75.0% What the model gets right
Always-DOWN baseline67.4% Trivial in this regime
Edge over baseline +7.6 pp The honest number
Balanced accuracy68.4% (UP recall + DOWN recall) / 2
UP precision65.6% When model says UP, how often it's right
UP recall49.3% Of actual UPs, how many caught
RMSE0.0256 From trend_metrics.json

Rolling-12-month accuracy vs. always-DOWN baseline

The shaded region is the model's edge over the trivial classifier in each rolling window. If the blue line slides toward (or below) the dashed baseline in recent months, the regime is shifting and the model's edge is collapsing.

Rolling accuracy chart

Per-month breakdown

One row per prediction month. Color reflects edge over the always-DOWN baseline within that month: red = negative edge, yellow = 0–5 pp, green = > 5 pp.

MonthCellsActual UPActual DOWN DOWN-baselineModelEdge UP correct / predDOWN correct / pred
2024-01 77 73 4 5.2% 94.8% +89.6 pp 73 / 77 0 / 0
2024-02 77 68 9 11.7% 88.3% +76.6 pp 68 / 77 0 / 0
2024-03 77 46 31 40.3% 40.3% +0.0 pp 0 / 0 31 / 77
2024-04 77 23 54 70.1% 70.1% +0.0 pp 0 / 0 54 / 77
2024-05 77 7 70 90.9% 90.9% +0.0 pp 0 / 0 70 / 77
2024-06 77 9 68 88.3% 88.3% +0.0 pp 0 / 0 68 / 77
2024-07 77 19 58 75.3% 75.3% +0.0 pp 0 / 0 58 / 77
2024-08 77 17 60 77.9% 77.9% +0.0 pp 0 / 0 60 / 77
2024-09 77 35 42 54.5% 54.5% +0.0 pp 0 / 0 42 / 77
2024-10 77 32 45 58.4% 58.4% +0.0 pp 0 / 0 45 / 77
2024-11 77 52 25 32.5% 67.5% +35.1 pp 52 / 77 0 / 0
2024-12 77 45 32 41.6% 58.4% +16.9 pp 45 / 77 0 / 0
2025-01 77 33 44 57.1% 42.9% -14.3 pp 33 / 77 0 / 0
2025-02 77 23 54 70.1% 46.8% -23.4 pp 19 / 56 17 / 21
2025-03 77 18 59 76.6% 76.6% +0.0 pp 0 / 0 59 / 77
2025-04 77 11 66 85.7% 85.7% +0.0 pp 0 / 0 66 / 77
2025-05 77 6 71 92.2% 92.2% +0.0 pp 0 / 0 71 / 77
2025-06 77 5 72 93.5% 93.5% +0.0 pp 0 / 0 72 / 77
2025-07 77 4 73 94.8% 94.8% +0.0 pp 0 / 0 73 / 77
2025-08 77 9 68 88.3% 88.3% +0.0 pp 0 / 0 68 / 77
2025-09 77 14 63 81.8% 81.8% +0.0 pp 0 / 0 63 / 77
2025-10 77 15 62 80.5% 80.5% +0.0 pp 0 / 0 62 / 77
2025-11 77 13 64 83.1% 83.1% +0.0 pp 0 / 0 64 / 77
2025-12 77 26 51 66.2% 68.8% +2.6 pp 7 / 12 46 / 65

Per property-type breakdown

Per property-type bar chart
Property typeCellsWithin-PT majority baseline Model accuracyEdgeRMSE
Apartment 456 71.3% 77.2% +5.9 pp 0.0308
Composite 480 69.0% 77.1% +8.1 pp 0.0195
Detached 480 65.2% 71.7% +6.5 pp 0.0264
Townhouse 432 63.9% 74.1% +10.2 pp 0.0248

"Within-PT majority baseline" = max(P(UP), P(DOWN)) of actuals restricted to that property type. This is the trivial classifier specific to the subgroup; it differs from the overall always-DOWN baseline because UP/DOWN balance varies by PT.

Confusion matrix

Confusion matrix heatmap

Per-area breakdown — top 10 best, bottom 10 worst

Aggregated across property types within each area. Areas with < 12 cells excluded as small-sample noise.

