Heating Oil Historical Replay: 2005-11 to 2006-05
Replay the heating oil futures market across 124 daily bars from November 2005, when prices climbed from 1.73 toward 1.95. Step through each session, weigh 7 critical decisions among 21 total choice points, and review your reasoning with an AI coach.
124 daily bars · 21 decision points · 2005-11 to 2006-05 · Commodities
Key facts
This window spans 182 days with a peak-to-trough drawdown of 13.9% and a 30.4% run-up.
- Max drawdown
- −13.9%
- Max run-up
- +30.4%
- Duration
- 182 days
- Largest single-day move
- +7.4%
- Bars
- 124 Daily bars
- Decision points
- 21
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 heating oil futures market in the 2000s represented a pivotal arena where energy traders navigated seasonal demand shifts and geopolitical supply concerns. This replay covers 124 daily bars from November 2005 through May 2006, placing participants at the heart of a commodity boom that tested both analytical rigor and emotional discipline. The stakes were clear: a market climbing from 1.73 that demanded decisive action across 21 decision points, with 7 critical moments where strategy could be made or broken.
Prices rose from 1.73 to 1.95, a 12.7% appreciation over the period, yet the journey proved far from linear. The market endured a maximum drawdown of 13.9%, and volatility struck with a largest single-bar move of 7.4%, underscoring the inherent turbulence of energy futures during peak seasonal transition. Participants who mistimed entries or failed to manage position size faced punishing setbacks, while those who respected risk parameters found opportunities amid the chaos.
This replay sharpens decision training by confronting traders with realistic trade-offs between conviction and caution. The 13.9% drawdown ceiling serves as a forcing function: participants must learn when to hold positions through volatility and when discipline demands exit. The 7 critical decision points test emotional resilience, asking whether logic or fear drives choices when markets move sharply. Reviewing these choices with an AI coach transforms experience into pattern recognition, building the calibrated judgment that distinguishes prepared traders from reactive ones.
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