Name: Liquidity Dynamics and Risk Modeling: Navigating Trading and Investment Portfolios Frontiers With Machine Learning Algorithms de Mazin a. M. Al Janabi(Palgrave Macmillan Ltd) (en Inglés)
Price: 187930.00 CLP
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Author: Al Janabi Mazin A. M.
ISBN: 9783031715020

portada Liquidity Dynamics and Risk Modeling: Navigating Trading and Investment Portfolios Frontiers With Machine Learning Algorithms de Mazin a. M. Al Janabi(Palgrave Macmillan Ltd) (en Inglés)

Liquidity Dynamics and Risk Modeling: Navigating Trading and Investment Portfolios Frontiers With Machine Learning Algorithms de Mazin a. M. Al Janabi(Palgrave Macmillan Ltd) (en Inglés)

Formato

Libro Físico

Editorial

Palgrave Macmillan Ltd

Autor

Al Janabi Mazin A. M.

Idioma

Inglés

Encuadernación

Tapa Dura

ISBN13

9783031715020

Liquidity Dynamics and Risk Modeling: Navigating Trading and Investment Portfolios Frontiers With Machine Learning Algorithms de Mazin a. M. Al Janabi(Palgrave Macmillan Ltd) (en Inglés)

Al Janabi Mazin A. M. (Autor) · Palgrave Macmillan Ltd · Tapa Dura

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Reseña del libro "Liquidity Dynamics and Risk Modeling: Navigating Trading and Investment Portfolios Frontiers With Machine Learning Algorithms de Mazin a. M. Al Janabi(Palgrave Macmillan Ltd) (en Inglés)"

This book presents a high-quality contribution to the applications of modern financial algorithms for liquidity risk management and its practical uses and applications to investable portfolios and mutual funds. It brings together the latest thinking on the emerging topic of contemporary liquidity risk estimations and management and includes principles, reviews, examples, and concrete financial markets applications to trading and investment portfolios. Furthermore, it explores research directions of liquidity risk management using modified Liquidity-Adjusted Value-at-Risk (L-VaR) models with the application of machine learning optimization algorithms. The book presents specific self-contained use-cases throughout, showing practical applications of the concepts discussed and providing further directions for researchers and financial markets participants. The book draws practical insights from personal experiences and applies specific examples (with the use of real-world case studies and analysis) about how the modeling techniques and machine learning optimization algorithms could address specific theoretical and practical issues of liquidity risk management and coherent asset allocation in trading and investment portfolios. It will be of interest to researchers, students, and practitioners of risk management, portfolio management, and machine learning.