Connections between entropic and linear projections in asset pricing estimation

The concept of entropy has a long and distinguished history in the physical sciences and engineering, in fields ranging from thermodynamics to image processing. Each of these applications employs a probability distribution that solves a relative entropy projection problem, i.e. an optimization probl...

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Published inJournal of econometrics Vol. 107; no. 1; pp. 159 - 174
Main Authors Kitamura, Yuichi, Stutzer, Michael
Format Journal Article
LanguageEnglish
Published Amsterdam Elsevier B.V 01.03.2002
Elsevier
Elsevier Sequoia S.A
SeriesJournal of Econometrics
Subjects
Online AccessGet full text
ISSN0304-4076
1872-6895
DOI10.1016/S0304-4076(01)00118-X

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Abstract The concept of entropy has a long and distinguished history in the physical sciences and engineering, in fields ranging from thermodynamics to image processing. Each of these applications employs a probability distribution that solves a relative entropy projection problem, i.e. an optimization problem with an entropy objective, subject to linear (e.g. moment) constraints. This paper develops the relationship between relative entropy project approaches and the better-known linear projection approaches to problems of estimation and performance diagnostics for stochastic discount factor models in asset pricing. Frequentist interpretations of relative entropy, enabled by large deviations theory, are used to unify the interpretation of the seemingly disparate procedures.
AbstractList The concept of entropy has a long distinguished history in the physical sciences and engineering, in fields ranging from thermodynamics to image processing. Each of these applications employs a probability distribution that solves a relative entropy projection problem, that is, an optimization problem with the entropy objective, subject to linear (e.g. moment) constraints. This paper develops the relationship between relative entropy project approaches and the better-known linear projection approaches to problems of estimation of performance diagnostics for stochastic discount factor models in asset pricing. Frequentist interpretations of relative entropy, enabled by large deviations theory, are used to unify the interpretation of the seemingly disparate procedures.
The concept of entropy has a long and distinguished history in the physical sciences and engineering, in fields ranging from thermodynamics to image processing. Each of these applications employs a probability distribution that solves a relative entropy projection problem, i.e. an optimization problem with an entropy objective, subject to linear (e.g. moment) constraints. This paper develops the relationship between relative entropy project approaches and the better-known linear projection approaches to problems of estimation and performance diagnostics for stochastic discount factor models in asset pricing. Frequentist interpretations of relative entropy, enabled by large deviations theory, are used to unify the interpretation of the seemingly disparate procedures.
Author Stutzer, Michael
Kitamura, Yuichi
Author_xml – sequence: 1
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  givenname: Michael
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  fullname: Stutzer, Michael
  email: michael-stutzer@uiowa.edu
  organization: Department of Finance, Tippie College of Business, University of Iowa, Iowa City, IA 52242, USA
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Issue 1
Keywords C111
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Entropy
Large deviations
Information
Stochastic discount factor
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Snippet The concept of entropy has a long and distinguished history in the physical sciences and engineering, in fields ranging from thermodynamics to image...
The concept of entropy has a long distinguished history in the physical sciences and engineering, in fields ranging from thermodynamics to image processing....
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SubjectTerms Asset valuation
Econometrics
Entropy
Estimating techniques
Estimation
Generalized method of moments
GMM
Information
Large deviations
Prices
Stochastic discount factor
Stochastic models
Stochastic processes
Studies
Title Connections between entropic and linear projections in asset pricing estimation
URI https://dx.doi.org/10.1016/S0304-4076(01)00118-X
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