Merval Uptrend Replay (2015-04-21 to 2015-05-05)
Replay eleven trading days of the Argentine Merval climbing from 11439 to 12097, a 5.8% uptrend. You step through each daily bar, face 7 decision points, and receive an AI coach review on your simulated choices.
30 daily bars · 7 decision points · 2015-04 to 2015-05 · Stocks
Key facts
This window spans 42 days with a peak-to-trough drawdown of 6.9% and a 10.2% run-up.
- Max drawdown
- −6.9%
- Max run-up
- +10.2%
- Duration
- 42 days
- Largest single-day move
- +4.4%
- Bars
- 30 Daily bars
- Decision points
- 7
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 the spring of 2015, Argentina's Merval index offered traders a concentrated lesson in navigating an emerging-market uptrend. The market had been consolidating after a period of volatility, and the April-May window presented a 5.8% climb from 11439 to 12097 across eleven trading days. For participants entering this replay, the central question was straightforward: how do you capture directional momentum while respecting the risk embedded in an unfamiliar market structure?
The journey proved instructive in its turbulence. Despite the net positive outcome, the scenario delivered a maximum drawdown of 6.9%, meaning that staying fully invested through every daily bar would have tested conviction more than once. The largest single-bar move of 4.4% appeared without warning, illustrating how quickly intraday swings can challenge position sizing assumptions. With seven decision points, three flagged as critical, the simulation forced participants to act repeatedly rather than set-and-forget—mirroring the cognitive demands of real market engagement.
This replay trains traders to separate outcome from process. The 5.8% final gain was achievable, but the path included drawdowns that would have unsettled most frameworks. By confronting 6.9% peak-to-trough declines in a simulated environment, participants learn to stress-test their risk tolerance before capital is at stake. The three critical junctures—where the path could have diverged sharply—develops pattern recognition for moments when conviction must override short-term noise. Success here is measured not by whether one captured the full move, but by whether decisions aligned with a disciplined process throughout.