China National (Real Estate Climate Index, 1998+) Historical Replay: 2008-08 to 2011-04
Replay 30 monthly bars of China's national property index from August 2008 to April 2011, navigating a 6.9% drawdown and a 2.1% swing. Make decisions at six checkpoints, receive an AI coach review, and explore the credit-easing boom through simulated educational replay.
30 monthly bars · 6 decision points · 2008-08 to 2011-04 · Property
Key facts
Peak-to-trough drawdown of 6.9% with a 11.8% run-up.
- Max drawdown
- −6.9%
- Max run-up
- +11.8%
- Largest single-month move
- +2.1%
- 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 centers on China's national property climate index spanning August 2008 to April 2011—a 30-month journey through one of the sector's most volatile postwar periods. This era followed the global financial crisis, when Beijing launched massive stimulus accompanied by aggressive credit easing. For participants, the stakes were clear: navigating a market caught between post-crisis panic and a subsequent credit-fueled recovery, all while enduring a 6.9% peak-to-trough drawdown. The index moved through two distinct decades (2000s and 2010s), requiring traders to adapt their frameworks as the macroeconomic narrative shifted monthly.
What transpired was a modest net advance of 1.4% (101.78 to 103.19), yet this headline figure conceals substantial intermediate turbulence. The largest single monthly swing reached 2.1%, while participants faced six explicit decision checkpoints—two deemed critical—testing their ability to act under uncertainty. Rather than a straight-line recovery, the index oscillated as stimulus hopes collided with sustainability concerns, creating multiple inflection points where positions could be won or lost depending on timing and conviction. The spread between peak optimism and trough fear defined the practical battlefield.
For educational purposes, this replay illuminates three enduring challenges: first, the danger of anchoring to initial conditions when macro regimes change; second, the psychological difficulty of maintaining discipline through a 6.9% drawdown while narrative momentum suggests recovery; and third, the asymmetry between knowing a stimulus will lift markets and predicting its precise timing. Participants learn that process—not prediction—must govern decision-making, and that volatility itself becomes information when filtered through a disciplined framework.
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