US 10-City Composite Historical Replay: 2000-01 to 2002-06
Step into the US 10-city property index from January 2000 to June 2002, watching it climb 31.2% across 30 monthly bars. Replay each decision point day by day, then get an AI coach review of your choices in this simulated educational replay.
30 monthly bars · 6 decision points · 2000-01 to 2002-06 · Property
Key facts
- Max run-up
- +31.2%
- Largest single-month move
- +1.4%
- 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 US 10-city composite property index at the dawn of the new millennium represented a broad measure of residential real estate health across America's major metropolitan markets. From January 2000 through June 2002, this 30-month window captured a pivotal era when mortgage rates were declining and the technology bubble's aftermath was redirecting capital toward tangible assets. For participants in this simulated replay, the central question was how to position decisions as this market demonstrated the early dynamics that would eventually characterize the broader housing boom.
The index rose steadily from 100.75 to 132.22, delivering a cumulative gain of 31.2% across those 30 monthly bars. Notably, the maximum drawdown remained at 0.0%, and the largest single-bar move registered just 1.4%, indicating a remarkably consistent upward drift. With 6 decision points embedded in the data, including 2 marked as critical, participants faced the challenge of navigating a sustained climb where gradual appreciation dominated over dramatic volatility.
This scenario offers a counterpoint to high-volatility environments, teaching that trending markets with minimal drawdown demand different strategic frameworks. The absence of correction can be psychologically disorienting for participants accustomed to volatility, yet process discipline remains paramount. The two critical decision points likely tested whether participants could maintain conviction during gradual gains without overcomplicating their approach. Psychology in such environments centers on resisting the temptation to second-guess steady appreciation and understanding that consistent, measured positioning can capture the full move over time.