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

被引：0

作者：

Leccadito, Arturo ^{[1
,2
]}

Staino, Alessandro ^{[1
]}

Toscano, Pietro ^{[3
]}

机构：

[1] Univ Calabria, Dept Econ Stat & Finance, I-87036 Arcavacata Di Rende, CS, Italy

[2] UCLouvain, LFIN LIDAM, Voie Roman Pays 34, B-1348 Louvain La Neuve, Belgium

[3] Fidel Investments, 245 Summer St, Boston, MA 02210 USA

来源：

FINANCIAL INNOVATION | 2024年 / 10卷 / 01期

关键词：

Value at risk; Expected shortfall; Gerber statistic; Model confidence set; Superior set of models; C51; C52; C58; G15; DYNAMIC CONDITIONAL CORRELATION; VALUE-AT-RISK; EXPECTED SHORTFALL; TIME-SERIES; MODELS; VOLATILITY;

D O I：

10.1186/s40854-024-00642-2

中图分类号：

F8 [财政、金融];

学科分类号：

0202 ;

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.

引用

页数：28

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