Multivariate dependence and portfolio optimization algorithms under illiquid market scenarios

Al Janabi, Mazin A.M. and Arreola Hernandez, Jose and Berger, Theo and Nguyen, Duc Khuong (2016): Multivariate dependence and portfolio optimization algorithms under illiquid market scenarios. Published in: European Journal of Operational Research , Vol. 259, No. 3 (2017): pp. 1121-1131.

Abstract

We propose a model for optimizing structured portfolios with liquidity-adjusted Value-at-Risk (LVaR) constraints, whereby linear correlations between assets are replaced by the multivariate nonlinear dependence structure based on Dynamic Conditional Correlation t-copula modeling. Our portfolio optimization algorithm minimizes the LVaR function under adverse market circumstances and multiple operational and financial constraints. When we consider a diversified portfolio of international stock and commodity market indices under multiple realistic portfolio optimization scenarios, the obtained results consistently show the superiority of our approach relative to other competing portfolio strategies including the minimum-variance, risk-parity and equally weighted portfolio allocations.

• Item Type: MPRA Paper
• Language: English
• Keywords: Dynamic copulas, LVaR, dependence structure, portfolio optimization algorithm
• Subjects: C - Mathematical and Quantitative Methods > C5 - Econometric Modeling; G - Financial Economics > G1 - General Financial Markets > G11 - Portfolio Choice ; Investment Decisions; G - Financial Economics > G1 - General Financial Markets > G17 - Financial Forecasting and Simulation

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