Phoenix Historical Replay: 2020-03 to 2022-08
Replay Phoenix's 30-month property climb from March 2020 to August 2022, posting a 64.7% close-to-close gain. Step through each monthly bar, tackle six decision points, and receive AI coach feedback on a simulated educational replay.
30 monthly bars · 6 decision points · 2020-03 to 2022-08 · Property
Key facts
Peak-to-trough drawdown of 2.3% with a 68.7% run-up.
- Max drawdown
- −2.3%
- Max run-up
- +68.7%
- Largest single-month move
- +3.7%
- 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 Phoenix property market entered an extraordinary chapter from March 2020 to August 2022, spanning 30 monthly bars across the 2020s decade. Low interest rates and shifting residential priorities in the post-pandemic era created a city-level boom dynamic that challenged conventional valuation assumptions. Participants faced the task of navigating a market where economic fundamentals were being rewritten in real time, with six decision points embedded throughout the scenario.
The market delivered a close-to-close appreciation of 64.7%, moving from 203.67 to 335.53. Notably, the maximum drawdown was only 2.3%, and the largest single-bar move reached 3.7%, indicating a remarkably steady ascent with contained volatility. These statistics frame a scenario that rewarded measured conviction rather than reactive trading.
The Phoenix replay tests both analytical process and psychological discipline. Six decision points, including two critical junctures, demand that participants distinguish signal from noise while managing downside risk in a rising market. This scenario is a valuable training ground for developing the patience and risk awareness that historical boom periods consistently demand of decision-makers.