Hands-On Financial Trading with Python: A practical guide to using Zipline and other Python libraries for backtesting trading strategies
genuine image
Hands-On Financial Trading with Python: A practical guide to using Zipline and other Python libraries for backtesting trading strategies
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.
Hands-On Financial Trading with Python: A practical guide to using Zipline and other Python libraries for backtesting trading strategies
зүйлийн дугаар: 34798096

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

зүйлийн дугаар: 34798096

MNT 225004

Price Details

Excluding Shipping & Custom charges ( Shipping and custom charges will be calculated on checkout )

*All items will import from АНУ

Нөөцөд байна
АНУ USA дэлгүүрээс импортолсон

QTY:

Яг одоо захиалаад ойрын хугацаанд хүлээн аваарай Пүрэв гараг, 6 дугаар сар 25
Secured transactionsecured 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.

Our Top Logistics Partners
  • fedex
  • dhl
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.
Илүүг харах
U-Care баталгаа:
Байхгүй
Төлөвлөгөө сонгох
fast shipping

Fast
Shipping

free return

Free
Return*

secure packaging

Secure Packaging

100% original products

100% Original Products

pci-dss

PCI DSS Compliance

iso certified

ISO 27001 Certified

paypal payment
visa payment
mastercard payment
Note: Step Down Voltage Transformer required for using electronics products of АНУ store (110-120). Recommended power converters Одоо худалдаж авах.

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.

Бүтээгдэхүүний дэлгэрэнгүй мэдээлэл

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 Mongolia. 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)

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.

  • Non-Coders

    Individuals lacking programming skills would struggle with the technical aspects of Python and trading libraries.

  • Casual Investors

    Investors seeking simple investment strategies may find backtesting and programming unnecessarily complex for their needs.

БАРААНЫ ТАЙЛБАР

Асуулга байна уу? Бидэнтэй чатлаарай

Хэрэглэгчийн асуулт ба хариултууд

  • Асуулт: What is 'Hands-On Financial Trading with Python' about?

    Хариулт: This book serves as a comprehensive guide for finance enthusiasts looking to harness the power of Python in trading. It covers essential concepts on using the Zipline library and other Python tools for backtesting trading strategies. Readers can expect to learn how to analyze historical data, evaluate trading performance, and optimize strategies, making it a valuable resource for anyone aiming to enhance their trading skills using Python.
  • Асуулт: Who is the target audience for this book?

    Хариулт: The book is aimed at traders, financial analysts, and data enthusiasts who have a basic understanding of Python programming. It also caters to individuals eager to delve into quantitative finance and algorithmic trading. By bridging the gap between coding and financial knowledge, this book allows beginners and seasoned professionals alike to utilize Python for effective strategy implementation.
  • Асуулт: Do I need prior programming experience to read this book?

    Хариулт: While some familiarity with Python will be beneficial, the book is written in an accessible manner for users at various skill levels. It provides foundational concepts and gradually builds towards more complex topics, making it approachable. Readers who are motivated can easily follow along even if they are relatively new to programming, thanks to practical examples and clear explanations.
  • Асуулт: What are the key features of the book?

    Хариулт: Key features include step-by-step tutorials on using Zipline for backtesting, practical examples that illustrate key concepts, and insights into various Python libraries essential for financial analysis. Additionally, the book emphasizes real-world application, showcasing how to apply theoretical knowledge to real trading scenarios effectively. This hands-on approach facilitates deeper learning and understanding of financial trading dynamics.
  • Асуулт: Can I apply the concepts learned in this book to real trading?

    Хариулт: Absolutely! The skills and techniques outlined in the book are designed with real-world application in mind. Readers can implement backtested strategies derived from the examples to make informed trading decisions. By following the guidelines provided, traders can create robust algorithms that adapt to market changes, enhancing their chances for success in live trading environments.
  • Асуулт: What tools do I need in conjunction with this book?

