US National (FHFA, 1975Q1+) Historical Replay: 1999-04 to 2006-07
Replay 30 monthly bars from April 1999 to July 2006 as U.S. national home prices climbed 70.4% from 220.16 to 375.06. Make decisions across 6 branching points, face the 2 critical calls, and receive an AI coach review of every choice in this educational market simulation.
30 monthly bars · 6 decision points · 1999-04 to 2006-07 · Property
Key facts
- Max run-up
- +70.4%
- Largest single-month move
- +3.8%
- 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 replay opens on U.S. national housing in April 1999, as the subprime lending boom quietly takes root. Across 30 monthly bars stretching to July 2006, players navigate a market where easy credit, loose lending standards, and speculative fever are beginning to inflate a national bubble. Six decision points await, including two critical junctions where conviction and timing separate disciplined participants from reactive ones.
What unfolds is a remarkably steady ascent. Prices climb from 220.16 to 375.06, a cumulative gain of 70.4% with zero recorded drawdown throughout the entire span. The largest single monthly candle measures just 3.8%, reflecting low volatility that paradoxically rewards passive holders while luring others into increasing exposure. There are no dramatic crashes or sharp reversals within the data window—only the quiet compounding of unsustainable growth.
For decision training, this era exposes several cognitive traps. First, a zero drawdown environment can breed false confidence; participants may mistake a smooth ride for skill rather than favorable tailwinds. Second, low volatility masks building risk; when 3.8% monthly moves seem large, complacency sets in. Third, the two critical decision points demand clear process: Do you scale out as prices accelerate? Do you tighten position size as consensus grows bullish? The lesson is not that participants should have predicted the eventual correction, but that disciplined frameworks matter most when conditions feel safest.