Professional tick data are expensive. Most retail traders and researchers can't afford it. Even if they can, historical data only gives you one timeline—you can't test strategies against market conditions that never happened.
Instead of replacing backtesting, we complement it. We used math to generate synthetic forex markets that let you stress-test beyond historical scenarios:
- Bid/ask spreads that widen under stress - Volatility clustering - Statistically validated against real EUR/USD market behavior - Real-time streaming via WebSocket (not just static exports)
The interface lets you build custom scenarios with your own parameters—control volatility, trend direction, and liquidity stress to create conditions that don't exist in historical data. We've also built one fully validated session (London-NY overlap) that matches real market statistics.
Use cases: - Stress-test strategies against scenarios that never happened - Generate diverse training data for ML models (prevent overfitting) - Practice risk management
The demo streams live—no signup, just click start and run the simulator.
Think of it as a flight simulator for algo traders. Pilots don't just replay old flights, they practice emergency scenarios. Same concept here.
Anonymous feedback button works if you want to tell me what's broken or missing.