{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,13]],"date-time":"2025-11-13T07:22:58Z","timestamp":1763018578454,"version":"build-2065373602"},"reference-count":41,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2023,2,6]],"date-time":"2023-02-06T00:00:00Z","timestamp":1675641600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001409","name":"Department of Science and Technology, India","doi-asserted-by":"publisher","award":["SR\/WOS-A\/PM-37\/2019"],"award-info":[{"award-number":["SR\/WOS-A\/PM-37\/2019"]}],"id":[{"id":"10.13039\/501100001409","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computation"],"abstract":"<jats:p>Range value at risk (RVaR) is a quantile-based risk measure with two parameters. As special examples, the value at risk (VaR) and the expected shortfall (ES), two well-known but competing regulatory risk measures, are both members of the RVaR family. The estimation of RVaR is a critical issue in the financial sector. Several nonparametric RVaR estimators are described here. We examine these estimators\u2019 accuracy in various scenarios using Monte Carlo simulations. Our simulations shed light on how changing p and q with respect to n affects the effectiveness of RVaR estimators that are nonparametric, with n representing the total number of samples. Finally, we perform a backtesting exercise of RVaR based on Acerbi and Szekely\u2019s test.<\/jats:p>","DOI":"10.3390\/computation11020028","type":"journal-article","created":{"date-parts":[[2023,2,7]],"date-time":"2023-02-07T01:56:48Z","timestamp":1675735008000},"page":"28","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Nonparametric Estimation of Range Value at Risk"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8534-5184","authenticated-orcid":false,"given":"Suparna","family":"Biswas","sequence":"first","affiliation":[{"name":"Indian Statistical Institute, Bangalore 560059, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2112-7532","authenticated-orcid":false,"given":"Rituparna","family":"Sen","sequence":"additional","affiliation":[{"name":"Indian Statistical Institute, Bangalore 560059, India"}]}],"member":"1968","published-online":{"date-parts":[[2023,2,6]]},"reference":[{"key":"ref_1","unstructured":"Philippe, J. 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