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Can I read Python for Algorithmic Trading Cookbook : Recipes for Designing, Building, and Deploying Algorithmic Trading Strategies with Python on EtoBox?
Python for Algorithmic Trading Cookbook : Recipes for Designing, Building, and Deploying Algorithmic Trading Strategies with Python by Jason Strimpel is a nonfiction available to read on EtoBox.
What is Python for Algorithmic Trading Cookbook : Recipes for Designing, Building, and Deploying Algorithmic Trading Strategies with Python about?
Harness the power of Python libraries to transform freely available financial market data into algorithmic trading strategies and deploy them into a live trading environmentKey FeaturesFollow practical Python recipes to acquire, visualize, and store market data for market researchDesign, backtest, and evaluate the performance of trading strategies using professional techniquesDeploy trading strategies built in Python to a live trading environment with API connectivityPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionDiscover 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 book 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. T
Who reads Python for Algorithmic Trading Cookbook : Recipes for Designing, Building, and Deploying Algorithmic Trading Strategies with Python?
It is typically read by self-directed learners exploring a subject in depth.
Common subject areas: history, science, philosophy, social sciences.
- Author
- Jason Strimpel
- Publisher
- Packt Publishing Pvt Ltd
- Published
- 2024
- Language
- EN
- ISBN
- 9781835084700
- Category
- nonfiction
- Subjects
- Computer Science, Finance, Language Learning
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