Cotton Historical Replay: 2012-07 to 2013-01
Replay 118 daily bars of cotton from July 2012 to January 2013, a 9.3% close that masked an 11.0% drawdown. Step through 21 decision points, seven of them critical, while an AI coach reviews each choice in a simulated educational environment.
118 daily bars · 21 decision points · 2012-07 to 2013-01 · Commodities
Key facts
This window spans 173 days with a peak-to-trough drawdown of 11.0% and a 12.7% run-up.
- Max drawdown
- −11.0%
- Max run-up
- +12.7%
- Duration
- 173 days
- Largest single-day move
- +4.0%
- Bars
- 118 Daily bars
- Decision points
- 21
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
This replay covers cotton futures across 118 daily bars from July 25, 2012 to January 14, 2013, a six-month window when the soft commodity sector faced shifting monetary policy signals. The decade under study was the 2010s, and the central educational question was how traders navigate policy-driven volatility in commodity markets. The stage was set for students to confront the tension between macro forces and raw material pricing.
The closing price moved from 69.1 to 75.52, delivering a 9.3% return that appeared modest on the surface. Beneath this outcome lay an 11.0% maximum drawdown and a largest single-bar move of 4.0%, creating treacherous intra-period conditions. Participants who ignored the drawdown statistic would have experienced significant unrealized losses before the eventual recovery.
The 21 decision points, seven of them critical, forced students to act under uncertainty without the comfort of hindsight. The simulation teaches that surviving drawdowns is a prerequisite for capturing returns, that position sizing must account for single-bar surprises, and that policy environments demand flexible frameworks rather than rigid forecasts. This is decision training for the 2010s era of central bank dominance.
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