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Mean univariate- GARCH VaR portfolio optimization: actual portfolio approach
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 JelicIn 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.
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Publication status
- Published
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- Published version
Journal
Computers & Operations ResearchISSN
0305-0548Publisher
ElsevierExternal DOI
Volume
72Page range
83-92Department affiliated with
- Business and Management Publications
Full text available
- Yes
Peer reviewed?
- Yes
Legacy Posted Date
2016-02-16First Open Access (FOA) Date
2016-06-21First Compliant Deposit (FCD) Date
2016-02-16Usage metrics
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