Introduction to Backtesting

Building and Testing a Momentum-Based Trading System

Learn the essentials of creating and evaluating a momentum-based trading system using Python:

Backtesting:
- Assess system performance using historical stock prices.
- Conduct scenario analysis to predict outcomes under uncommon price movements.
- Recognize the randomness of stock prices, which rarely repeat trajectories.
System Resilience:
- Develop strategies to perform well during various market conditions.
- Protect against significant losses while maximizing gains.
Analysis Server:
- Functions:
- Reads data
- Models stock behavior
- Forecast future prices
- Makes trading decisions
- Process:
- If automated, place buy/sell orders and update records post-execution.
- Continuous data reading for real-time adjustments.
Backtesting Mechanism:
- Validate strategies with past data to ensure robustness before live trading.
- Use historical dates to simulate conditions for backtesting.

In the next section, implementing the core of backtesting will be explored.