Nonparametric Estimation of Range Value at Risk

被引：0

作者：

Biswas, Suparna ^{[1
]}

Sen, Rituparna ^{[1
]}

机构：

[1] Indian Stat Inst, Bangalore 560059, Karnataka, India

来源：

MATHEMATICAL AND STATISTICAL METHODS FOR ACTUARIAL SCIENCES AND FINANCE, MAF 2022 | 2022年

关键词：

Range Value at Risk; Nonparametric estimation; Monte Carlo simulations; ROBUSTNESS;

D O I：

10.1007/978-3-030-99638-3_18

中图分类号：

F8 [财政、金融];

学科分类号：

0202 ;

摘要：

Range Value at Risk (RVaR) is a two-parameter class of quantile-based risk measures. It is the conditional expectation of the loss when it lies between two values of VaR, for levels p and q, where 0 < p < q < 1. We describe some of the nonparametric estimators of RVaR. Using Monte Carlo simulations, we compare the accuracy of these estimators under certain conditions. Our simulations provide insight into the effect of varying p and q with n on the performance of nonparametric RVaR estimators, where n is the sample size.

引用

页码：109 / 114

页数：6

共 13 条

[1] BANDWIDTH SELECTION FOR KERNEL DISTRIBUTION FUNCTION ESTIMATION [J].

ALTMAN, N ;

LEGER, C .

JOURNAL OF STATISTICAL PLANNING AND INFERENCE, 1995, 46 (02) :195-214

[2]

Biswas S., 2019, arXiv

[3] Estimating conditional tail expectation with actuarial applications in view [J].

Brazauskas, Vytaras ;

Jones, Bruce L. ;

Puri, Madan L. ;

Zitikis, Ricardas .

JOURNAL OF STATISTICAL PLANNING AND INFERENCE, 2008, 138 (11) :3590-3604

[4] Robustness and sensitivity analysis of risk measurement procedures [J].

Cont, Rama ;

Deguest, Romain ;

Scandolo, Giacomo .

QUANTITATIVE FINANCE, 2010, 10 (06) :593-606

[5] Extreme quantile estimation for dependent data, with applications to finance [J].

Drees, H .

BERNOULLI, 2003, 9 (04) :617-657

[6] Quantile-Based Risk Sharing [J].

Embrechts, Paul ;

Liu, Haiyan ;

Wang, Ruodu .

OPERATIONS RESEARCH, 2018, 66 (04) :936-949

[7] Aggregation-robustness and model uncertainty of regulatory risk measures [J].

Embrechts, Paul ;

Wang, Bin ;

Wang, Ruodu .

FINANCE AND STOCHASTICS, 2015, 19 (04) :763-790

[8] What is the best risk measure in practice? A comparison of standard measures [J].

Emmer, Susanne ;

Kratz, Marie ;

Tasche, Dirk .

JOURNAL OF RISK, 2015, 18 (02) :31-60

[9] On the elicitability of range value at risk [J].

Fissler, Tobias ;

Ziegel, Johanna F. .

STATISTICS & RISK MODELING, 2021, 38 (1-2) :25-46

[10]

Hill J.B., 2013, Expected shortfall estimation and gaussian inference for infinite variance time series. Unpublished monograph

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