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Learn ICT trading deeply
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Module 11
Backtesting Trading Strategies in Python
1
Backtesting and the Perils of Look-Ahead Bias
Explain the purpose of backtesting and the danger of look-ahead bias
Vectorized vs. Event-Driven Backtesting
Differentiate between vectorized and event-driven backtesting approaches
3
Vectorized Backtesting with Pandas
Build a simple vectorized backtester using pandas for a rule-based strategy
4
Executing Your Trading Strategy: Generating Entry & Exit Points
Generate a series of trades (entry/exit points) from your strategy logic
5
Trading Performance Metrics
Calculate and interpret key performance metrics: win rate, profit factor, and drawdown
6
Decoding Equity Curves: Performance & Risk
Analyze a backtest's equity curve to assess strategy performance and volatility
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Systematic Risk and Trade Management
Next module
Capstone: Building a Hybrid Trading Plan