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 st
Python for Algorithmic Trading: From Idea to Cloud Deployment
β Scribed by Yves Hilpisch
- Publisher
- O'Reilly Media
- Year
- 2020
- Tongue
- English
- Leaves
- 382
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
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 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. By 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
π SIMILAR VOLUMES
<div><p>The financial industry is adopting Python at an increasing rate. Top hedge funds use the language on a daily basis for quantitative research, data exploration, and analysis and for prototyping, testing, and executing trading strategies. Thereβs also a rise in trading activity by individuals
<div><p>The financial industry is adopting Python at an increasing rate. Top hedge funds use the language on a daily basis for quantitative research, data exploration, and analysis and for prototyping, testing, and executing trading strategies. Thereβs also a rise in trading activity by individuals
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 st
<p><span>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</span></p><h4><span>Key Features</span></h4><ul><li><span><span>Follow practical Python recipes to acquire, visualize
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 Key Features - Follow practical Python recipes to acquire, visualize, and store market data for market research - Design,