Persistent Link:
http://hdl.handle.net/10150/280043
Title:
A collection of essays in empirical finance
Author:
Roskelley, Kenneth
Issue Date:
2002
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 consists of three papers. The first assesses the ability of bivariate distribution models to explain the contemporaneous and autocorrelation between volume and volatility. GMM is used to fit first and second moments of the model to the data and analyze the model's fit. The second paper looks at the uncertainty surrounding cost recovery in regulated utilities. Stock market data is used to ascertain the market's perception about the deregulation of electricity in the United States. The third and final paper looks at the economic evidence for a stochastic opportunity set from an investor's point of view. A Bayesian investor must allocate her wealth between a risky and a risk free asset after observing market data when the model for asset returns is unknown and returns are potentially predictable.
Type:
text; Dissertation-Reproduction (electronic)
Keywords:
Economics, Finance.; Energy.
Degree Name:
Ph.D.
Degree Level:
doctoral
Degree Program:
Graduate College; Business Administration
Degree Grantor:
University of Arizona
Advisor:
Lamoureux, Chris

Full metadata record

DC FieldValue Language
dc.language.isoen_USen_US
dc.titleA collection of essays in empirical financeen_US
dc.creatorRoskelley, Kennethen_US
dc.contributor.authorRoskelley, Kennethen_US
dc.date.issued2002en_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 consists of three papers. The first assesses the ability of bivariate distribution models to explain the contemporaneous and autocorrelation between volume and volatility. GMM is used to fit first and second moments of the model to the data and analyze the model's fit. The second paper looks at the uncertainty surrounding cost recovery in regulated utilities. Stock market data is used to ascertain the market's perception about the deregulation of electricity in the United States. The third and final paper looks at the economic evidence for a stochastic opportunity set from an investor's point of view. A Bayesian investor must allocate her wealth between a risky and a risk free asset after observing market data when the model for asset returns is unknown and returns are potentially predictable.en_US
dc.typetexten_US
dc.typeDissertation-Reproduction (electronic)en_US
dc.subjectEconomics, Finance.en_US
dc.subjectEnergy.en_US
thesis.degree.namePh.D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.disciplineBusiness Administrationen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorLamoureux, Chrisen_US
dc.identifier.proquest3053911en_US
dc.identifier.bibrecord.b42819684en_US
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