A Project Sequence for Learning Quantitative Trading with VN.PY

Summary

This document lays out a sequence of practical exercises for learning quantitative trading with VN.PY. The projects cover market data retrieval and database storage, vectorized indicator calculations, CTA strategy development, cleaning futures data, and building a cointegration-based spread strategy. Later exercises extend into parameter optimization, intraday volatility breakout testing, simulated live trading with risk controls, and performance reporting.

Key ideas

• The exercises link data acquisition, storage, analysis, strategy coding, and reporting into a learning progression.
• They propose comparing vectorized MACD calculations with loop-based calculations.
• The spread-trading exercise combines cointegration testing with Z-score entry and exit rules.
• The strategy projects include backtesting, parameter scans, and performance measures such as drawdown and Sharpe ratio.
• The live-trading exercise introduces automated operation, loss limits, and logging.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.