US National (FHFA, 1975Q1+) Historical Replay: 2009-07 to 2016-10
Replay 30 monthly bars from 2009-07 to 2016-10 as U.S. home prices climbed 14.9% in a slow recovery boom. Step through each decision point, weigh the volatility, and receive an AI coach review of your choices in this simulated training scenario.
30 monthly bars · 6 decision points · 2009-07 to 2016-10 · Property
Key facts
Peak-to-trough drawdown of 7.3% with a 23.9% run-up.
- Max drawdown
- −7.3%
- Max run-up
- +23.9%
- Largest single-month move
- −2.8%
- 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 scene opens in July 2009, six months after the collapse of Lehman Brothers. U.S. home prices, as measured by the FHFA national index, had been declining for more than two years. The Federal Reserve had flooded the system with liquidity, and the market was at an inflection point—torn between the memory of a catastrophic crash and the early signals of stabilization. For trainees replaying this period, the fundamental question was stark: is this the beginning of a durable recovery, or another bear-market bounce that will fade? With six decision points embedded across thirty monthly bars, participants would face the slow, uneven nature of post-crisis healing, where conviction is tested not by dramatic single events but by months of grinding, sideways chop.
What actually unfolded was a gradual recovery boom. The index rose from 332.27 to 381.92, a total return of 14.9% spread over the 2009–2016 window. The journey was far from linear: a maximum drawdown of 7.3% reminded participants that recoveries do not travel in straight lines. The largest single monthly move of 2.8% was modest by equity standards, reflecting the slower heartbeat of real estate compared to stocks. Over the decades covered—the 2000s and 2010s—this stretch represents a textbook case of structural healing, driven by policy support, gradually improving employment, and the simple arithmetic of supply constraints in hard-hit markets.
For decision training, the central lesson is the discipline of staying calibrated in a market that rewards patience and punishes impatience. A 14.9% total return over roughly seven years tests emotional endurance; a 7.3% drawdown during that same period tests conviction. Trainees must practice distinguishing normal volatility from signals that the recovery is breaking down. The AI coach reviews whether participants overcorrected at the first sign of a pullback or, conversely, whether they ignored early warnings. By stepping through each of the six decision points—two of them critical—trainees build the habit of process-driven reasoning that remains steady even when the market rewards come slowly.