Live Cattle Historical Replay: 2020-03 to 2020-06
Live cattle fell from 490.75 to 428.25 between March and June 2020 as pandemic shocks rippled through commodity markets. Replay the 62 days bar-by-bar, tackle 11 decision points with AI coach review, and study how volatility actually unfolded.
62 daily bars · 11 decision points · 2020-03 to 2020-06 · Commodities
Key facts
This window spans 87 days with a peak-to-trough drawdown of 15.0% and a 8.6% run-up.
- Max drawdown
- −15.0%
- Max run-up
- +8.6%
- Duration
- 87 days
- Largest single-day move
- +5.5%
- 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
The live cattle futures market entered uncharted territory in March 2020 as the COVID-19 pandemic disrupted global supply chains and crushed consumer demand. Over the following months, commodity traders faced a landscape where traditional relationships between supply, demand, and price broke down under unprecedented stress. This replay scenario covers 62 daily bars from March 24 to June 19, placing traders directly into the heart of that dislocation, where every decision carried amplified consequences.
The numbers tell a stark story: live cattle fell 12.7% from 490.75 to 428.25 during this period, with a maximum drawdown of 15.0%. The market's largest single-day swing reached 5.5%, underscoring the volatility that characterized this pandemic-era commodity environment. Across the 62 trading days, traders encountered 11 decision points—four deemed critical—each testing their ability to process rapidly evolving information while managing positions in a market defined by uncertainty.
What this scenario teaches goes beyond technical analysis. Participants must confront the psychological pressures of trading during a crisis: the temptation to panic-sell at market bottoms, the difficulty of maintaining discipline when headlines scream catastrophe, and the importance of position sizing in environments where normal risk parameters are violated. Working through 11 decision points with AI coach review, traders can identify patterns in their own decision-making that may prove costly in live markets, making this replay a valuable exercise in building resilient trading processes regardless of market conditions.
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