Iron Ore Historical Replay: 2024-11 to 2025-05
Replay 114 daily bars of iron ore from 2024-11-21 to 2025-05-14, capturing a 17.8% drawdown amid shifting US tariff and dollar policy. Work through 20 decision points day by day with AI coach feedback in a simulated, educational environment.
114 daily bars · 20 decision points · 2024-11 to 2025-05 · Commodities
Key facts
This window spans 174 days with a peak-to-trough drawdown of 17.8% and a 12.2% run-up.
- Max drawdown
- −17.8%
- Max run-up
- +12.2%
- Duration
- 174 days
- Largest single-day move
- −5.6%
- Bars
- 114 Daily bars
- Decision points
- 20
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 transports participants to iron ore markets during a turbulent stretch from November 2024 to May 2025. Over 114 trading days, this educational scenario immerses users in a period where US tariff policy and dollar dynamics created persistent uncertainty across commodity markets. The central challenge: navigate shifting policy signals while maintaining disciplined risk management in a market known for its sensitivity to macroeconomic forces.
Iron ore opened at 777.5 and closed at 737, recording a -5.2% decline over the full period. Beneath this modest headline figure lay much greater turbulence—a maximum drawdown of 17.8% tested positions severely, while the largest single session move of 5.6% demonstrated how quickly policy headlines could reprice the market. Participants confronted 20 decision points, with 7 flagged as critical moments requiring deliberate choices about entries, exits, and position adjustments under pressure.
This replay sharpens three capabilities essential for any market participant. First, it trains calibration: the gap between the -5.2% net change and the 17.8% drawdown illustrates why headline returns tell only part of the story. Second, it reinforces process discipline—the educational framework rewards consistent methodology over outcome chasing. Third, it builds psychological resilience by placing users in realistic decision scenarios where conviction must be balanced against adaptive risk management. The goal is not to predict policy outcomes but to develop the decision-making infrastructure that performs across uncertain environments.
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