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Python for Algorithmic Trading: From Idea to Cloud Deployment
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Python is the tool of choice for many traders today, showing readers how to use Python in the fascinating field of algorithmic trading.
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Produktdetaljer
- Learn how to apply Python in algorithmic trading
- Explore backtesting trading strategies and interacting with online platforms
- Master vectorization for financial analytics with NumPy and pandas
- Generate market predictions using machine learning and deep learning
- Implement automated algorithmic trading strategies with popular trading platforms
- Set up a Python environment for algorithmic trading and cloud deployment
| Publisher | O'Reilly Media |
| Publication date | December 22, 2020 |
| Edition | 1st |
| Language | English |
| Print length | 378 pages |
| ISBN-10 | 149205335X |
| ISBN-13 | 978-1492053354 |
| Item Weight | 2.31 pounds (1.05 kg) |
| Dimensions | 7.25 x 0.75 x 9.25 inches (18.4 x 1.9 x 23.5 cm) |
Hvem bør købe?
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Aspiring Traders
Individuals looking to enter algorithmic trading and need a structured approach to understand Python implementation effectively.
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Data Scientists
Professionals wanting to expand their skill set to include finance, and develop trading algorithms using Python.
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Developers
Software engineers interested in applying their programming skills to financial applications and cloud deployments.
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Beginner Coders
Users with no prior programming experience might find the content too advanced without foundational skills in Python.
Produktbeskrivelse
About This Item
Looking to dive into the exciting world of algorithmic trading? Look no further than "Python for Algorithmic Trading: From Idea to Cloud Deployment 1st Edition." This comprehensive book is the ultimate guide for anyone interested in algorithmic trading using the power of Python. Whether you're a beginner or an experienced trader, this book is packed with valuable insights and techniques to take your trading strategies to the next level. With Python as your weapon of choice, you'll learn how to implement advanced trading algorithms, develop efficient models, and optimize your strategies for maximum profitability. This book takes a hands-on approach, providing real-world examples and practical exercises that will help you apply these concepts to your own trading endeavors. Featuring a Pythonic approach, this book explores various strategies and tools that are essential for Algorithmic Trading success.
You'll discover how to leverage Python libraries and powerful algorithms to backtest your strategies, analyze market data, and manage your trading portfolio with precision. Not only will you gain a deep understanding of the Python programming language, but you'll also learn how to utilize machine learning techniques, neural networks, and sentiment analysis to make informed trading decisions. Dive into the world of high-frequency trading, market making, and order execution, and learn how to harness Python's capabilities to excel in these areas. This book doesn't stop at theory – it also provides practical guidance on deploying your algorithms to the cloud for real-time trading data analysis. With step-by-step instructions, you'll learn how to build a robust algorithmic trading platform that can handle massive amounts of data, giving you a competitive edge in the financial markets. Whether you're an aspiring quant, a seasoned trader, or a programmer looking to apply your skills to the world of finance, "Python for Algorithmic Trading: From Idea to Cloud Deployment 1st Edition" is your go-to resource.
Start your journey today and unlock the potential of algorithmic trading with Python.
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Egenskaber og fordele
- Algorithmic trading is now open to small organizations and individual traders using online platforms.
- This practical book shows you how to use Python in the field of algorithmic trading.
- Learn how to retrieve financial data, vectorization for financial analytics with NumPy and pandas, and master vectorized backtesting.
- Explore systematic ways to build and deploy automated algorithmic trading strategies.
- Generate market predictions by using machine learning and tackle real-time processing of streaming data with socket programming tools.
- Implement automated algorithmic trading strategies with the OANDA and FXCM trading platforms.
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