• Media type: E-Book; Report
  • Title: Mean Univariate-GARCH VaR Portfolio Optimization: Actual Portfolio Approach
  • Contributor: Rankovic, Vladimir [Author]; Drenovak, Mikica [Author]; Uroševic, Branko [Author]; Jelic, Ranko [Author]
  • imprint: Munich: Center for Economic Studies and ifo Institute (CESifo), 2016
  • Language: English
  • Keywords: NSGA-II ; value at risk ; actual portfolios ; GARCH ; C61 ; portfolio optimization
  • Origination:
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  • Description: 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.
  • Access State: Open Access