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Two-stage portfolio optimization with higher-order conditional measures of risk

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TitleInfo
Title
Two-stage portfolio optimization with higher-order conditional measures of risk
Name (type = personal)
NamePart (type = family)
Gülten
NamePart (type = given)
Sitki
NamePart (type = date)
1983-
DisplayForm
Sitki Gülten
Role
RoleTerm (authority = RULIB)
author
Name (type = personal)
NamePart (type = family)
Ruszczynski
NamePart (type = given)
Andrzej
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Andrzej Ruszczynski
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Advisory Committee
Role
RoleTerm (authority = RULIB)
chair
Name (type = personal)
NamePart (type = family)
Eckstein
NamePart (type = given)
Jonathan
DisplayForm
Jonathan Eckstein
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
internal member
Name (type = personal)
NamePart (type = family)
Jones
NamePart (type = given)
Douglas H.
DisplayForm
Douglas H. Jones
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
internal member
Name (type = personal)
NamePart (type = family)
Katehakis
NamePart (type = given)
Michael N.
DisplayForm
Michael N. Katehakis
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
internal member
Name (type = personal)
NamePart (type = family)
Dentcheva
NamePart (type = given)
Darinka
DisplayForm
Darinka Dentcheva
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
outside member
Name (type = corporate)
NamePart
Rutgers University
Role
RoleTerm (authority = RULIB)
degree grantor
Name (type = corporate)
NamePart
Graduate School - Newark
Role
RoleTerm (authority = RULIB)
school
TypeOfResource
Text
Genre (authority = marcgt)
theses
OriginInfo
DateCreated (qualifier = exact)
2014
DateOther (qualifier = exact); (type = degree)
2014-10
CopyrightDate (encoding = w3cdtf)
2014
Place
PlaceTerm (type = code)
xx
Language
LanguageTerm (authority = ISO639-2b); (type = code)
eng
Abstract (type = abstract)
In this study, an application of novel risk modeling and optimization techniques to daily portfolio management will be described. In the first part, I develop and compare specialized methods for scenario generation and scenario tree construction. The quality of multi-stage stochastic optimization models depends heavily on the quality of the underlying scenario model. First, multivariate GO-GARCH model is used to generate adequate number of scenarios. Then, five different methods, a multi-facility location based backward scenario tree generation method, and forward and backward modified K-Means and Two-Step Cluster methods are used to generate scenario trees. Next, these five methods are tested on two-stage portfolio problems with different number of scenario sets. Finally, a Monge-Kantorovich transportation model is developed to compare the probability distribution of the GARCH-generated scenarios with the probability distribution in the constructed scenario trees. In the second part, I construct a two-stage stochastic programming problem with conditional measures of risk, which is used to re-balance the portfolio on a rolling horizon basis, with transaction costs included in the model. A conditional risk mapping approach will be used in the model so that information from the previous investment period can be used in the decision for the next investment period. Artzner et al. introduced coherent risk measures that reflect the interests of risk-averse investors. I will use coherent risk measures, such as semideviation risk function of order two or higher in this study. Next, the risk-averse multicut method, which is an extension of Bender’s decomposition and proposed originally for first-order risk measure by Miller and Ruszczy´nski, will be generalized to higher order risk measures in order to solve two-stage mean-risk portfolio problem. Performance of this method with the stated risk functions are evaluated on the scenario tree which is constructed in the first part. In the third part, I present an extensive simulation study on daily returns of Dow Jones companies by using several versions of the methodology. We show that two-stage models outperform single-stage models in terms of long-term performance. We also show that using high-order risk measures are superior to first-order measures.
Subject (authority = RUETD)
Topic
Management
Subject (authority = ETD-LCSH)
Topic
Risk management
Subject (authority = ETD-LCSH)
Topic
Portfolio management
Subject (authority = ETD-LCSH)
Topic
Investment analysis
RelatedItem (type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier (type = RULIB)
ETD
Identifier
ETD_5776
PhysicalDescription
Form (authority = gmd)
electronic resource
InternetMediaType
application/pdf
InternetMediaType
text/xml
Extent
1 online resource (ix, 71 p. : ill.)
Note (type = degree)
Ph.D.
Note (type = bibliography)
Includes bibliographical references
Note (type = vita)
Includes vita
Note (type = statement of responsibility)
by Sitki Gülten
RelatedItem (type = host)
TitleInfo
Title
Graduate School - Newark Electronic Theses and Dissertations
Identifier (type = local)
rucore10002600001
Location
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NjNbRU
Identifier (type = doi)
doi:10.7282/T318384D
Genre (authority = ExL-Esploro)
ETD doctoral
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Rights

RightsDeclaration (ID = rulibRdec0006)
The author owns the copyright to this work.
RightsHolder (type = personal)
Name
FamilyName
Gülten
GivenName
Sitki
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2014-08-18 14:23:32
AssociatedEntity
Name
Sitki Gulten
Role
Copyright holder
Affiliation
Rutgers University. Graduate School - Newark
AssociatedObject
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.
RightsEvent
DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2014-10-31
DateTime (encoding = w3cdtf); (qualifier = exact); (point = end)
2015-05-02
Type
Embargo
Detail
Access to this PDF has been restricted at the author's request. It will be publicly available after May 2nd, 2015.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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ContentModel
ETD
OperatingSystem (VERSION = 5.1)
windows xp
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