ATX Downtrend Replay (2000-02-14 to 2000-03-07)
Replay the February 2000 ATX correction across 34 daily bars as the index slips 0.5% from 1099.09 to 1093.36. Step through seven decision points, navigate an 8.9% drawdown, and receive an AI coach review of every simulated trade you make along the way.
34 daily bars · 7 decision points · 2000-02 to 2000-03 · Stocks
Key facts
This window spans 45 days with a peak-to-trough drawdown of 8.9% and a 8.1% run-up.
- Max drawdown
- −8.9%
- Max run-up
- +8.1%
- Duration
- 45 days
- Largest single-day move
- −3.5%
- Bars
- 34 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 Austrian Traded Index entered February 2000 in the midst of a global technology sell-off that had begun rattling equity markets worldwide. As the dot-com bubble showed signs of unwinding, the ATX faced pressure typical of European blue-chip indices exposed to the broader market uncertainty of that era. This scenario recreates 34 daily bars of authentic price action spanning the correction period, placing participants directly into the decision-making environment of that volatile moment.
The replay tracks the index from 1099.09 to 1093.36, representing a modest net decline of 0.5% over the data window. However, this headline figure obscures the true market behavior: an 8.9% maximum drawdown tested portfolio resilience, while the largest single-day move of 3.5% demonstrated how quickly sentiment could shift. Participants navigate seven decision points, three of which the scenario flags as critical junctures where directional conviction and risk management were essential.
For decision training purposes, this correction scenario illustrates how small percentage losses can mask significant intra-period volatility that demands active position management. The three critical decision points serve as focal moments to practice discipline under drawdown conditions, while the AI coach review provides structured feedback on trade execution and emotional regulation. Understanding that a seemingly tame -0.5% outcome involved an 8.9% trough reinforces why process—not outcome—must guide decision-making in volatile markets.