Machine Learning for Asset Managers (Hardcover)

Language: English

Published by Cambridge University Press, Cambridge, 2026

1009702424 / 9781009702423

Series: Book 1 of 7 - Elements in Quantitative Finance

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Hardcover. Successful investment strategies are specific implementations of general theories. An investment strategy that lacks a theoretical justification is likely to be false. Hence, an asset manager should concentrate her efforts on developing a theory rather than on backtesting potential trading rules. The purpose of this Element is to introduce machine learning (ML) tools that can help asset managers discover economic and financial theories. ML is not a black box, and it does not necessarily overfit. ML tools complement rather than replace the classical statistical methods. Some of ML's strengths include (1) a focus on out-of-sample predictability over variance adjudication; (2) the use of computational methods to avoid relying on (potentially unrealistic) assumptions; (3) the ability to learn complex specifications, including nonlinear, hierarchical, and noncontinuous interaction effects in a high-dimensional space; and (4) the ability to disentangle the variable search from the specification search, robust to multicollinearity and other substitution effects. The purpose of this Element is to introduce machine learning (ML) tools that can help asset managers discover economic and financial theories. ML is not a black box, and it does not necessarily overfit. ML tools complement rather than replace the classical statistical methods. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Seller Inventory # 9781009702423

Title
Machine Learning for Asset Managers (Hardcover)
Author
Marcos M. Lopez de Prado
Publisher
Cambridge University Press, Cambridge
Publication year
2026
Condition
new
Binding
Hardcover
Language
English
ISBN 10
1009702424
ISBN 13
9781009702423
Series
Book 1 of 7: Elements in Quantitative Finance

Grand Eagle Retail

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