Inflation · Shenzhen Component Index (2010)
Replay 150 daily bars of the Shenzhen Component Index from July 2010 to March 2011, when a 19.3% rise masked a 17.1% drawdown amid tightening-policy fears. Step into 26 decision points across each volatile day, receive an AI coach review, and learn how inflation-era policy shocks unfold using simulated capital only.
150 daily bars · 26 decision points · 2010-07 to 2011-03 · Stocks
Key facts
This window spans 229 days with a peak-to-trough drawdown of 17.1% and a 29.3% run-up.
- Max drawdown
- −17.1%
- Max run-up
- +29.3%
- Duration
- 229 days
- Largest single-day move
- −7.0%
- Bars
- 150 Daily bars
- Decision points
- 26
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 mid-2010, China confronted mounting inflationary pressures that prompted widespread expectations of monetary tightening. The Shenzhen Component Index entered this charged environment on 2010-07-30, with investors bracing for potential interest-rate hikes, reserve-requirement increases, and credit tightening across sectors. The central question was whether equity valuations could withstand the dual headwinds of cooling liquidity and persistent price growth. This period placed every market participant at a decision crossroads: how to position portfolios when policy direction remained uncertain and growth prospects competed with tightening risks.
The 150-day replay window from 2010-07-30 to 2011-03-16 encapsulated this tension. The index ultimately rose 19.3%, closing at 12865.75 from an opening of 10785.35. Yet this net gain obscured a treacherous path—a maximum drawdown of 17.1% tested portfolio resilience at various points, while the largest single-bar move of 7.0% demonstrated how policy signals could swing prices sharply in either direction. Across 26 decision points (9 critical), participants encountered alternating surges of optimism and risk-off episodes driven by inflation data and central-bank communications. The market did climb, but only for those who could endure the intermediate turbulence.
This scenario distills several enduring lessons for decision training. First, headline returns mask the psychological toll of drawdowns; managing risk during a 17.1% decline requires discipline that aggregate performance numbers never reveal. Second, volatility environments demand clear entry and exit criteria, as a 7.0% single-day swing can easily override imprecise stop-loss logic. Third, the 26 decision points remind trainees that market timing is not a single bet but a series of evaluations that compound over time. For those training under simulated conditions, this replay teaches patience, risk calibration, and the humility to accept that even a rising market can punish unprepared participants.