This chapter implements a reasonable approach for the measurement and control of market price risk-exposure for financial trading portfolios that contain some illiquid equity assets. The simulation and testing approach are based on the renowned concept of liquidity-adjusted value at risk (LVaR) along with the application of an optimization risk-algorithm utilizing the matrix-algebra technique. Our broad market/liquidity risk model and algorithm can simultaneously handle and analyse potential LVaR exposures under normal and adverse market circumstances. Further, it can empirically test for the effects of illiquidity of traded equity securities under crisis-driven market circumstances with the purpose of demonstrating the appropriate use of LVaR and stress-testing methods, real-world examples, in the form of applied risk techniques case studies, along with quantitative analysis of trading risk management are presented for the Gulf Cooperation Council (GCC) stock markets. To this end, several practical case studies are achieved with the objective of simulating a realistic framework of liquidity trading risk measurement in addition to the application of a risk optimization process for the calculation of maximum authorized LVaR threshold limits. In all case studies, the implemented conditional volatilities are assessed using GARCH (1, 1)-M model and the optimization algorithm is based on the definition of parametric LVaR as the maximum possible loss over a specified time horizon within a given confidence level. The implemented methodology and risk assessment algorithms can aid in advancing risk management practices in emerging and Islamic markets, particularly in the wake of the recent sub-prime credit crunch and the consequent financial turmoil.