Quantitative Trading: How to Build Your Own Algori Format: Cloth
Language: English
Published by John Wiley and Sons, 2021
- Hardcover
- New
Seller: INDOO, Avenel, NJ, U.S.A.INDOO
AbeBooks seller since August 9, 2004
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Add to basketSeller Inventory # 9781119800064
- Title
- Quantitative Trading: How to Build Your Own Algori Format: Cloth
- Author
- Ernest P. Chan
- Publisher
- John Wiley and Sons
- Publication year
- 2021
- Condition
- New
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 1119800064
- ISBN 13
- 9781119800064
- Edition
- 2nd Edition
Master the lucrative discipline of quantitative trading with this insightful handbook from a master in the field
In 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 examples
- A new technique on optimizing parameters with changing market regimes using machine learning.
- A guide to selecting the best traders and advisors to manage your money
Perfect 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.
"Synopsis" may belong to another edition of this title.
About the Author
ERNEST P. CHAN, PhD, is an expert in the application of statistical models and software for trading currencies, futures, and stocks. He holds a doctorate in theoretical physics from Cornell University and is Managing Member of investment management firm QTS Capital Management and founder of financial machine learning firm Predictnow.ai.
"About the title" may belong to another edition of this title.
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