Multivariate dependence and portfolio optimization algorithms under illiquid market scenarios

Mazin A.M. Al Janabi, Jose Arreola Hernandez, Theo Berger, Duc Khuong Nguyen

Research output: Contribution to journalArticlepeer-review

42 Citations (Scopus)

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 considering 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.

Original languageEnglish
Pages (from-to)1121-1131
Number of pages11
JournalEuropean Journal of Operational Research
Volume259
Issue number3
DOIs
Publication statusPublished - Jun 16 2017
Externally publishedYes

Keywords

  • Dependence structure
  • Dynamic copulas
  • Finance
  • LVaR
  • Portfolio optimization algorithm

ASJC Scopus subject areas

  • Computer Science(all)
  • Modelling and Simulation
  • Management Science and Operations Research
  • Information Systems and Management

Fingerprint

Dive into the research topics of 'Multivariate dependence and portfolio optimization algorithms under illiquid market scenarios'. Together they form a unique fingerprint.

Cite this