Python for Finance, 2nd Edition

Part IV. Algorithmic Trading

This part of the book is about the use of Python for algorithmic trading. More and more trading platforms and brokers allow their clients to use, for example, REST APIs to programmatically retrieve historical data or streaming data, or to place buy and sell orders. What has been the domain of large financial institutions for a long period now has become accessible even to retail algorithmic traders. In this space, Python has secured a top position as a programming language and technology platform. Among other factors, this is driven by the fact that many trading platforms, such as the one from FXCM Forex Capital Markets, provide easy-to-use Python wrapper packages for their REST APIs.

This part of the book comprises three chapters:

• Chapter 14 introduces the FXCM trading platform, its REST API, and the fxcmpy wrapper package.

• Chapter 15 focuses on the use of methods from statistics and machine learning to derive algorithmic trading strategies; the chapter also shows how to use vectorized backtesting.

• Chapter 16 looks at the deployment of automated algorithmic trading strategies; it addresses capital management, backtesting for performance and risk, online algorithms, and deployment.