Publication: Portfolio analysis using stochastic dominance, relative entropy, and empirical likelihood
Program
KU-Authors
KU Authors
Co-Authors
Poti, Valerio
Publication Date
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Type
Embargo Status
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Abstract
This study formulates portfolio analysis in terms of stochastic dominance, relative entropy, and empirical likelihood. We define a portfolio inefficiency measure based on the divergence between given probabilities and the nearest probabilities that rationalize a given portfolio for some admissible utility function. When applied to a sample of time-series observations in a blockwise fashion, the inefficiency measure becomes a likelihood ratio statistic for testing inequality moment conditions. The limiting distribution of the test statistic is bounded by a chi-squared distribution under general sampling schemes, allowing for conservative large-sample testing. We develop a tight numerical approximation for the test statistic based on a two-stage optimization procedure and piecewise linearization techniques. A Monte Carlo simulation study of the empirical likelihood ratio test shows superior small-sample properties compared with various generalized method of moments tests. An application analyzes the efficiency of a passive stock market index in data sets from the empirical asset pricing literature.
Source
Publisher
The Institute for Operations Research and the Management Sciences (INFORMS)
Subject
Management, Operations research, Management science
Citation
Has Part
Source
Management Science
Book Series Title
Edition
DOI
10.1287/mnsc.2015.2325