Top 10 — highest accuracy

AreaCellsBaselineModelEdge
North Vancouver 96 63.5% 87.5% +24.0 pp
Port Coquitlam 96 69.8% 86.5% +16.7 pp
Coquitlam 96 75.0% 86.5% +11.5 pp
Vancouver East 96 71.9% 81.2% +9.4 pp
Burnaby East 96 74.0% 81.2% +7.3 pp
Maple Ridge 96 74.0% 80.2% +6.2 pp
West Vancouver 72 73.6% 79.2% +5.6 pp
Burnaby North 96 64.6% 78.1% +13.5 pp
Richmond 96 81.2% 78.1% -3.1 pp
Vancouver West 96 69.8% 76.0% +6.2 pp

Bottom 10 — lowest accuracy

AreaCellsBaselineModelEdge
Bowen Island 48 58.3% 33.3% -25.0 pp
Whistler 96 52.1% 64.6% +12.5 pp
Sunshine Coast 96 63.5% 65.6% +2.1 pp
Squamish 96 53.1% 67.7% +14.6 pp
Pitt Meadows 96 67.7% 68.8% +1.0 pp
Tsawwassen 96 63.5% 69.8% +6.2 pp
Ladner 96 59.4% 71.9% +12.5 pp
Burnaby South 96 69.8% 72.9% +3.1 pp
Port Moody 96 70.8% 75.0% +4.2 pp
New Westminster 96 77.1% 76.0% -1.0 pp

Live forecasts (un-verified)

Forecast made 2026-04. Verifiable starting 2026-11 (when 2026-10 HPI lands). 81 (area, property_type) cohort predictions in forecast_202604_6m.csv.

Top 10 by predicted return

AreaProperty typeBenchmark price Pred returnDirection Future price$ change
Whistler Apartment $515,100 −1.49% DOWN $507,411 −$7,689
Squamish Apartment $491,900 −1.56% DOWN $484,222 −$7,678
West Vancouver Apartment $1,017,000 −1.59% DOWN $1,000,823 −$16,177
Sunshine Coast Apartment $389,600 −1.60% DOWN $383,363 −$6,237
Sunshine Coast Composite $768,000 −1.64% DOWN $755,408 −$12,592
Sunshine Coast Detached $820,700 −1.64% DOWN $807,244 −$13,456
Whistler Composite $1,290,500 −1.67% DOWN $1,268,921 −$21,579
Maple Ridge Townhouse $723,900 −1.68% DOWN $711,744 −$12,156
Port Coquitlam Apartment $580,400 −1.68% DOWN $570,647 −$9,753
Vancouver East Detached $1,681,000 −1.68% DOWN $1,652,717 −$28,283

Bottom 10 by predicted return

AreaProperty typeBenchmark price Pred returnDirection Future price$ change
Port Moody Apartment $703,400 −1.95% DOWN $689,667 −$13,733
Burnaby North Townhouse $931,900 −1.95% DOWN $913,706 −$18,194
Tsawwassen Detached $1,530,000 −1.95% DOWN $1,500,130 −$29,870
Vancouver East Apartment $664,800 −1.95% DOWN $651,821 −$12,979
Ladner Townhouse $983,600 −1.95% DOWN $964,397 −$19,203
Port Coquitlam Detached $1,326,700 −1.95% DOWN $1,300,828 −$25,872
North Vancouver Townhouse $1,273,700 −1.95% DOWN $1,248,862 −$24,838
North Vancouver Detached $2,129,900 −1.95% DOWN $2,088,365 −$41,535
North Vancouver Apartment $784,500 −1.95% DOWN $769,201 −$15,299
North Vancouver Composite $1,320,500 −1.95% DOWN $1,294,749 −$25,751

Track record (forward-prediction history)

Forecast archive started 2026-05. The first scoreable forecast becomes verifiable ~6 months after it was made (once the target month's HPI is published). Historical pre-archive months are not recoverable; the per-month backtest table above is the available proxy until archive matures.

Backtest vs live. Backtest accuracy (rendered above) and live-forecast accuracy (track-record section) are not directly comparable: the backtest re-trains at each cutoff (walk-forward), while the live model in forecast.py is the latest single fit. Expect live to underperform backtest by 1–3 pp once the track record matures.

Provenance. Backtest data from trend_backtest.csv last modified 2026-05-08 19:45. Headline overall accuracy from trend_metrics.json last modified 2026-05-08 19:45. Render time: 0.21s.

Caveat. If train_trend.py runs again, the backtest CSV will be overwritten. Past dashboard renders are not retained automatically; consider committing a snapshot if a number is load-bearing in correspondence.

Forecast verification