Python for Algorithmic Trading Cookbook
eBook Details:
- Paperback: 412 pages
- Publisher: WOW! eBook (August 16, 2024)
- Language: English
- ISBN-10: 1835084702
- ISBN-13: 978-1835084700
eBook Description:
Python for Algorithmic Trading Cookbook: Recipes for designing, building, and deploying algorithmic trading strategies with Python. Harness the power of Python libraries to transform freely available financial market data into algorithmic trading strategies and deploy them into a live trading environment.
Discover how Python has made algorithmic trading accessible to non-professionals with unparalleled expertise and practical insights from Jason Strimpel, founder of PyQuant News and a seasoned professional with global experience in trading and risk management. This Python for Algorithmic Trading Cookbook guides you through from the basics of quantitative finance and data acquisition to advanced stages of backtesting and live trading.
Detailed recipes will help you leverage the cutting-edge OpenBB SDK to gather freely available data for stocks, options, and futures, and build your own research environment using lightning-fast storage techniques like SQLite, HDF5, and ArcticDB. This book shows you how to use SciPy and statsmodels to identify alpha factors and hedge risk, and construct momentum and mean-reversion factors. You’ll optimize strategy parameters with walk-forward optimization using vectorbt and construct a production-ready backtest using Zipline Reloaded. Implementing all that you’ve learned, you’ll set up and deploy your algorithmic trading strategies in a live trading environment using the Interactive Brokers API, allowing you to stream tick-level data, submit orders, and retrieve portfolio details.
- Acquire and process freely available market data with the OpenBB Platform
- Build a research environment and populate it with financial market data
- Use machine learning to identify alpha factors and engineer them into signals
- Use VectorBT to find strategy parameters using walk-forward optimization
- Build production-ready backtests with Zipline Reloaded and evaluate factor performance
- Set up the code framework to connect and send an order to Interactive Brokers
By the end of this Python for Algorithmic Trading Cookbook book, you’ll not only have grasped the essential concepts but also the practical skills needed to implement and execute sophisticated trading strategies using Python.