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Mean univariate- GARCH VaR portfolio optimization: actual portfolio approach

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Version 2 2023-06-12, 06:37
Version 1 2023-06-09, 00:18
journal contribution
posted on 2023-06-12, 06:37 authored by Vladimir Rankovic, Mikica Drenovak, Branko Urosevic, Ranko JelicRanko Jelic
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.

History

Publication status

  • Published

File Version

  • Published version

Journal

Computers & Operations Research

ISSN

0305-0548

Publisher

Elsevier

Volume

72

Page range

83-92

Department affiliated with

  • Business and Management Publications

Full text available

  • Yes

Peer reviewed?

  • Yes

Legacy Posted Date

2016-02-16

First Open Access (FOA) Date

2016-06-21

First Compliant Deposit (FCD) Date

2016-02-16

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