China National (Real Estate Climate Index, 1998+) Historical Replay: 2016-06 to 2019-01
Replay China's national property gauge from June 2016 through January 2019, navigating a sideways 0.3% drift across 30 monthly bars. Make decisions at 6 pivotal moments, including 2 critical ones, and receive an AI coach review after each simulated bar.
30 monthly bars · 6 decision points · 2016-06 to 2019-01 · Property
Key facts
Peak-to-trough drawdown of 1.4% with a 1.7% run-up.
- Max drawdown
- −1.4%
- Max run-up
- +1.7%
- Largest single-month move
- −1.3%
- 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 opens in June 2016 as China's property market confronted a pivotal regulatory shift. The national housing sentiment index, having tracked a decade of expansion through the 2010s, now faced fresh purchase restrictions imposed in September 2016 across dozens of cities. This scenario tests whether participants can navigate a market caught between lingering optimism and tightening policy constraints. The gauge's 30-month journey from mid-2016 through early 2019 would prove that the most dangerous environment is not always the most dramatic one.
The index drifted a mere -0.3% over the full data span, closing at 100.58 versus an opening of 100.92. Yet this deceptive calm contained a 1.4% maximum drawdown and single-bar movements reaching 1.3%, creating subtle but persistent pressure on capital. Across six decision points—two deemed critical—players encountered moments where conviction mattered more than direction, and where patience outlasted opportunity. The sideways profile offered no easy narrative to follow.
This replay trains participants to recognize that low-volatility environments carry their own psychological hazards. The absence of dramatic crashes breeds complacency, while hidden drawdowns and occasional spikes test discipline in ways that trending markets do not. Decision training here centers on maintaining systematic processes when price action provides no compelling story, avoiding the trap of forced action during periods of genuine non-information. The scenario ultimately teaches that process reliability matters most when external validation is absent.