MSCI Emerg Markets Uptrend Replay (2018-08-15 to 2018-08-29)
Replay ten trading days across a MSCI Emerging Markets rally with simulated capital, then endure a 6.8% slide after the 2018-08-29 peak. Make daily decisions at seven checkpoints, receive AI coaching, and study how volatility shaped historical outcomes.
30 daily bars · 7 decision points · 2018-08 to 2018-09 · Stocks
Key facts
This window spans 42 days with a peak-to-trough drawdown of 7.5% and a 6.2% run-up.
- Max drawdown
- −7.5%
- Max run-up
- +6.2%
- Duration
- 42 days
- Largest single-day move
- −2.9%
- 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
The replay transports you to August 2018, when the MSCI Emerging Markets index was navigating a fragile uptrend in the late summer months. Over ten trading days from mid-August, participants faced the challenge of capturing gains during a rally while preparing for an inevitable reversal. With simulated capital at stake, every checkpoint tested the ability to read momentum and manage positions through a period of significant uncertainty.
The data reveals a decisive shift: after the August 29 peak, the index fell from 44.46 to 41.44, a -6.8% correction that unfolded within weeks. The maximum drawdown of 7.5% tested risk management frameworks, while the largest single-bar move of 2.9% demonstrated how quickly sentiment can reverse in emerging markets. Seven decision points punctuated the period, three of which proved critical to outcome. These moments demanded traders balance trend-following instincts against the risk of sudden reversals.
This scenario distills essential lessons in decision discipline: the importance of predefined exit strategies, the psychology of holding winners through increasing volatility, and the humility to acknowledge when a trend has exhausted itself. By studying how volatility shapes historical outcomes, participants internalize that process matters more than prediction. The AI coaching prompts reflection on why certain decisions felt right in the moment yet proved costly in hindsight, building the self-awareness that separates informed traders from impulsive ones.