A0699
Title: Expected shortfall estimation with stationary vine copulas
Authors: Juan Mora - Universidad de Alicante (Spain) [presenting]
Roberto Fuentes-Martinez - Universidad de Alicante - IMT Alti Studi Lucca (Italy)
Abstract: The performance of stationary vine copula models (S-vines) is assessed for estimating the expected shortfall (ES) of returns from a portfolio of financial assets. To this end, an estimation procedure is proposed based on the Monte Carlo method using S-vines, for estimating the k-period-ahead ES of a financial portfolio at a given time period t, employing a rolling window approach. Notably, by means of a simulation study, evidence is found that, under some dependence scenarios, the S-vine ES estimates outperform those of models commonly used in financial time series modeling, while exhibiting relatively similar performance under other data-generating processes. Finally, through an empirical application, it is shown that using the S-vine ES estimates in the context of portfolio optimization can lead to better strategies than those derived from models that consider serial dependence and cross-sectional dependence individually, particularly when working with large portfolios.
