Regression-Based Expected Shortfall Backtesting

Lade...
Vorschaubild
Dateien
Bayer_2-s7q087by7m369.pdf
Bayer_2-s7q087by7m369.pdfGröße: 1.38 MBDownloads: 83
Datum
2022
Herausgeber:innen
Kontakt
ISSN der Zeitschrift
Electronic ISSN
ISBN
Bibliografische Daten
Verlag
Schriftenreihe
Auflagebezeichnung
Internationale Patentnummer
Angaben zur Forschungsförderung
Projekt
Open Access-Veröffentlichung
Open Access Hybrid
Core Facility der Universität Konstanz
Gesperrt bis
Titel in einer weiteren Sprache
Forschungsvorhaben
Organisationseinheiten
Zeitschriftenheft
Publikationstyp
Zeitschriftenartikel
Publikationsstatus
Published
Erschienen in
Journal of Financial Econometrics. Oxford University Press. 2022, 20(3), pp. 437-471. ISSN 1479-8409. eISSN 1479-8417. Available under: doi: 10.1093/jjfinec/nbaa013
Zusammenfassung

This article introduces novel backtests for the risk measure Expected Shortfall (ES) following the testing idea of Mincer and Zarnowitz (1969). Estimating a regression model for the ES stand-alone is infeasible and thus, our tests are based on a joint regression model for the Value at Risk (VaR) and the ES, which allows for different test specifications. These ES backtests are the first which solely backtest the ES in the sense that they only require ES forecasts as input variables. As the tests are potentially subject to model misspecification, we provide asymptotic theory under misspecification for the underlying joint regression. We find that employing a misspecification robust covariance estimator substantially improves the tests’ performance. We compare our backtests to existing joint VaR and ES backtests and find that our tests outperform the existing alternatives throughout all considered simulations. In an empirical illustration, we apply our backtests to ES forecasts for 200 stocks of the S&P 500 index.

Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
330 Wirtschaft
Schlagwörter
Konferenz
Rezension
undefined / . - undefined, undefined
Zitieren
ISO 690BAYER, Sebastian, Timo DIMITRIADIS, 2022. Regression-Based Expected Shortfall Backtesting. In: Journal of Financial Econometrics. Oxford University Press. 2022, 20(3), pp. 437-471. ISSN 1479-8409. eISSN 1479-8417. Available under: doi: 10.1093/jjfinec/nbaa013
BibTex
@article{Bayer2022Regre-57838,
  year={2022},
  doi={10.1093/jjfinec/nbaa013},
  title={Regression-Based Expected Shortfall Backtesting},
  number={3},
  volume={20},
  issn={1479-8409},
  journal={Journal of Financial Econometrics},
  pages={437--471},
  author={Bayer, Sebastian and Dimitriadis, Timo}
}
RDF
<rdf:RDF
    xmlns:dcterms="http://purl.org/dc/terms/"
    xmlns:dc="http://purl.org/dc/elements/1.1/"
    xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
    xmlns:bibo="http://purl.org/ontology/bibo/"
    xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#"
    xmlns:foaf="http://xmlns.com/foaf/0.1/"
    xmlns:void="http://rdfs.org/ns/void#"
    xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > 
  <rdf:Description rdf:about="https://kops.uni-konstanz.de/server/rdf/resource/123456789/57838">
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
    <dcterms:title>Regression-Based Expected Shortfall Backtesting</dcterms:title>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2022-06-23T13:57:04Z</dc:date>
    <dcterms:issued>2022</dcterms:issued>
    <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/57838/1/Bayer_2-s7q087by7m369.pdf"/>
    <dcterms:abstract xml:lang="eng">This article introduces novel backtests for the risk measure Expected Shortfall (ES) following the testing idea of Mincer and Zarnowitz (1969). Estimating a regression model for the ES stand-alone is infeasible and thus, our tests are based on a joint regression model for the Value at Risk (VaR) and the ES, which allows for different test specifications. These ES backtests are the first which solely backtest the ES in the sense that they only require ES forecasts as input variables. As the tests are potentially subject to model misspecification, we provide asymptotic theory under misspecification for the underlying joint regression. We find that employing a misspecification robust covariance estimator substantially improves the tests’ performance. We compare our backtests to existing joint VaR and ES backtests and find that our tests outperform the existing alternatives throughout all considered simulations. In an empirical illustration, we apply our backtests to ES forecasts for 200 stocks of the S&amp;P 500 index.</dcterms:abstract>
    <dc:contributor>Dimitriadis, Timo</dc:contributor>
    <dc:creator>Bayer, Sebastian</dc:creator>
    <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/57838"/>
    <dcterms:rights rdf:resource="https://rightsstatements.org/page/InC/1.0/"/>
    <dc:language>eng</dc:language>
    <dc:creator>Dimitriadis, Timo</dc:creator>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/46"/>
    <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/57838/1/Bayer_2-s7q087by7m369.pdf"/>
    <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2022-06-23T13:57:04Z</dcterms:available>
    <dc:contributor>Bayer, Sebastian</dc:contributor>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/46"/>
    <dc:rights>terms-of-use</dc:rights>
  </rdf:Description>
</rdf:RDF>
Interner Vermerk
xmlui.Submission.submit.DescribeStep.inputForms.label.kops_note_fromSubmitter
Kontakt
URL der Originalveröffentl.
PrĂĽfdatum der URL
PrĂĽfungsdatum der Dissertation
Finanzierungsart
Kommentar zur Publikation
Allianzlizenz
Corresponding Authors der Uni Konstanz vorhanden
Internationale Co-Autor:innen
Universitätsbibliographie
Nein
Begutachtet
Ja
Diese Publikation teilen