Name: Machine Learning for Asset Management and Pricing (en Inglés)
SKU: 67193118
Price: 109.18 USD
Availability: InStock
Author: Henry Schellhorn;Tianmin Kong

portada Machine Learning for Asset Management and Pricing (en Inglés)

Machine Learning for Asset Management and Pricing (en Inglés)

Formato

Libro Físico

Editorial

SIAM - Society for Industrial and Applied Mathematics

Autor

Henry Schellhorn;Tianmin Kong

Año

2024

Idioma

Inglés

N° páginas

277

Encuadernación

Tapa Blanda

ISBN13

9781611977899

Machine Learning for Asset Management and Pricing (en Inglés)

Henry Schellhorn;Tianmin Kong (Autor) · SIAM - Society for Industrial and Applied Mathematics · Tapa Blanda

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Reseña del libro "Machine Learning for Asset Management and Pricing (en Inglés)"

Covers the latest advances in machine-learning methods for asset management and asset pricing. Cutting-edge material is integrated with mainstream finance theory and statistical methods to provide a coherent narrative.

This textbook covers the latest advances in machine-learning methods for asset management and asset pricing. Recent research in deep learning applied to finance shows that some of the techniques used by asset managers (usually kept confidential) result in better investments than the more standard techniques. Cutting-edge material is integrated with mainstream finance theory and statistical methods to provide a coherent narrative. Coverage includesan original machine learning method for strategic asset allocation;the no-arbitrage theory applied to a wide portfolio of assets as well as other asset management methods, such as mean-variance, Bayesian methods, linear factor models, and strategic asset allocation; andtechniques other than neural networks, such as nonlinear and linear programming, principal component analysis, reinforcement learning, dynamic programming, and clustering.
The authors use technical and nontechnical arguments to accommodate readers with different levels of mathematical preparation. Readers will find the book easy to read yet rigorous and a large number of exercises.