Publikation: Can We Give the Maximum Sharpe Ratio Portfolio a Chance?
Lade...
Dateien
Zu diesem Dokument gibt es keine Dateien.
Datum
2024
Autor:innen
Herausgeber:innen
ISSN der Zeitschrift
Electronic ISSN
ISBN
Bibliografische Daten
Verlag
Schriftenreihe
Auflagebezeichnung
DOI (zitierfähiger Link)
Internationale Patentnummer
Angaben zur Forschungsförderung
Projekt
Open Access-Veröffentlichung
Sammlungen
Core Facility der Universität Konstanz
Titel in einer weiteren Sprache
Publikationstyp
Beitrag zu einem Sammelband
Publikationsstatus
Published
Erschienen in
KNOTH, Sven, Hrsg., Yarema OKHRIN, Hrsg., Philipp OTTO, Hrsg.. Advanced Statistical Methods in Process Monitoring, Finance, and Environmental Science : Essays in Honour of Wolfgang Schmid. 1. Cham: Springer, 2024, S. 337-366. ISBN 978-3-031-69110-2. Verfügbar unter: doi: 10.1007/978-3-031-69111-9_16
Zusammenfassung
This chapter studies the applicability of the maximum Sharpe ratio (MaxSR) portfolio strategy in real-world settings. As shown by Okhrin and Schmidt the plug-in estimated weights show abysmal distributional properties such that it renders an application impossible for financial practitioners. In this chapter we propose a double regularization approach for the MaxSR portfolio strategy based on the bagged pretested portfolio selection (BPPS) algorithm. We show that for certain settings the doubly shrunken portfolio weights strongly mitigate the adverse properties of the plug-in estimated weights and can beat the popular 1/N benchmark strategy.
Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
330 Wirtschaft
Schlagwörter
Konferenz
Rezension
undefined / . - undefined, undefined
Zitieren
ISO 690
POHLMEIER, Winfried, Ekaterina KAZAK, 2024. Can We Give the Maximum Sharpe Ratio Portfolio a Chance?. In: KNOTH, Sven, Hrsg., Yarema OKHRIN, Hrsg., Philipp OTTO, Hrsg.. Advanced Statistical Methods in Process Monitoring, Finance, and Environmental Science : Essays in Honour of Wolfgang Schmid. 1. Cham: Springer, 2024, S. 337-366. ISBN 978-3-031-69110-2. Verfügbar unter: doi: 10.1007/978-3-031-69111-9_16BibTex
@incollection{Pohlmeier2024Maxim-71133, year={2024}, doi={10.1007/978-3-031-69111-9_16}, title={Can We Give the Maximum Sharpe Ratio Portfolio a Chance?}, edition={1}, isbn={978-3-031-69110-2}, publisher={Springer}, address={Cham}, booktitle={Advanced Statistical Methods in Process Monitoring, Finance, and Environmental Science : Essays in Honour of Wolfgang Schmid}, pages={337--366}, editor={Knoth, Sven and Okhrin, Yarema and Otto, Philipp}, author={Pohlmeier, Winfried and Kazak, Ekaterina} }
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/123456789/71133"> <dcterms:issued>2024</dcterms:issued> <dcterms:title>Can We Give the Maximum Sharpe Ratio Portfolio a Chance?</dcterms:title> <dcterms:abstract>This chapter studies the applicability of the maximum Sharpe ratio (MaxSR) portfolio strategy in real-world settings. As shown by Okhrin and Schmidt the plug-in estimated weights show abysmal distributional properties such that it renders an application impossible for financial practitioners. In this chapter we propose a double regularization approach for the MaxSR portfolio strategy based on the bagged pretested portfolio selection (BPPS) algorithm. We show that for certain settings the doubly shrunken portfolio weights strongly mitigate the adverse properties of the plug-in estimated weights and can beat the popular 1/N benchmark strategy.</dcterms:abstract> <foaf:homepage rdf:resource="http://localhost:8080/"/> <dc:language>eng</dc:language> <dc:contributor>Kazak, Ekaterina</dc:contributor> <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/46"/> <dc:creator>Kazak, Ekaterina</dc:creator> <dc:creator>Pohlmeier, Winfried</dc:creator> <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2024-11-07T12:09:18Z</dcterms:available> <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/71133"/> <dc:contributor>Pohlmeier, Winfried</dc:contributor> <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/46"/> <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2024-11-07T12:09:18Z</dc:date> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> </rdf:Description> </rdf:RDF>
Interner Vermerk
xmlui.Submission.submit.DescribeStep.inputForms.label.kops_note_fromSubmitter
Prüfungsdatum der Dissertation
Finanzierungsart
Kommentar zur Publikation
Allianzlizenz
Corresponding Authors der Uni Konstanz vorhanden
Internationale Co-Autor:innen
Universitätsbibliographie
Ja