Title: Portfolio optimization based on forecasting models using vine copulas: An empirical assessment for the financial crisis
Authors: Andreas Stephan - Linnaeus University (Sweden) [presenting]
Maziar Sahamkhadam - Linnaeus University (Sweden)
Abstract: Vine copulas are employed for modeling the symmetric and asymmetric dependency structure and forecasting of financial returns. AR-GARCH models are used for filtering out the residuals. Asset allocation is performed during the 2007-2010 financial crisis and different portfolio strategies were tested including maximum reward-to-risk ratio (SR), minimum variance (MV) and minimum conditional Value-at-Risk (CVaR). Regular, drawable and canonical vine copulas were specified including Clayton, Frank, Joe and mixed copula. Both in-sample and out-of-sample analyses of portfolio performances were conducted. The out-of-sample portfolio back-testing showed that vine copulas reduce portfolio risk more than simple copulas. The results of the VaR back-testing and risk-adjusted performance showed improvement in forecasting of the downside risk for all portfolio strategies obtained from using mixed copula families, implying time-varying tail dependence of stock market returns. Copula families which capture symmetric tail dependence (Frank) and upper tail dependence (Joe) lead to higher terminal values of portfolios over the financial crisis.