USD/THB Historical Replay: 2018-11 to 2019-05
Replay USD/THB across 130 daily bars from November 2018 to May 2019 as the pair slipped from 32.915 toward 31.5. Step through each session, weigh 23 policy-driven decision points, and receive an AI coach review of your simulated choices.
130 daily bars · 23 decision points · 2018-11 to 2019-05 · Forex
Key facts
This window spans 180 days with a peak-to-trough drawdown of 6.9% and a 4.1% run-up.
- Max drawdown
- −6.9%
- Max run-up
- +4.1%
- Duration
- 180 days
- Largest single-day move
- +2.0%
- Bars
- 130 Daily bars
- Decision points
- 23
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 foreign exchange market rarely offers a cleaner laboratory for studying policy-driven volatility than the USD/THB pair during the winter of 2018–2019. From November 2018 through May 2019, traders faced a six-month window during which the Federal Reserve executed a pronounced dovish pivot, forcing participants across emerging market currencies to recalibrate positions. The Bank of Thailand, meanwhile, navigated a strengthening baht that complicated export competitiveness, creating a high-stakes environment where every policy signal carried outsized consequences. This scenario invites you to inhabit that uncertainty, processing real-time communications and economic data as they arrived.
The price action tells the story concisely: the pair declined from 32.915 to 31.5, a -4.3% move across 130 daily bars. The journey was far from linear, with a maximum drawdown of 6.9% testing even disciplined traders and a largest single-bar move of 2.0% underscoring how quickly sentiment could shift on policy headlines. Twenty-three decision points peppered the replay, eight of them critical junctures where the trajectory could have diverged sharply. Navigating each required not merely reading the data but anticipating the psychological weight that official communications would carry in live markets.
This replay teaches that process trumps prediction in policy-driven markets. You must construct a framework for distinguishing signal from noise, for knowing when a communication represents a genuine pivot versus tactical positioning. Risk management becomes existential when single-day moves can reach 2.0%, demanding that position sizing reflect the true tail risk of the environment. Psychologically, the scenario forces you to manage the tension between patience during grinding trends and decisiveness at genuine inflection points—neither drifting passively nor reacting impulsively to every headline.
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