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Essays on Bayesian analysis of financial economics

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TypeOfResource
Text
TitleInfo (ID = T-1)
Title
Essays on Bayesian analysis of financial economics
Identifier
ETD_1607
Identifier (type = hdl)
http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000051370
Language
LanguageTerm (authority = ISO639-2); (type = code)
eng
Genre (authority = marcgt)
theses
Subject (ID = SBJ-1); (authority = RUETD)
Topic
Economics
Subject (ID = SBJ-1); (authority = ETD-LCSH)
Topic
Bayesian statistical decision theory
Subject (ID = SBJ-1); (authority = ETD-LCSH)
Topic
Finance--Econometric models
Subject (ID = SBJ-1); (authority = ETD-LCSH)
Topic
Markov processes
Abstract
This dissertation consists of three essays with each essay forming a chapter. The regression models in these three chapters are different but share the same feature: the error terms of the models all follow ARMA-GARCH error processes generated either from normal or exponential power distributions.
In the first chapter I present a spot asset pricing model that is known as the CKLS model. Two CKLS models are compared. In one model the ARMA-GARCH error process is generated by the exponential power distribution while in the other model the error process is generated by the normal distribution. Using monthly U.S. federal funds rate I estimate the parameters of the CKLS models. From the predictive densities I obtain the distributions of the mean squared errors of forecast (MSEF) and the predictive deviance information criterion (PDIC). In addition I use the Bayes factor and the deviance information criterion (DIC). Markov Chain Monte Carlo (MCMC) algorithms, which are stochastic numerical integration methods, are used. I find that in general the CKLS model with the error term generated by the exponential power distribution is chosen over the model with the normal error term.
In the second chapter I first compare two MCMC algorithms: random walk draw and non-random walk draw for a Markov switching regression model. Two Markov switching models are compared: one with the variance of the normal distribution generated by the state space variable and the other with the constant variance. The realized volatilities of MMM Company are used to estimate and compare the models. The mean squared errors (MSE) and mean squared errors of forecast (MSEF) are used as the model selection criteria. I find that the model with the constant variance is chosen over the model with the state space variance by the MSE but the latter is chosen over the former by the MSEF.
In the third chapter I estimate a bivariate copula model. Each of the two regressions is generated by the exponential power distribution. I use monthly data on SP500 and FTSE100. Results show that the correlation parameter for SP500 and FTSE100 is .6893.
PhysicalDescription
Form (authority = gmd)
electronic resource
Extent
viii, 97 p. : ill.
InternetMediaType
application/pdf
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text/xml
Note (type = degree)
Ph.D.
Note (type = bibliography)
Includes bibliographical references (p. 86-96)
Note (type = statement of responsibility)
by Liuling Li
Name (ID = NAME-1); (type = personal)
NamePart (type = family)
Li
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Liuling
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1976
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author
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Liuling Li
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Tsurumi
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Hiroki
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chair
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Advisory Committee
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Hiroki Tsurumi
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NamePart (type = family)
Swanson
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Norman
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internal member
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Advisory Committee
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Norman Swanson
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NamePart (type = family)
Mizrach
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Bruce
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internal member
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Advisory Committee
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Bruce Mizrach
Name (ID = NAME-5); (type = personal)
NamePart (type = family)
Goldman
NamePart (type = given)
Elena
Role
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outside member
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Advisory Committee
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Elena Goldman
Name (ID = NAME-1); (type = corporate)
NamePart
Rutgers University
Role
RoleTerm (authority = RULIB); (type = )
degree grantor
Name (ID = NAME-2); (type = corporate)
NamePart
Graduate School - New Brunswick
Role
RoleTerm (authority = RULIB); (type = )
school
OriginInfo
DateCreated (point = ); (qualifier = exact)
2009
DateOther (qualifier = exact); (type = degree)
2009-05
Place
PlaceTerm (type = code)
xx
RelatedItem (type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier (type = RULIB)
ETD
RelatedItem (type = host)
TitleInfo
Title
Graduate School - New Brunswick Electronic Theses and Dissertations
Identifier (type = local)
rucore19991600001
Location
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NjNbRU
Identifier (type = doi)
doi:10.7282/T3VX0GQC
Genre (authority = ExL-Esploro)
ETD doctoral
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The author owns the copyright to this work.
Copyright
Status
Copyright protected
Availability
Status
Open
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Type
Permission or license
Detail
Non-exclusive ETD license
AssociatedObject (AUTHORITY = rulib); (ID = 1)
Type
License
Name
Author Agreement License
Detail
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
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ETD
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application/pdf
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application/x-tar
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901120
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