Navigating Liquidity Waves: Practical Applications of Liquidity Risk Management and Investable Portfolio Optimization in Financial Markets

This chapter presents practical applications for forecasting efficient (optimum) and coherent (optimal) economic capital using Liquidity-Adjusted Value-at-Risk (L-VaR) modeling techniques and optimization algorithms. The asset allocation of economic capital is achieved by minimizing the objective function of L-VaR, with optimization satisfying constraints set by the portfolio manager. Illustrating how robust L-VaR algorithms can be employed by equity trading units in dynamic asset allocation frameworks, it addresses risk exposure reporting, economic capital optimization, and risk reduction alternatives. Empirical results from emerging Gulf Cooperation Council (GCC) financial markets underscore the significance of incorporating meaningful nonlinear and dynamic constraints in L-VaR optimization procedures, particularly post-2007–2009 global financial crisis. The discussed modeling algorithms and empirical findings are valuable in theory and practice, with potential applications in financial markets. Furthermore, the optimization techniques and risk assessment algorithms contribute to advancing risk management practices globally, including in regulatory technology (RegTech) and FinTech. This chapter offers insights for professionals, regulators, and researchers in financial engineering, machine learning for policymaking, and Internet of Things (IoT) data analytics. In addition, it provides real-world implications for compliance with Basel best practices on liquidity risk and capital adequacy.