RBOB Gasoline Historical Replay: 2024-07 to 2025-01
Replay 126 daily bars of RBOB gasoline from July 2024 to January 2025 as prices slid 14.3% amid policy-driven volatility. Walk through each session, make choices at 22 decision points including 8 critical ones, and receive an AI coach review of your reasoning in a simulated environment.
126 daily bars · 22 decision points · 2024-07 to 2025-01 · Commodities
Key facts
This window spans 181 days with a peak-to-trough drawdown of 25.8% and a 15.5% run-up.
- Max drawdown
- −25.8%
- Max run-up
- +15.5%
- Duration
- 181 days
- Largest single-day move
- −10.4%
- Bars
- 126 Daily bars
- Decision points
- 22
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
RBOB gasoline futures traded across the US energy complex during a period of significant monetary policy shifts. From mid-July 2024 through mid-January 2025, the market digested the Fed's September 2024 rate cut and its implications for a weakening dollar, setting the stage for elevated volatility. The scenario presents 22 decision points including 8 critical junctures, spanning 126 daily bars of authentic price action from the 2020s era.
Prices retreated from 2.52 to close near 2.16, a decline of 14.3% over the data span. The journey proved punishing for directional positioning, with peak-to-trough drawdown reaching 25.8% and individual sessions delivering moves as large as 10.4%. Such extremes tested anyone holding size through the period, exposing the asymmetry between paper risk and realized volatility in commodities during policy transitions.
This replay sharpens decision-making under uncertainty. Participants confront real-time positioning dilemmas across the full dataset, learning how policy-driven shifts can rapidly reprice energy exposure. The training emphasizes drawdown management and signal interpretation over prediction, while the psychological dimension proves equally vital: maintaining discipline when confronted with 10.4% single-day swings, avoiding reactive exits during Fed-driven volatility, and calibrating position size for the inherent turbulence of energy markets. Historical context transforms abstract risk concepts into lived experience.