Scenario optimization technique for the assessment of downside-risk and investable portfolios in post-financial crisis

Abstract

The aim of this paper is to develop an optimization technique for the assessment of downside-risk limits and investable financial portfolios under crisis-driven outlooks subject to applying meaningful financial and operational constraints. The simulation and testing methods are based on the renowned concept of liquidity-adjusted value-at-risk (LVaR) along with the development of an optimization risk-algorithm utilizing matrix–algebra technique. With the purpose of demonstrating the effectiveness of LVaR and stress-testing techniques, real-world quantitative analysis of structured equity portfolios are depicted for the Gulf Cooperation Council (GCC) financial markets. To this end, several structural simulations studies are accomplished with the goal of establishing realistic financial modeling algorithm for the calculation of downside-risk parameters and to empirically assess portfolio managers' optimal and investable portfolios. The developed methodology and risk valuation algorithms can aid in advancing risk assessment and portfolio management practices in emerging markets, particularly in the wake of the most recent credit crunch and the subsequent financial turmoil.