New York Historical Replay: 2017-03 to 2019-08
Replay a steady New York property climb from March 2017 to August 2019, covering 30 monthly bars with only a 0.4% max drawdown. You step through each authentic day, face six decision points including two critical ones, and receive an AI coach review in a simulated, educational setting.
30 monthly bars · 6 decision points · 2017-03 to 2019-08 · Property
Key facts
Peak-to-trough drawdown of 0.4% with a 7.4% run-up.
- Max drawdown
- −0.4%
- Max run-up
- +7.4%
- Largest single-month move
- +0.8%
- 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 New York property market replay spans March 2017 to August 2019, covering 30 monthly bars across the steady appreciation phase of the 2010s. Participants enter a market defined by consistent, measured gains with remarkably low volatility. Six decision points are woven into the historical timeline, including two critical junctures where market conditions presented more complex trade-offs. The scenario tests whether trainees can maintain disciplined analysis when the market environment appears benign.
Over the full data span, prices advanced from 187.32 to 201.27, delivering a 7.4% cumulative return. The journey was notably smooth: the largest single monthly move reached just 0.8%, while the maximum drawdown totaled only 0.4%. These compressed ranges meant that timing pressure was subtle rather than dramatic, rewarding patience and systematic thinking over reactive moves.
The scenario teaches that low-volatility environments demand as much psychological vigilance as turbulent ones. With minimal pullbacks, the temptation to over-leverage or abandon process grows. The two critical decision points test whether trainees can distinguish between quiet strength and complacency. AI coach review helps participants examine how their assumptions and risk tolerance held when the market offered few obvious signals, building habits that transfer to more volatile periods.
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