Liquidity Dynamics and Risk Modeling: Navigating Trading and Investment Portfolios Frontiers with Machine Learning Algorithms - Tapa dura

Acerca del autor

Mazin A. M. Al Janabi has more than three decades of multifaceted experience across science, technology, finance, and academia. Holding a PhD in Nuclear Engineering from the University of London, UK, Prof. Al Janabi's journey has been marked by roles within top-tier international financial institutions, including ING-Barings and BBVA, where he held senior management positions like Director of Global Market Risk Management, Head of Trading Risk Management, Head of Derivative Products, and Head of Fixed Income Research. He also served as a Full Research Professor at institutions such as EGADE Business School, Tecnologico de Monterrey in Mexico, United Arab Emirates University (UAEU) in Abu Dhabi, and Al Akhawayn University in Ifrane (AUI), Morocco. A research fellow at the Economic Research Forum (ERF), Prof. Al Janabi's scholarly pursuits delve into the dynamics of emerging and developed economies.

De la contraportada

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, in one place, 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., and Furthermore, it explores research directions of liquidity risk management using modified Lliquidity-Aadjusted Vvalue-at-Rrisk (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.

Mazin A. M. Al Janabi has more than three decades of multifaceted experience across science, technology, finance, and academia. Holding a PhD in Nuclear Engineering from the University of London, UK, Prof. Al Janabi's journey has been marked by roles within top-tier international financial institutions, including ING-Barings and BBVA, where he held senior management positions like Director of Global Market Risk Management, Head of Trading Risk Management, Head of Derivative Products, and Head of Fixed Income Research. He also served as a Full Research Professor at institutions such as EGADE Business School, Tecnologico de Monterrey in Mexico, United Arab Emirates University (UAEU) in Abu Dhabi, and Al Akhawayn University in Ifrane (AUI), Morocco. A research fellow at the Economic Research Forum (ERF), Prof. Al Janabi's scholarly pursuits delve into the dynamics of emerging and developed economies.