China National (Real Estate Climate Index, 1998+) Historical Replay: 2019-09 to 2022-02
Replay China's national property climate index from September 2019 as it slides 4.3% across thirty monthly bars. Work through six decision points day by day, meet two critical pivots, and receive an AI coach review of each simulated call.
30 monthly bars · 6 decision points · 2019-09 to 2022-02 · Property
Key facts
Peak-to-trough drawdown of 4.5% with a 4.1% run-up.
- Max drawdown
- −4.5%
- Max run-up
- +4.1%
- Largest single-month move
- −3.5%
- 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
In the autumn of 2019, China's national property climate index sat at 101.23, a reading that masked growing tension beneath the surface of the world's largest property market. The period from September 2019 through February 2022 would span thirty monthly bars across the 2010s and 2020s, a timeframe during which Beijing was preparing one of the most consequential regulatory pivots in modern Chinese real estate history. What was at stake was not merely an index number but the structural framework governing how property developers could finance operations, a framework that would fundamentally reshape market expectations.
Over those thirty months, the index closed at 96.89, a decline of -4.3% that appears modest in isolation but contains significant internal volatility. The maximum drawdown reached 4.5% while the largest single monthly move measured 3.5%, both figures that reveal the market's sensitivity to policy signals. Participants navigating this replay encountered six decision points, with two emerging as critical pivots where the trajectory could have shifted materially depending on how one interpreted incoming regulatory signals.
For decision training purposes, this scenario excels at exposing the gap between reading a headline and pricing its implications. The index did not collapse; it drifted, creating a pattern where neither panic nor complacency served well. The lesson centers on developing calibration discipline under gradual stress, maintaining position sizing frameworks when no single event demands action, and recognizing that regulatory shifts often price themselves in slowly before the market fully absorbs their significance. Psychology in this environment rewards patience over reaction and structured review over improvised judgment.