Article ID: | iaor20132681 |
Volume: | 205 |
Issue: | 1 |
Start Page Number: | 109 |
End Page Number: | 139 |
Publication Date: | May 2013 |
Journal: | Annals of Operations Research |
Authors: | Al Janabi Mazin |
Keywords: | programming: nonlinear |
This paper broadens research literature associated with the assessment of modern portfolio risk management techniques by presenting a thorough modeling of nonlinear dynamic asset allocation and management under the supposition of illiquid and adverse market settings. Specifically, the paper proposes a re‐engineered and robust approach to optimal economic capital allocation, in a Liquidity‐Adjusted Value at Risk (L‐VaR) framework, and particularly from the perspective of trading portfolios that have both long and short‐sales trading positions. This paper expands previous approaches by explicitly modeling the liquidation of trading portfolios, over the holding period, with the aid of an appropriate scaling of the multiple‐assets’ L‐VaR matrix along with GARCH‐M technique to forecast conditional volatility and expected return. Moreover, in this paper, the authors develop a dynamic nonlinear portfolio selection model and an optimization algorithm which allocates both economic capital and trading assets subject to some selected financial and operational rational constraints. The empirical results strongly confirm the importance of enforcing financially and operationally meaningful nonlinear and dynamic constraints, when they are available, on economic capital optimization procedure. The empirical results are interesting in terms of theory as well as practical applications and can aid in developing robust portfolio management algorithms that financial entities could consider in light of the aftermath of the latest financial crisis.