Minneapolis Historical Replay: 2006-03 to 2008-08
Step into a 30-month US city housing collapse where prices fell 15.7% from 168.71 to 142.17 amid an 18.5% drawdown. Replay each monthly bar, face 6 decision points including 2 critical junctures, and receive an AI coach review of your simulated choices.
30 monthly bars · 6 decision points · 2006-03 to 2008-08 · Property
Key facts
Peak-to-trough drawdown of 18.5% with a 2.9% run-up.
- Max drawdown
- −18.5%
- Max run-up
- +2.9%
- Largest single-month move
- −3.4%
- Bars
- 30 Monthly bars
- Decision points
- 6
Every figure above is computed programmatically from this replay’s own candle series — no editorial input, no LLM. Methodology: Methodology
The market advances day by day. You only see candles up to the current day — as if you were really there.
At key decision points choose Buy / Trim / Exit / Hold. Each decision advances the timeline by one day.
After settlement you get a six-dimension score and an AI coach review. Your result enters the scenario leaderboard.
Event Replay
What happened — and what it teaches
The scene opens on Minneapolis, a mid-sized American city whose housing market had spent years climbing alongside the national boom. By March 2006, the market had reached a peak valuation of 168.71, and the 2000s credit expansion was showing the first cracks beneath its surface. Participants enter this replay knowing only that the market will move month by month through 30 bars, facing six decision points—two of which the scenario flags as critical junctures. The educational mission is clear: learn to navigate a collapsing property market without the benefit of hindsight.
What unfolded over the next 30 months was a sustained contraction. The closing index fell from 168.71 to 142.17, representing a -15.7% decline. The maximum drawdown measured 18.5%, meaning anyone holding through the worst stretch saw nearly a fifth of their simulated capital erased. The largest single monthly move reached 3.4%, a modest figure by equity standards but meaningful in a market where investors had grown accustomed to steady appreciation. The descent was gradual and grinding rather than sudden—a psychological trap in itself, as the slow bleed eroded confidence month after month.
This replay teaches three enduring lessons. First, process discipline: following a monthly bar structure forces deliberate evaluation rather than reactive trading. Second, risk calibration: an 18.5% drawdown in a single asset class demands sizing discipline that many participants violate in retrospect. Third, psychological resilience: markets that fall steadily rather than crash outright test conviction differently, often tempting investors to hold too long or exit too early. By confronting this compressed 30-month collapse with an AI coach reviewing each simulated choice, learners internalize how their decision-making degrades under sustained loss conditions—preparing them better for any future market regime they may face.
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