Quantitative Trading: How to Build Your Own Algorithmic Trading Business (Wiley Trading)
Quantitative Trading: How to Build Your Own Algorithmic Trading Business (Wiley Trading)
Master the lucrative discipline of quantitative trading with this insightful handbook from a master in the field.
Quantitative Trading: How to Build Your Own Algorithmic Trading Business (Wiley Trading)
Nº de artículo: 90458706

Quantitative Trading: How to Build Your Own Algorithmic Trading Business (Wiley Trading)

Nº de artículo: 90458706

HNL 2029

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What Stands Out

Comprehensive Guide
Covers all aspects of building algorithmic trading systems, making it suitable for beginners and experienced traders alike. Offers step-by-step strategies to implement successful quantitative trading methodologies.
Expert Insights
Authored by industry experts, providing valuable knowledge and real-world examples that enhance understanding. Enables users to learn from experienced professionals, improving their trading strategies and decision-making.
Practical Applications
Focuses on actionable techniques and tools, ensuring readers can apply concepts immediately. Addresses common trading challenges, empowering readers to create effective algorithms that adapt to market changes.

Detalles de producto

Shop Quantitative Trading: How to Build Your Own Algorithmic Trading Business (Wiley Trading) online at a best price in Honduras. 1119800064
  • Master the lucrative discipline of quantitative trading with this insightful handbook from a master in the fieldIn the newly revised Second Edition of Quantitative Trading: How to Build Your Own Algorithmic Trading Business, quant trading expert Dr. Ernest P. Chan shows you how to apply both time-tested and novel quantitative trading strategies to develop or improve your own trading firm.You'll discover new case studies and updated information on the application of cutting-edge machine learning investment techniques, as well as:Updated back tests on a variety of trading strategies, with included Python and R code examplesA new technique on optimizing parameters with changing market regimes using machine learning.A guide to selecting the best traders and advisors to manage your moneyPerfect for independent retail traders seeking to start their own quantitative trading business, or investors looking to invest in such traders, this new edition of Quantitative Trading will also earn a place in the libraries of individual investors interested in exploring a career at a major financial institution.
Publisher Wiley
Publication date 16 Sept. 2021
Edition 2nd
Language English
Print length 256 pages
ISBN-10 1119800064
ISBN-13 978-1119800064
Item weight 210 g
Dimensions 16 x 2.79 x 23.11 cm

Who Should Buy?

Suitable For
  • Aspiring Traders

    Individuals eager to start algorithmic trading and seeking practical strategies to build their trading business.

  • Data Analysts

    Professionals proficient in data analysis looking to apply their skills in the financial markets through algorithmic trading.

  • Finance Students

    Students studying finance who wish to gain insights into quantitative methods and algorithmic trading applications.

Not Suitable For
  • Beginner Investors

    Individuals with no trading experience may find the material too advanced without foundational knowledge in trading.

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Preguntas y respuestas de los clientes

  • Pregunta: Who is the target audience for this book?

    Respuesta: This book is perfect for independent retail traders seeking to start their own quantitative trading business or investors looking to invest in such traders.
  • Pregunta: What will the readers learn from this book

    Respuesta: Readers will learn time-tested and novel quantitative trading strategies as well as new case studies and the latest machine learning investment techniques, optimization techniques with changing market regimes, and a guide to selecting the best traders and advisors to manage their money.
  • Pregunta: Does the book provide code examples?

    Respuesta: Yes, the book provides both Python and R code examples.

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