title: "Quantitative Trading Backtesting System" description: "Use Python to fetch stock data, calculate technical indicators (MA, MACD, RSI), build a complete backtesting system." duration: "120 minutes" difficulty: "Advanced"
Quantitative Trading Backtesting System
Have you ever wondered:
"If I had bought when price broke below MA last month and sold now, what would my return be?" "Can I write a program to auto-analyze stocks and find buy/sell signals?" "I want to test a strategy but if I use real money and lose, what then?"
Algorithmic Trading uses code to make trading decisions. Backtesting tests strategies on historical data before trading.
Technologies Used
- Python, Pandas for data analysis
- yFinance for historical stock data
- TA-Lib for technical indicators (MACD, RSI, Bollinger)
- Backtrader for backtesting framework
- Prophet for trend prediction
Course Outline
Chapter 1: Quant Trading Basics
What is quant trading? Install Python financial tools.
Chapter 2: Technical Indicators
Calculate MA, MACD, RSI, Bollinger Bands.
Chapter 3: Strategy Implementation
Golden Cross and DCA strategies.
Chapter 4: Backtrader Framework
Professional backtesting with commissions and slippage.
Chapter 5: Strategy Optimization
Tune parameters - but watch for overfitting.
Chapter 6: Risk Management
Stop-loss, portfolio allocation, capital management.