Backtesting & Analysis
Master backtesting frameworks, advanced indicators, statistical models, and portfolio optimization with Python.
Skills You'll Gain
Prerequisites
Complete Step 1: Python Trading Fundamentals before starting this section.
Step 1: FundamentalsLessons
Backtesting with Backtrader
70 minBuild and test trading strategies with built-in indicators, analyzers, and multi-timeframe support.
Technical Analysis with TA-Lib
60 minCalculate 150+ technical indicators — RSI, MACD, Bollinger Bands, and candlestick patterns.
Fast Backtesting with vectorbt
55 minRun thousands of backtests in seconds with vectorized parameter optimization and heatmaps.
Indicators with pandas-ta
40 minAdd 130+ technical indicators to pandas DataFrames with a single line of code.
Statistical Models (statsmodels)
50 minApply ARIMA forecasting, regression analysis, and cointegration tests to trading.
Portfolio Backtesting with bt
45 minBuild and backtest portfolio allocation strategies with rebalancing and benchmarking.
Next Step
After mastering backtesting, move on to live trading integration and machine learning.
Step 3: Live Trading & ML