Persistent Link:
http://hdl.handle.net/10150/184608
Title:
Nonparametric statistical methods in financial market research.
Author:
Corrado, Charles J.
Issue Date:
1988
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
This dissertation presents an exploration of the use of nonparametric statistical methods based on ranks for use in financial market research. Applications to event study methodology and the estimation of security systematic risk are analyzed using a simulation methodology with actual daily security return data. The results indicate that procedures based on ranks are more efficient than normal theory procedures currently in common use.
Type:
text; Dissertation-Reproduction (electronic)
Keywords:
Capital market -- Statistical methods.; Nonparametric statistics.
Degree Name:
Ph.D.
Degree Level:
doctoral
Degree Program:
Business Administration; Graduate College
Degree Grantor:
University of Arizona
Advisor:
Bierwag, Gerald O.

Full metadata record

DC FieldValue Language
dc.language.isoenen_US
dc.titleNonparametric statistical methods in financial market research.en_US
dc.creatorCorrado, Charles J.en_US
dc.contributor.authorCorrado, Charles J.en_US
dc.date.issued1988en_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.description.abstractThis dissertation presents an exploration of the use of nonparametric statistical methods based on ranks for use in financial market research. Applications to event study methodology and the estimation of security systematic risk are analyzed using a simulation methodology with actual daily security return data. The results indicate that procedures based on ranks are more efficient than normal theory procedures currently in common use.en_US
dc.typetexten_US
dc.typeDissertation-Reproduction (electronic)en_US
dc.subjectCapital market -- Statistical methods.en_US
dc.subjectNonparametric statistics.en_US
thesis.degree.namePh.D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineBusiness Administrationen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorBierwag, Gerald O.en_US
dc.contributor.committeememberDyl, Edward A.en_US
dc.contributor.committeememberSchatzberg, John A.en_US
dc.contributor.committeememberHigle, Julia J.en_US
dc.identifier.proquest8907953en_US
dc.identifier.oclc701890428en_US
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