    Хариулт: To get the most out of this book, having a working environment set up with Python and required libraries (like Zipline, Pandas, etc.) is essential. Additionally, using tools such as Jupyter Notebook can enhance your learning experience, allowing you to run and experiment with code snippets interactively. These resources enable a more hands-on approach to learning and applying financial trading concepts.
  • Асуулт: Is backtesting covered in detail in this book?

    Хариулт: Yes, backtesting is one of the central themes of the book. It provides in-depth guidance on how to leverage Zipline to backtest trading strategies effectively. By learning the intricacies of backtesting, traders can assess the profitability of their strategies against historical data, which is crucial for understanding potential performance before engaging in real trading, significantly reducing risks.
  • Асуулт: What Python libraries are covered in this book?

    Хариулт: The book focuses on several vital Python libraries, with Zipline being a primary one for backtesting. It also introduces libraries like Pandas for data manipulation, NumPy for numerical calculations, and Matplotlib for data visualization. Understanding these libraries equips readers with a toolkit essential for executing and analyzing trading strategies within the Python ecosystem.
  • Асуулт: How is the book structured?

    Хариулт: The book is structured logically, beginning with foundational concepts of financial trading and gradually progressing to more advanced topics like strategy implementation and optimization. Each chapter builds on the last, reinforcing previously learned material while introducing new ideas and challenges. Specific chapters are dedicated to hands-on projects, allowing readers to practice their skills in real-time.
  • Асуулт: Where can I buy 'Hands-On Financial Trading with Python'?

    Хариулт: You can purchase 'Hands-On Financial Trading with Python: A practical guide to using Zipline and other Python libraries for backtesting trading strategies' on Ubuy in Mongolia. Ubuy offers a convenient platform for acquiring this essential resource, helping you embark on your journey towards mastering financial trading with Python.

Python 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." **

Customer Reviews & Ratings

4.2
35 Хэрэглэгчийн үнэлгээ
  • 5 од
    68%
  • 4 од
    8%
  • 3 од
    12%
  • 2 од
    6%
  • 1 од
    6%

Энэ бараанд шүүмж өгөх

Бусад хэрэглэгчидтэй санал бодлоо хуваалцана уу

Давуу тал

  • 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.

Сул талууд

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

Product Price History

Чухал мэдээлэл

  • Хязгаарлалт : Олон улсын хүргэлтээр илгээгдсэн барааны тохиолдолд, үйлдвэрлэгчийн баталгаа хүчингүй байх, үйлдвэрлэгчийн үйлчилгээ хүргэх боломжгүй, барааны заавар, гарын авлага болон анхааруулга очих улсын хэлдээр биш байх магадлалтай гэдгийг анхаарна уу. Мөн бараа болон дагалдах хэрэгсэл нь тухайн улсын стандартыг мөрдөөгүй, чанарын заалт болон шошгын шаардлагыг хангаагүй байх магадлалтай бөгөөд, тухайн улсын цахилгааны вольтод тохирохгүй байж болзошгүй (тохирох адаптер болон хувиргагч шаардлагатай) юм. Хүлээн авагч нь барааг тухайн улс уруу хуулийн дагуу импортлогдохыг батлах ёстой. Ubuy болон түүний холбоот түншүүдээс худалдан авсан тохиолдолд худалдан авагч нь хүлээн авах улсын бүх хууль болон заалтуудыг мөрдөх ёстой.
  • Ubuy нь дэлхий даяар хэрэглэгддэг хайлтын хэрэгсэл учраас Ubuy дээр байгаа бараа бүр зарагдана гэсэн үг биш. Бараанууд нь экспорт болон худалдааны журмыг дагаж мөрдөх ёстой.

MNT 225004

Яг одоо захиалаад ойрын хугацаанд хүлээн аваарай Пүрэв гараг, 6 дугаар сар 25

QTY:

Secured transactionsecured 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.

Our Top Logistics Partners
  • fedex
  • dhl
Fastest cross-border delivery

Онцлог & Давуу талууд

  • 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.