Step-by-step Python code examples for algorithmic trading enable hands-on learning and application
Covers backtesting, financial data retrieval, and machine learning for comprehensive strategy development
Includes real-time data processing and integration with Oanda and FXCM platforms for practical deployment
Explains vectorization and data analysis with NumPy and Pandas for efficient financial analytics
Provides access to public and proprietary financial data sources for robust analysis
Summarized by Shop
Algorithmic trading, once the exclusive domain of institutional players, is now open to small organizations and individual traders using online platforms. The tool of choice for many traders today is Python and its ecosystem of powerful packages. In this practical book, author Yves Hilpisch shows students, academics, and practitioners how