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Hands-On Financial Trading with Python: A practical guide to using Zipline and other Python libraries for backtesting trading strategies
Item #: 34798096

Hands-On Financial Trading with Python: A practical guide to using Zipline and other Python libraries for backtesting trading strategies

Item #: 34798096

AUD 107

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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

Shop Hands-On Financial Trading with Python: A practical guide to using Zipline and other Python libraries for backtesting trading strategies online at a best price in Australia. 1838982884
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?

Suitable For
  • Aspiring Traders

    Individuals looking to learn financial trading strategies with practical Python applications for successful trading.

  • Quantitative Analysts

    Professionals wanting to enhance their skills in using Python for backtesting and creating trading algorithms.

  • Python Developers

    Software engineers interested in applying their Python skills to the financial markets for algorithmic trading.

Not Suitable For
  • Beginners in Finance

    People with no prior knowledge of finance may find the content too technical and challenging to comprehend.

Product Description

Hands-On Financial Trading with Python: A practical guide to using Zipline and other Python libraries for backtesting trading strategies

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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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