China National (Real Estate Climate Index, 1998+) Historical Replay: 2011-03 to 2013-10
Replay 30 monthly bars of China’s national property index from March 2011, navigating a 5.9% slide with an 8.5% drawdown. Step through each authentic decision point, weigh the data, and receive an AI coach review of your simulated choices.
30 monthly bars · 6 decision points · 2011-03 to 2013-10 · Property
Key facts
Peak-to-trough drawdown of 8.5% with a 3.7% run-up.
- Max drawdown
- −8.5%
- Max run-up
- +3.7%
- Largest single-month move
- +2.4%
- 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
This replay begins in March 2011 with China's national property index at elevated levels, launching participants into a 30-month journey through October 2013 that would test their ability to navigate a sector under pressure. The market faced headwinds from macroeconomic tightening policies and a cooling property sector, creating an environment where disciplined analysis and risk management were essential for anyone seeking to understand how institutional and individual decisions shape outcomes during challenging periods.
The data reveals a cumulative decline of 5.9% over the replay, with the index closing at 96.88 down from 102.98. The journey was marked by an 8.5% maximum drawdown, indicating substantial portfolio stress at various points. Volatility manifested through a largest single-bar move of 2.4%, presenting six distinct decision points—two of which were particularly critical—requiring participants to demonstrate both analytical precision and emotional resilience in their simulated trading approach.
This scenario offers rich terrain for decision training. Participants encounter the tension between maintaining conviction in the face of declining prices and recognizing when adaptation is warranted. The experience highlights the psychological pressures inherent in navigating a market that fails to recover quickly, teaching that discipline in process and risk management often matters more than predicting the next move. Each decision point serves as a practical lesson in decision-making under uncertainty, reinforcing habits that distinguish prepared participants from reactive ones.
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