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Beijing, China Historical Replay: 2020-04 to 2022-09

PropertyCity IndexCNCollapse2020-04 to 2022-09Difficulty 5/5FreeView charts

A Chinese property index plunged from 185.63 to 111.9, a 39.7% decline replayed across 30 monthly bars from April 2020 to September 2022. Step through each authentic decision point in this simulated training scenario and receive an AI coach review of your calls.

30K lines
6Decision points
5Difficulty
monthlyGranularity

30 monthly bars · 6 decision points · 2020-04 to 2022-09 · Property

Key facts

Peak-to-trough drawdown of 46.5% with a 9.9% run-up.

Max drawdown
−46.5%
Max run-up
+9.9%
Largest single-month move
−46.5%
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

How to play
  1. The market advances day by day. You only see candles up to the current day — as if you were really there.

  2. At key decision points choose Buy / Trim / Exit / Hold. Each decision advances the timeline by one day.

  3. 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 Chinese property sector entered a period of profound structural stress as credit conditions tightened and developer balance sheets deteriorated. From April 2020 through September 2022, investors and analysts tracked a sector index that had once traded near 185.63 as it increasingly showed signs of systemic strain. The stakes were substantial: property accounts for a significant portion of household wealth in China, and the sector's interconnections with banks, local governments, and supply chains meant that any sustained decline carried macro-financial implications far beyond the market itself.

What unfolded over those 30 monthly bars was a sustained compression in valuations, with the index ultimately settling at 111.9—a decline of -39.7% from the starting level. The journey was not smooth; the maximum drawdown reached 46.5%, and some individual monthly candles recorded moves of comparable magnitude. For those navigating this environment, six distinct decision points emerged as moments where directional conviction was tested, with two marked as critical junctures requiring explicit directional choices.

The scenario distills several enduring lessons for decision training. First, process discipline matters: navigating a -39.7% decline without adequate sizing or hedging can erode capital base permanently. Second, volatility itself becomes information—the 46.5% drawdown signals non-linear risk that standard historical models may underestimate. Third, psychology is tested most in extended drawdowns; the temptation to average down or exit at lows represents the core behavioral challenge. Training through this replay forces confrontation with these patterns in a simulated environment where lessons carry no real capital loss but build habits applicable when stakes are real.