Liquidity Dynamics and Risk Modeling
Navigating Trading and Investment Portfolios Frontiers with Machine Learning Algorithms
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Liquidity Dynamics and Risk Modeling
Navigating Trading and Investment Portfolios Frontiers with Machine Learning Algorithms
About this book
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.
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Table of contents
- Cover
- Front Matter
- 1. Beyond the Surface: In-Depth Perspectives on Liquidity and Risk Frontiers
- 2. Unlocking the Microstructure of Liquidity Risk: Understanding Interactions with Other Financial Risks and Best Practices in Oversight and Governance
- 3. Crises to Opportunities: Derivatives Trading, Liquidity Management, and Risk Mitigation Strategies in Emerging Markets
- 4. Insights into Liquidity Dynamics: Optimizing Asset Allocation and Portfolio Risk Management with Machine Learning Algorithms
- 5. Navigating Liquidity Waves: Practical Applications of Liquidity Risk Management and Investable Portfolio Optimization in Financial Markets
- 6. Leveraging Liquidity Models in Commodity Markets: Customizing Risk-Appetite Trading Limits for Robust Investment Portfolios
- 7. Liquidity Spectrum: Unraveling Theoretical Frameworks and Leveraging Modeling Algorithms for In-Depth Insights into Overall and Relative Liquidity Risk Dynamics
- 8. Beyond Boundaries: Navigating Liquidity Frontiers with Advanced L-VaR Optimization Algorithms and Strategic Integration of Bid-Ask Modeling Spreads
- Back Matter