Land Algorithmdemo
OverviewObjective BuilderDeal ExplorerPortfolio SimulatorStrategy Compare
Demo data — synthetic mock parcels. Engine: Python at /src; UI re-runs Gate 4 in TypeScript.

Portfolio Simulator

Take the parcels your active Objective marks BUY, draw a few thousand market scenarios, and chart the outcome distribution (P5 / P50 / P95, probability of net loss, max drawdown).

Objective
Conservative Cash — Florida
BUYs in this portfolio
43
Total acquisition + costs: $1,152,000

Market dials

Recession severity (0%)
Per-deal catastrophe prob (12.0%)
Cat severity (20% of cost)
N scenarios
Directional only — uncalibrated. Distributions and per-Objective comparisons are reliable; absolute P(loss) / P(ruin) / exact ROI numbers are pinned to placeholder market priors and should not be quoted as forecasts. Use the distribution shape and the right-vs-left comparison story, not the exact percentages. (ADR-021 / ADR-024 — recalibration awaits v3.)
Mean P/L
$1,127,809
Median (P50)
$1,134,485
P5 / P95
$883,478 / $1,355,103
P(net loss) †
0.0%
uncalibrated
Std dev
$143,474
Max drawdown †
51.2%
worst-case / total cost · uncalibrated
Expected ROI †
97.9%
uncalibrated
Outcome std / total cost
12.5%

Outcome distribution

scenariosmedianbreak-even