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

IF 6.9 1区经济学 Q1 BUSINESS, FINANCE Financial Innovation Pub Date : 2024-08-02 DOI:10.1186/s40854-024-00642-2

Arturo Leccadito, Alessandro Staino, Pietro Toscano

引用次数: 0

Abstract

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.

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

估算金融收益协方差矩阵的新型稳健方法在风险管理中的应用

本研究介绍了动态格伯模型（DGC），并评估了该模型在预测风险价值（VaR）和预期亏空（ES）方面与其他参数、非参数和半参数收益协方差矩阵估计方法相比的性能。根据 ES 回溯测试，DGC 方法总体上能准确预测 ES。此外，我们还使用模型置信集程序来确定优越的模型集（SSM）。对于我们考虑的所有投资组合和 VaR/ES 置信度水平，我们发现 DGC 属于 SSM。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文去求助

来源期刊

Financial Innovation Economics, Econometrics and Finance-Finance

CiteScore

11.40

自引率

11.90%

发文量

审稿时长

5 weeks

期刊介绍： Financial Innovation (FIN), a Springer OA journal sponsored by Southwestern University of Finance and Economics, serves as a global academic platform for sharing research findings in all aspects of financial innovation during the electronic business era. It facilitates interactions among researchers, policymakers, and practitioners, focusing on new financial instruments, technologies, markets, and institutions. Emphasizing emerging financial products enabled by disruptive technologies, FIN publishes high-quality academic and practical papers. The journal is peer-reviewed, indexed in SSCI, Scopus, Google Scholar, CNKI, CQVIP, and more.