Iron Ore Historical Replay: 2018-05 to 2018-08
Replay 62 daily bars of an iron ore market scenario with a 7.7% max drawdown and 4 critical decision points. Walk through each session, commit simulated trades, and receive an AI coach review of your historical choices.
62 daily bars · 11 decision points · 2018-05 to 2018-08 · Commodities
Key facts
This window spans 88 days with a peak-to-trough drawdown of 7.7% and a 11.5% run-up.
- Max drawdown
- −7.7%
- Max run-up
- +11.5%
- Duration
- 88 days
- Largest single-day move
- −5.0%
- Bars
- 62 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
In May 2018, iron ore futures entered a period of heightened volatility amid shifting steel demand expectations and evolving supply dynamics. Over the next three months—spanning 62 daily trading sessions from May 10 to August 6—the market presented traders with 11 decision points, four of which proved critical to navigating the period's most turbulent stretches. For those replaying this scenario, understanding the macroeconomic context of the 2010s ferrous market was essential to framing each tactical choice.
The replay period ultimately delivered a modest positive return, with prices climbing from 470 to 502.5—a 6.9% gain. However, this aggregate outcome obscured significant intraperiod turbulence: a maximum drawdown of 7.7% tested risk discipline, while the largest single-session move reached 5.0%, demanding real-time composure. Navigating between the 11 decision points required traders to balance conviction against the psychological strain of drawdown environments.
This scenario excels as a decision-training vehicle because it illustrates how "quiet" market periods can conceal sharp reversals. Participants learn to distinguish between price noise and structural shifts, manage position sizing relative to a 7.7% drawdown tolerance, and maintain emotional equilibrium when a single bar wipes out a portion of accumulated gains. The four critical decision points serve as deliberate friction points, forcing learners to articulate entry, exit, and risk-management rationale before reviewing historical outcomes against their simulated choices.