China National (Real Estate Climate Index, 1998+) Historical Replay: 2020-05 to 2022-10
Replay China’s national property index as it fell from 99.46 to 94.66 across 30 months, a 6.7% drawdown era. You walk through each monthly decision point in a simulated historical replay and get an AI coach review of your choices.
30 monthly bars · 6 decision points · 2020-05 to 2022-10 · Property
Key facts
Peak-to-trough drawdown of 6.7% with a 2.0% run-up.
- Max drawdown
- −6.7%
- Max run-up
- +2.0%
- 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
The replay transports you to China’s national property sector as the “Three Red Lines” regulatory framework reshaped the industry starting in mid-2020. The National Housing Prosperity Index, a broad barometer of nationwide real estate health, entered a testing phase from May 2020. The sector was navigating a fundamental policy reset—a deliberate effort to reduce leverage across the industry—and the stakes were high for anyone with capital exposed to property-linked assets. This replay challenges you to manage risk through 30 months of shifting sentiment.
The index closed the period at 94.66, down from an opening of 99.46, representing a -4.8% decline. During the replay window, the maximum drawdown reached 6.7%, with the largest single monthly swing measuring 3.5%. Across the 30 monthly bars, you faced six decision points—two of which were classified as critical, requiring you to act with incomplete information as policy signals evolved. The market never collapsed, but the sustained pressure tested conviction and discipline.
For decision training, this scenario is valuable precisely because it lacks a dramatic crash. Instead, it forces you to practice position management under a grinding downtrend, distinguish between noise and signal in regulatory communications, and control the urge to overact to monthly volatility. The educational goal is to build a repeatable process for navigating policy-driven uncertainty—a skillset that transfers far beyond any single market cycle.