# Algorithm Development and Validation

Building a robust trading algorithm is a multi-step, scientifically proven process designed to avoid overfitting and ensure real-world applicability.

Creating a reliable trading algorithm is a multi-stage, scientifically grounded process designed to avoid "overfitting" and ensure applicability in real-world conditions.

### Development Process

1. **Research and Hypothesis:** Scientists formulate mathematical models and signal functions based on identified market behaviors (e.g., trend persistence or mean reversion).
2. **Optimization on Training Data (In-Sample):** Models are calibrated on historical data using methods such as the **Monte Carlo Method** and **Coordinate Descent Method**, optimizing for metrics like the Sharpe ratio.
3. **Validation on Test Data (Out-of-Sample) and Walk-Forward Testing:** A critical stage. Models are tested on completely unseen time periods. **Walk-forward testing** over several years ensures they adapt to changing markets and are not mere artifacts of past data.
4. **Launch into Live Trading:** Only models that have passed validation enter live trading with minimal initial capital and are continuously monitored for performance against expectations.

### Protection Against Overfitting

We employ a robust validation system to ensure our strategies possess **generalization ability**. By strictly separating the data used for model training (in-sample) from the data used for testing (out-of-sample), we control for "noise" in historical data and build systems designed for future performance, not just past results.

> ***Important:** We understand that even the most rigorous statistical validation of past data does not guarantee future profit. Therefore, we never cease monitoring and control*
