The Science of Algorithmic Trading and Portfolio Management: Applications Using Advanced Statistics, Optimization, and Machine Learning Techniques
Language: English
Published by Academic Press, 2013
- First Edition
- Hardcover
- Used




Seller: Chapter Two (Chesham), Chesham, United KingdomChapter Two (Chesham)
AbeBooks seller since December 10, 2019
Condition: Used - Good
US$ 48.32
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- Title
- The Science of Algorithmic Trading and Portfolio Management: Applications Using Advanced Statistics, Optimization, and Machine Learning Techniques
- Author
- Kissell, Robert
- Publisher
- Academic Press
- Publication year
- 2013
- Condition
- Good
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 0124016898
- ISBN 13
- 9780124016897
- Edition
- 1st Edition
- Item weight
- 1,179 grams
- Dimensions
- 19.81 centimeters width by 23.62 centimeters height by 3.05 centimeters depth
The Science of Algorithmic Trading and Portfolio Management, with its emphasis on algorithmic trading processes and current trading models, sits apart from others of its kind. Robert Kissell, the first author to discuss algorithmic trading across the various asset classes, provides key insights into ways to develop, test, and build trading algorithms. Readers learn how to evaluate market impact models and assess performance across algorithms, traders, and brokers, and acquire the knowledge to implement electronic trading systems.
This valuable book summarizes market structure, the formation of prices, and how different participants interact with one another, including bluffing, speculating, and gambling. Readers learn the underlying details and mathematics of customized trading algorithms, as well as advanced modeling techniques to improve profitability through algorithmic trading and appropriate risk management techniques. Portfolio management topics, including quant factors and black box models, are discussed, and an accompanying website includes examples, data sets supplementing exercises in the book, and large projects.
- Prepares readers to evaluate market impact models and assess performance across algorithms, traders, and brokers.
- Helps readers design systems to manage algorithmic risk and dark pool uncertainty.
- Summarizes an algorithmic decision making framework to ensure consistency between investment objectives and trading objectives.
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About the Author
"About the title" may belong to another edition of this title.
Chapter Two (Chesham)
Chesham, United Kingdom
AbeBooks seller since December 10, 2019
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