Orange Juice Historical Replay: 2021-10 to 2022-01
Replay 64 daily bars of orange juice from October 2021, when a regulatory shock drove an 8.7% drawdown amid 23.3% net swings. You step through each decision point across 4 critical junctures for an AI coach review, simulated capital only.
64 daily bars · 11 decision points · 2021-10 to 2022-01 · Commodities
Key facts
This window spans 94 days with a peak-to-trough drawdown of 8.7% and a 36.6% run-up.
- Max drawdown
- −8.7%
- Max run-up
- +36.6%
- Duration
- 94 days
- Largest single-day move
- +5.1%
- Bars
- 64 Daily bars
- Decision points
- 11
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 orange juice futures market entered a volatile chapter in October 2021, as regulatory scrutiny swept through commodity markets. Over the following months through January 2022, traders faced an environment where policy signals could trigger sharp intraday swings, making disciplined decision-making essential. This episode from the 2020s offers a window into how government intervention reshapes risk dynamics in soft commodities.
Sixty-four daily bars trace a 23.3% net gain from 126 to 155.35, yet the journey was anything but smooth. An 8.7% maximum drawdown tested position management, while the largest single-bar move of 5.1% underscored the volatility regime that regulatory uncertainty can create. Across 11 decision points—4 deemed critical—traders were forced to recalibrate positions as policy headlines rewrote the market narrative.
This replay sharpens process awareness. Position sizing must account for regime shifts where historical volatility understates tail risk. The psychological dimension proves equally vital: reacting to news-driven spikes with position changes often compounds losses. Trainees learn to distinguish signal from noise, maintaining conviction through drawdowns while respecting stop logic when evidence shifts. The goal is building decision-making frameworks that perform under the pressure of policy-driven volatility, not just in calm markets.
Featured in the archive