Name: Machine Learning for Asset Managers (Elements in Quantitative Finance) (en Inglés)
SKU: 52922203
Price: 33.30 USD
Availability: InStock
Author: López de Prado, Marcos M.
ISBN: 9781108792899

portada Machine Learning for Asset Managers (Elements in Quantitative Finance) (en Inglés)

Machine Learning for Asset Managers (Elements in Quantitative Finance) (en Inglés)

Formato

Libro Físico

Autor

Marcos M. López de Prado

Editorial

Cambridge University Press

Año

2020

Idioma

Inglés

N° páginas

152

Encuadernación

Tapa Blanda

Dimensiones

22.9x15.2x0.8 cm

Peso

0.21 kg.

ISBN13

9781108792899

Categorías

Finanzas

Machine Learning for Asset Managers (Elements in Quantitative Finance) (en Inglés)

Marcos M. López de Prado (Autor) · Cambridge University Press · Tapa Blanda

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Reseña del libro "Machine Learning for Asset Managers (Elements in Quantitative Finance) (en Inglés)"

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.