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

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

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Hvad der skiller sig ud

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.

Produktdetaljer

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 Danmark. 1838982884
  • Discover how to build and backtest algorithmic trading strategies with ZiplineKey FeaturesGet to grips with market data and stock analysis and visualize data to gain quality insightsFind out how to systematically approach quantitative research and strategy generation/backtesting in algorithmic tradingLearn how to navigate the different features in Python's data analysis librariesBook DescriptionAlgorithmic trading helps you stay ahead of the markets by devising strategies in quantitative analysis to gain profits and cut losses.The book starts by introducing you to algorithmic trading and explaining why Python is the best platform for developing trading strategies. You'll then cover quantitative analysis using Python, and learn how to build algorithmic trading strategies with Zipline using various market data sources. Using Zipline as the backtesting library allows access to complimentary US historical daily market data until 2018. As you advance, you will gain an in-depth understanding of Python libraries such as NumPy and pandas for analyzing financial datasets, and explore Matplotlib, statsmodels, and scikit-learn libraries for advanced analytics. You'll also focus on time series forecasting, covering pmdarima and Facebook Prophet.By the end of this trading book, you will be able to build predictive trading signals, adopt basic and advanced algorithmic trading strategies, and perform portfolio optimization.What you will learnDiscover how quantitative analysis works by covering financial statistics and ARIMAUse core Python libraries to perform quantitative research and strategy development using real datasetsUnderstand how to access financial and economic data in PythonImplement effective data visualization with MatplotlibApply scientific computing and data visualization with popular Python librariesBuild and deploy backtesting algorithmic trading strategiesWho this book is forThis book is for data analysts and financial traders who want to explore how to design algorithmic trading strategies using Python's core libraries. If you are looking for a practical guide to backtesting algorithmic trading strategies and building your own strategies, then this book is for you. Beginner-level working knowledge of Python programming and statistics will be helpful.Table of ContentsIntroduction to algorithmic tradingExploratory Data Analysis in PythonHigh-speed Scientific Computing using NumPyData Manipulation and Analysis with PandasData Visualization using MatplotlibStatistical Estimation, Inference, and PredictionFinancial Market Data Access in PythonIntroduction to Zipline and PyFolioFundamental algorithmic trading strategies
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)

Hvem bør købe?

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.

Produktbeskrivelse

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  • spørgsmål: Hvordan shopper man Hands-On Financial Trading with Python: A practical online fra Ubuy?

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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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Fordele

  • 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.

Ulemper

  • May require some statistical background for deeper comprehension, particularly in advanced chapters.

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