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Artikelnr.:
90458706
Quantitative Trading: How to Build Your Own Algorithmic Trading Business (Wiley Trading)
Artikelnr.:
90458706
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Master the lucrative discipline of quantitative trading with this insightful handbook from a master in the field.
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Wat opvalt
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 inzichten
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.
Productdetails
- 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.
| Uitgever | Wiley |
| Publicatiedatum | 16 Sept. 2021 |
| Editie | 2nd |
| Taal | Nederlands |
| Afdruklengte | 256 pages |
| ISBN-10 | 1119800064 |
| ISBN-13 | 978-1119800064 |
| Artikelgewicht | 210 g |
| Afmetingen | 16 x 2.79 x 23.11 cm |
Voor wie is dit geschikt?
-
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.
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Finance Students
Students studying finance who wish to gain insights into quantitative methods and algorithmic trading applications.
-
Beginner Investors
Individuals with no trading experience may find the material too advanced without foundational knowledge in trading.
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vraag:
Who is the target audience for this book?
antwoord: This book is perfect for independent retail traders seeking to start their own quantitative trading business or investors looking to invest in such traders. -
vraag:
What will the readers learn from this book
antwoord: 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. -
vraag:
Does the book provide code examples?
antwoord: Yes, the book provides both Python and R code examples.
Investments & Securities Editorial Review
**** "Quantitative Trading: How to Build Your Own Algorithmic Trading Business" by Ernie Chan has elicited a mixed reception among readers, reflecting a wide spectrum of experiences with the book's content and structure. While some readers appreciate the book's foundational insights into quantitative trading, including backtesting and various trading strategies, others critique its clarity and depth. Positive reviews highlight the book's accessible overview of complex topics, making it a potentially valuable resource for beginners intrigued by quantitative trading. Particular emphasis is placed on the understanding of backtesting and the Prospect of starting an individual trading fund, resonating with those eager to enter the field. The anecdotes shared by Chan about trading in a professional environment provide a relatable context that enhances learning for some readers, who find comfort in the author's real-world experiences. Conversely, the book faces significant criticism, particularly regarding its writing quality and the technical clarity of its coding examples. Many readers express frustration over grammatical errors and poorly structured explanations, leading to a perception that the book lacks substance and depth. Detractors argue that the content is overly simplistic, suggesting that it could be condensed into a smaller format without losing essential insights. Some reviewers go as far as to deem the book as little more than an advertisement for Chan's other services, undermining the perceived integrity of the material. Overall, while "Quantitative Trading" has its merits, especially as a light introduction to algorithmic trading concepts, it also falls short in delivering thorough, well-structured content that meets the needs of more advanced readers or those seeking practical guidance in quantitative methodologies. **
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- Accessible introduction to quantitative trading concepts for beginners.
- Valuable insights into backtesting and starting a quantitative fund.
- Author shares relatable real-world trading experiences.
Nadelen
- Poor writing quality and numerous grammatical errors.
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- Learn time-tested and novel quantitative trading strategies.
- Discover case studies and the latest machine learning investment techniques.
- Get Python and R code examples.
- Learn optimization techniques with changing market regimes.
- Guide to selecting the best traders and advisors to manage your money.
- Suitable for independent retail traders or investors looking for such traders.
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