Gold Historical Replay: 2019-08 to 2019-11
Replay 68 daily bars of gold from August to November 2019 as trade-war tensions reshaped precious metals sentiment. Work through 12 decision points, including 4 critical ones, and receive an AI coach review of your choices in this simulated educational scenario.
68 daily bars · 12 decision points · 2019-08 to 2019-11 · Commodities
Key facts
This window spans 94 days with a peak-to-trough drawdown of 6.3% and a 3.5% run-up.
- Max drawdown
- −6.3%
- Max run-up
- +3.5%
- Duration
- 94 days
- Largest single-day move
- −2.3%
- Bars
- 68 Daily bars
- Decision points
- 12
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 setting is gold futures in the 2010s, specifically the August to November 2019 period when US-China trade tensions were reshaping precious metals sentiment. Over 68 daily bars, traders face the challenge of navigating a market caught between safe-haven demand and profit-taking pressure. Twelve decision points await, four of them critical moments where positioning and conviction matter most.
The replay shows gold closing the period at 1463.1, down from an opening of 1504.6, a net decline of -2.8%. The journey was not smooth: the maximum drawdown reached 6.3%, and the largest single-bar move was 2.3%. These figures hide the real texture of the market—sharp reversals, sudden shifts in risk appetite, and the constant tension between geopolitical headlines and technical levels.
For decision training, this scenario teaches process over prediction. The modest overall decline masks intra-period volatility that punishes reactive trading and rewards disciplined risk management. Participants learn to separate signal from noise, manage exposure through uncertain macro backdrops, and confront the psychological difficulty of holding positions when the directional edge is unclear. AI coach reviews then expose blind spots in timing, sizing, and emotional control that the historical data alone cannot reveal.