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This practical Python book will introduce you to Python and tell you exactly why it's the best platform for developing trading strategies. As you advance, you will gain an in-depth understanding of Python libraries and explore Matplotlib, statsmodels, and scikit-learn libraries for advanced analytics.
Item #:
34798096
Hands-On Financial Trading with Python: A practical guide to using Zipline and other Python libraries for backtesting trading strategies
Item #:
34798096
ZAR 1279
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This practical Python book will introduce you to Python and tell you exactly why it's the best platform for developing trading strategies. As you advance, you will gain an in-depth understanding of Python libraries and explore Matplotlib, statsmodels, and scikit-learn libraries for advanced analytics.
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What Stands Out
Practical Application
Offers hands-on experience with real trading scenarios by utilizing Python libraries for effective strategy backtesting, ensuring users can apply learned concepts directly to their trading practices.
Comprehensive Coverage
Covers various tools and techniques, including Zipline, providing a broad understanding of financial trading methodologies while catering to both beginners and experienced traders seeking to enhance their skills.
User-Friendly Approach
Designed with clarity and accessibility in mind, this guide breaks down complex topics into manageable sections, making it easier for users to grasp essential trading concepts and significantly boosting their confidence.
Product Details
- A practical guide for financial trading with Python
- Covers the use of Zipline and other Python libraries for backtesting trading strategies
- Provides hands-on experience in applying Python to financial trading
- Offers guidance on implementing and testing trading strategies
- Useful resource for individuals interested in algorithmic trading and quantitative finance
- Written to help readers gain practical skills in financial trading using Python
| Publisher | Packt Publishing |
| Publication date | April 29, 2021 |
| Language | English |
| Print length | 360 pages |
| ISBN-10 | 1838982884 |
| ISBN-13 | 978-1838982881 |
| Item Weight | 1.36 pounds (620 grams) |
| Dimensions | 7.5 x 0.82 x 9.25 inches (19.1 x 2.1 x 23.5 cm) |
Who Should Buy?
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Aspiring Traders
Individuals looking to learn financial trading strategies with practical Python applications for successful trading.
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Quantitative Analysts
Professionals wanting to enhance their skills in using Python for backtesting and creating trading algorithms.
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Python Developers
Software engineers interested in applying their Python skills to the financial markets for algorithmic trading.
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Beginners in Finance
People with no prior knowledge of finance may find the content too technical and challenging to comprehend.
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Non-Coders
Individuals lacking programming skills would struggle with the technical aspects of Python and trading libraries.
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Casual Investors
Investors seeking simple investment strategies may find backtesting and programming unnecessarily complex for their needs.
Product Description
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Mathematical & Statistical Editorial Review
**** "Holding the reins of algorithmic trading in Python is made accessible with 'Hands-on Financial Trading with Python'. This book comes highly recommended for aspiring algo traders, particularly those who are willing to delve into practical applications using Python. Readers commend chapters focused on essential libraries like NumPy, Pandas, and Matplotlib, which are presented with clear, hands-on coding examples that facilitate easy comprehension and implementation. However, navigating the more detailed chapters, especially those involving time series models and statistical backgrounds, may pose challenges for beginners. Some feedback suggests that while the book serves as an excellent introduction to various aspects of trading, it may only skim the surface of more advanced concepts, necessitating further exploration into specialized literature for deeper knowledge. Although much of the information is practical and instructive, there have been critiques regarding the lack of explanations surrounding certain coding values and outcomes, leaving some confusion among readers about the book's suitability for their level of expertise. The inclusion of real-world scenarios demonstrates the author's understanding of the aio trading environment and aligns with the practical needs of readers. Particularly noted is the treatment of zipline, with many readers appreciating the insights on installation and setup amidst a scarcity of reliable resources. The suggestion for a new chapter on zipline-trader indicates that even amidst the positive reception, there is room for expansion and improvement. In summary, 'Hands-on Financial Trading with Python' engages readers with its structured approach to algorithmic trading, aided by practical examples. Yet, potential buyers should bear in mind that while the book serves as a user-friendly entry point, those seeking comprehensive understanding might still need to pursue additional resources to fully grasp the complexities of the field." **
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Pros
- Comprehensive and practical approach to Python libraries like NumPy, Pandas, and Matplotlib.
- Clear coding examples that enhance understanding.
- Gradual build-up of concepts aiding the learning process.
- Helpful resource for those new to algorithmic trading or looking to expand their toolkit.
Cons
- May require some statistical background for deeper comprehension, particularly in advanced chapters.
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ZAR 1279
Order now and get it around Thursday, June 25
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Secured transaction
Ubuy works hard to protect your security and privacy. Our advanced payment security system ensures confidentiality by encrypting your information during transmission using AES (Advanced Encryption Standards) and SSL (Secure Socket Layer) protocols. Your payment details are 100% secure as we do not share your payment details with third party sellers.
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Features & Benefits
- Learn Python and its best data libraries for effective trading strategies.
- Go from creating a backtesting system to deploying it.
- Gain in-depth knowledge of quantitative analysis and financial statistics.
- Master data visualization and scientific computing using popular Python libraries.
- Ability to build and deploy algorithmic trading strategies.
- Suitable for both financial traders and data analysts wanting hands-on exposure to developing algorithmic trading strategies.