China National (Real Estate Climate Index, 1998+) Historical Replay: 2010-03 to 2012-10
Replay China's national real-estate climate index from 2010-03 to 2012-10 as it fell 10.7% across 30 monthly bars. Make decisions at 6 checkpoints, including 2 critical ones, and receive an AI coach review of your reasoning in this simulated educational scenario.
30 monthly bars · 6 decision points · 2010-03 to 2012-10 · Property
Key facts
Peak-to-trough drawdown of 10.9% with a 1.4% run-up.
- Max drawdown
- −10.9%
- Max run-up
- +1.4%
- 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
China's national real-estate climate index traces the pulse of the world's largest property market. From March 2010 to October 2012, policymakers were tightening credit, restricting purchases, and taxing transactions in an effort to cool an overheated sector. Participants in this replay step into a period where a decade-long boom faced its first serious regulatory test, and the stakes involved not just capital but the fate of an entire growth model. The index moved across 30 monthly bars as participants weighed each decision checkpoint.
Over the full 30 months, the index fell from 105.89 to 94.56, a decline of 10.7%. The maximum drawdown hit 10.9%, meaning any participant who bought near the high would have seen roughly that much erosion before the period ended. The largest single monthly move was only 1.4%, a reminder that gradual, persistent pressure can be as instructive as dramatic crashes. Six decision points peppered the replay, with two marked as critical, forcing learners to act under uncertainty rather than wait for perfect clarity.
This scenario trains the discipline of process over prediction. The modest but relentless 10.7% slide shows how cumulative small losses can reshape a portfolio without dramatic headlines. Participants must practice sizing positions, managing drawdown, and staying mentally sharp when each monthly bar offers only a 1.4% signal. The two critical decision points force honest evaluation of whether one is reacting to price or to a pre-committed plan—a distinction that separates disciplined learners from impulsive gamblers.
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