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Risk-adjusted information content in option prices

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TypeOfResource
Text
TitleInfo (ID = T-1)
Title
Risk-adjusted information content in option prices
Identifier
ETD_2669
Identifier (type = hdl)
http://hdl.rutgers.edu/1782.2/rucore10002600001.ETD.000052945
Language
LanguageTerm (authority = ISO639-2); (type = code)
English
Genre (authority = marcgt)
theses
Subject (ID = SBJ-1); (authority = RUETD)
Topic
Management
Subject (ID = SBJ-2); (authority = ETD-LCSH)
Topic
Options (Finance)--Prices
Subject (ID = SBJ-3); (authority = ETD-LCSH)
Topic
Options (Finance)--Prices--Econometric models
Abstract (type = abstract)
There are many measures to price an option. This dissertation investigates a risk-adjusted measure to price the option with an alternative numeraire that retains the expected return of the underlying in the pricing equation. This model is consistent with the Black-Scholes model when their assumptions are imposed and is consistent with the standard capital asset pricing model. Unlike many asset pricing models that rely on historical data, we provide a forward-looking approach for extracting the ex ante return distribution parameters of the underlying from option prices. Using this framework and observing the market prices of options, we jointly extract implied return and implied volatility of the underlying assets for different days-to-maturity using a grid search method of global optima. Our approach does not use a preference structure or information about the market such as the market risk premium to estimate the expected return of the underlying asset. We find that when there are not many near-the-money traded options available our approach provides a better solution to forecast future volatility than the Black-Scholes implied volatility. Further, our results show that option prices reflect a higher expectation of stock return in the short-term, but a lower expectation of stock return in the long-term that is robust to many alternative tests. We further find that ex ante expected returns have a positive and significant cross-sectional relation with ex ante betas even in the presence of firm size, book-to-market, and momentum. The cross-sectional regression estimate of ex ante market risk premium has a statistical significance as well as an economic significance in that it contains significant forward-looking information on future macroeconomic conditions. Furthermore, in an ex ante world, firm size is still negatively significant, but book-to-market is also negatively significant, which is the opposite of the ex post results. Our risk-adjusted approach provides a framework for extraction of ex ante information from option prices with alternative assumptions of stochastic processes. In this vein, we provide a risk-adjusted stochastic volatility pricing model and discuss its estimation process.
PhysicalDescription
Form (authority = gmd)
electronic resource
Extent
viii, 178 p. : ill.
InternetMediaType
application/pdf
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text/xml
Note (type = degree)
Ph.D.
Note
Includes abstract
Note
Vita
Note (type = bibliography)
Includes bibliographical references
Note (type = statement of responsibility)
by Durga Prasad Panda
Name (ID = NAME-1); (type = personal)
NamePart (type = family)
Panda
NamePart (type = given)
Durga Prasad
Role
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author
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Durga Panda
Name (ID = NAME-2); (type = personal)
NamePart (type = family)
Chen
NamePart (type = given)
Ren-Raw
Role
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chair
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Advisory Committee
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Ren-Raw Chen
Name (ID = NAME-3); (type = personal)
NamePart (type = family)
Lee
NamePart (type = given)
Cheng-Few
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RoleTerm (authority = RULIB)
internal member
Affiliation
Advisory Committee
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Cheng-Few Lee
Name (ID = NAME-4); (type = personal)
NamePart (type = family)
Palmon
NamePart (type = given)
Oded
Role
RoleTerm (authority = RULIB)
internal member
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Advisory Committee
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Oded Palmon
Name (ID = NAME-5); (type = personal)
NamePart (type = family)
Kim
NamePart (type = given)
Dongcheol
Role
RoleTerm (authority = RULIB)
outside member
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Advisory Committee
DisplayForm
Dongcheol Kim
Name (ID = NAME-6); (type = personal)
NamePart (type = family)
John
NamePart (type = given)
Kose
Role
RoleTerm (authority = RULIB)
outside member
Affiliation
Advisory Committee
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Kose John
Name (ID = NAME-1); (type = corporate)
NamePart
Rutgers University
Role
RoleTerm (authority = RULIB)
degree grantor
Name (ID = NAME-2); (type = corporate)
NamePart
Graduate School - Newark
Role
RoleTerm (authority = RULIB)
school
OriginInfo
DateCreated (qualifier = exact)
2010
DateOther (qualifier = exact); (type = degree)
2010
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 - Newark Electronic Theses and Dissertations
Identifier (type = local)
rucore10002600001
Location
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NjNbRU
Identifier (type = doi)
doi:10.7282/T3TD9XF3
Genre (authority = ExL-Esploro)
ETD doctoral
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Rights

RightsDeclaration (AUTHORITY = GS); (ID = rulibRdec0006)
The author owns the copyright to this work.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
RightsHolder (ID = PRH-1); (type = personal)
Name
FamilyName
Panda
GivenName
Durga
Role
Copyright Holder
RightsEvent (ID = RE-1); (AUTHORITY = rulib)
Type
Permission or license
DateTime
2010-04-26 20:18:12
AssociatedEntity (ID = AE-1); (AUTHORITY = rulib)
Role
Copyright holder
Name
Durga Panda
Affiliation
Rutgers University. Graduate School - Newark
AssociatedObject (ID = AO-1); (AUTHORITY = rulib)
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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Technical

ContentModel
ETD
MimeType (TYPE = file)
application/pdf
MimeType (TYPE = container)
application/x-tar
FileSize (UNIT = bytes)
2529280
Checksum (METHOD = SHA1)
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