Python for algorithmic trading : from idea to cloud deployment

Includes bibliographical references and index.

1. Python and algorithmic trading -- 2. Python infrastructure -- 3. Working with financial data -- 4. Mastering vectorized backtesting -- 5. Predicting market movements with machine learning -- 6. Building classes for event-based backtesting -- 7. Working with real-time data and sockets -- 8. CFD trading with Oanda -- 9. FX trading with FXCM -- 10. Automating trading operations.

Algorithmic trading, once the exclusive domain of institutional players, is now open to small organizations and indivisual traders using online platforms. The tool of choice for many traders today is Python and its ecosystems of powerful packages. In this practical book, author Yves Hilpisch shows students, academics, and practitioners how to use Python in the fascinating field of algorithmic trading. You'll learn several ways to apply Python to different aspects of algorithmic trading, such as backtesting trading strategies and interacting with online trading platforms. Some of the biggest buy and sell-side institutions make heavy use of Python. Ny exploring options for systematically building and deploying automated algorithmic trading strategies, this book will help you level the playing field. Set up a proper Python environment for algorithmic trading ; Learn how to retrieve financial data from public and proprietary data sources ; Explore vectorization for financial analytics with NumPy and pandas ; Master vectorized backtesting of different algorithmic trading strategies ; Generate market predictions by using machine learning and deep learning ; Tackle real-time processing of streaming data with socket programming tools ; Implement automated algorithmic trading strategies with the OANDA and FXCM trading platforms.