ORCID

Abstract

Portfolio optimisation aims to efficiently find optimal proportions of portfolio assets, given certain constraints, and has been well-studied. While portfolio optimisation ascertains asset combinations most suited to investor requirements, numerous real-world problems impact its simplicity, e.g., investor preferences. Trading restrictions are also commonly faced, and must be met. However, in adding constraints to Markowitz's basic mean-variance model, problem complexity increases, causing difficulties for exact optimisation approaches to find large problem solutions inside reasonable timeframes. This paper addresses portfolio optimisation complexities by applying the Worst Case GARCH-Copula Conditional Value at Risk (CVaR) approach. In particular, the GARCH-copula methodology is used to model the portfolio dependence structure, and the Worst Case CVaR (WCVaR) is considered as an alternative risk measure, able to provide a more accurate evaluation of financial risk compared to traditional approaches. Copulas model the marginal of each asset separately (which may be any distribution) and also the interdependencies between assets. This allows an accurate risk to investment assessment to be applied, in order to compare it with the traditional methods. In this paper we present two case studies to evaluate the performance of the WCVaR and compare it against the VaR measure. The first case study focuses on the time series of the closing prices of six major market indexes, while the second case study considers a large dataset of the share prices of the Gulf Cooperation Council's (GCC) oil-based companies. Results show that the values of WCVaR are always higher than those of VaR, demonstrating that the WCVaR approach provides a more accurate assessment of financial risk.

DOI

10.3390/jrfm15100482

Publication Date

2022-10-17

Publication Title

Journal of Risk and Financial Management

Volume

15

Issue

10

ISSN

1911-8066

Embargo Period

2022-10-25

Organisational Unit

School of Engineering, Computing and Mathematics

Keywords

Copula, GARCH, Portfolio optimisation, VaR, WCVaR

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