Mean univariate- GARCH VaR portfolio optimization: actual portfolio approach

Rankovic, Vladimir, Drenovak, Mikica, Urosevic, Branko and Jelic, Ranko (2016) Mean univariate- GARCH VaR portfolio optimization: actual portfolio approach. Computers & Operations Research, 72. pp. 83-92. ISSN 0305-0548

[img] PDF - Accepted Version
Download (1MB)
[img] PDF - Published Version
Available under License Creative Commons Attribution-NonCommercial No Derivatives.

Download (998kB)

Abstract

In accordance with Basel Capital Accords, the Capital Requirements (CR) for market risk exposure of banks is a nonlinear function of Value-at-Risk (VaR). Importantly, the CR is calculated based on a bank’s actual portfolio, i.e. the portfolio represented by its current holdings. To tackle mean-VaR portfolio optimization within the actual portfolio framework (APF), we propose a novel mean-VaR optimization method where VaR is estimated using a univariate Generalized AutoRegressive Conditional Heteroscedasticity (GARCH) volatility model. The optimization was performed by employing a Nondominated Sorting Genetic Algorithm (NSGA-II). On a sample of 40 large US stocks, our procedure provided superior mean-VaR trade-offs compared to those obtained from applying more customary mean-multivariate GARCH and historical VaR models. The results hold true in both low and high volatility samples.

Item Type: Article
Keywords: Portfolio optimization, Actual portfolios, Value at Risk, GARCH, NSGA-II
Schools and Departments: School of Business, Management and Economics > Business and Management
Subjects: H Social Sciences
Depositing User: Tahir Beydola
Date Deposited: 16 Feb 2016 08:38
Last Modified: 20 Aug 2017 17:04
URI: http://sro.sussex.ac.uk/id/eprint/59655

View download statistics for this item

📧 Request an update