Portfolio Optimization Based on Forecasting Models Using Vine Copulas: An Empirical Assessment for the Financial Crisis

Abstract

We employ and examine vine copulas in modeling symmetric and asymmetric dependency structures and forecasting financial returns. We analyze the asset allocations performed during the 2008–2009 global financial crisis and the year 2020 COVID-19 crisis and test different portfolio strategies such as maximum Sharpe ratio, minimum variance, and minimum conditional Value-at-Risk. Using international financial markets, we specify the regular, drawable, and canonical vine copulas, such as the Student-t, Clayton, Frank, Joe, Gumbel, and mixed copulas, and analyze both in-sample and out-of-sample portfolio performances. Out-of-sample portfolio back-testing shows that vine copulas reduce portfolio risk better than simple copulas. Overall, we find that the Student-t drawable vine copula models perform best with regard to risk reduction, both for the entire period 2005–2012 as well as during the global financial crisis.