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Optimizing dynamic portfolio selection

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TypeOfResource
Text
TitleInfo (ID = T-1)
Title
Optimizing dynamic portfolio selection
SubTitle
PartName
PartNumber
NonSort
Identifier
ETD_2104
Identifier (type = hdl)
http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000051917
Language (objectPart = )
LanguageTerm (authority = ISO639-2); (type = code)
eng
Genre (authority = marcgt)
theses
Subject (ID = SBJ-1); (authority = RUETD)
Topic
Industrial and Systems Engineering
Subject (ID = SBJ-2); (authority = ETD-LCSH)
Topic
Portfolio management
Subject (ID = SBJ-3); (authority = ETD-LCSH)
Topic
Investment analysis
Abstract
In this dissertation, a control-theoretic decision model is proposed for an agent to “optimally” allocate and deploy its financial resources over time among a dynamically changing list of opportunities (e.g., financial assets), in an uncertain market environment. This control-theoretic approach is unique in the sense that it solves the problem at distinct time epochs over a finite time horizon. The solution is a sequence of actions with the objective of optimizing a reward function over that time horizon.
While the above problem is quite general, we will focus solely on the problem of dynamic financial portfolio management. The dynamic portfolio model looks at the portfolio as a moving object to achieve a maximal expected utility for a given risk level and time horizon. We tackle this problem using Semi-Markov Decision Processes and develop an efficient solution methodology based on the Q-learning algorithm. The performance of the model is analyzed, and results from the model are compared to a known market index.
The “optimal” portfolio management policy is then extended to configurations whereby only incomplete information is available. Furthermore, quality of information and its impact on the decision making process is assessed. Here the market environment is characterized by its volatility and price dynamics. The existence of other agents in the market place, who can act adversarial or collaborative, further complicates the underlying price dynamics. The complexity of interactions among different agents is an important challenge for the dynamic portfolio management problem. We fully examine this challenge using a game-theoretic approach to determine the optimal actions of non-price-taking agents with and without a debt constraint.
PhysicalDescription
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electronic resource
Extent
viii, 98 p. : ill.
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Note (type = degree)
Ph.D.
Note (type = bibliography)
Includes bibliographical references (p. 89-96)
Note (type = statement of responsibility)
by Haleh Valian
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Valian
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Haleh
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Haleh Valian
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Jafari
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Mohsen
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chair
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Advisory Committee
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Mohsen A Jafari
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Boucher
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Thomas
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internal member
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Advisory Committee
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Thomas O Boucher
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Elsayed
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Advisory Committee
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Longo
NamePart (type = given)
John
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outside member
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Advisory Committee
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John M Longo
Name (ID = NAME-1); (type = corporate)
NamePart
Rutgers University
Role
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degree grantor
Name (ID = NAME-2); (type = corporate)
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Graduate School - New Brunswick
Role
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school
OriginInfo
DateCreated (point = ); (qualifier = exact)
2009
DateOther (qualifier = exact); (type = degree)
2009-10
Place
PlaceTerm (type = code)
xx
Location
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NjNbRU
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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
Identifier (type = doi)
doi:10.7282/T3125ST8
Genre (authority = ExL-Esploro)
ETD doctoral
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RightsDeclaration (AUTHORITY = GS); (ID = rulibRdec0006)
The author owns the copyright to this work
Copyright
Status
Copyright protected
Notice
Note
Availability
Status
Open
Reason
Permission or license
Note
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Name
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Valian
GivenName
Haleh
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Copyright holder
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DateTime
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Haleh Valian
Affiliation
Rutgers University. Graduate School - New Brunswick
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License
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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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Technical

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ETD
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application/x-tar
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