A novel robust method for estimating the covariance matrix of financial returns with applications to risk management  

作　　者：Arturo Leccadito Alessandro Staino Pietro Toscano 

机构地区：[1]Department of Economics,Statistics and Finance,University of Calabria,87036,Ponte Bucci,Rende,CS,Italy [2]LFIN/LIDAM,UCLouvain,Voie du Roman Pays 34,1348,Louvain la neuve,Belgium [3]Fidelity Investments,245 Summer Street,Boston,MA,02210,USA

出　　处：《Financial Innovation》2024年第1期652-679,共28页金融创新(英文)

摘　　要：This study introduces the dynamic Gerber model(DGC)and evaluates its performance in the prediction of Value at Risk(VaR)and Expected Shortfall(ES)compared to alternative parametric,non-parametric and semi-parametric methods for estimating the covariance matrix of returns.Based on ES backtests,the DGC method produces,overall,accurate ES forecasts.Furthermore,we use the Model Confidence Set procedure to identify the superior set of models(SSM).For all the portfolios and VaR/ES confidence levels we consider,the DGC is found to belong to the SSM.

关 键 词：Value at risk Expected shortfall Gerber statistic Model confidence set Superior set of models 

分 类 号：F22[经济管理—国民经济]