SMC Algorithmic Backtester
We built an institutional-grade backtesting engine capable of processing 10 years of tick data in seconds, enabling rapid strategy validation for a private trading firm.
The Challenge
Our client was manually backtesting Smart Money Concepts (SMC) strategies on TradingView. This process was slow, prone to human error, and impossible to scale. They needed a way to scientifically validate their edge across multiple currency pairs and timeframes without spending hundreds of hours on manual replay.
The Solution
We engineered a custom Python-based backtesting kernel wrapped in a Next.js 14 dashboard. The system ingests tick-level data, simulates realistic orderbook conditions (slippage, spread), and executes the specific SMC logic rules (Order Blocks, FVG, liquidity sweeps).
The frontend provides an interactive "Command Center" where traders can adjust parameters (Risk %, Stop Loss buffer, Time Session) and instantly visualize the equity curve.
Key Technologies
Project Outcomes
- Eliminated manual testing completely
- New strategies validated in minutes
- Identified optimal Asian Session pairs
- Deployed to live trading server