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Stochastic Programming DEA Model of Fundamental Analysis of Public Firms for Portfolio Selection

  • N. C. P. Edirisinghe
Conference paper
Part of the Operations Research Proceedings book series (ORP)

Abstract

A stochastic programming (SP) extension to the traditional Data Envelopment Analysis (DEA) is developed when input/output parameters are random variables. The SPDEA framework yields a robust performance metric for the underlying firms by controlling for outliers and data uncertainty. Using accounting data, SPDEA determines a relative financial strength (RFS) metric that is strongly correlated with stock returns of public firms. In contrast, the traditional DEA model overestimates actual firm strengths. The methodology is applied to public firms covering all major U.S. market sectors using their quarterly financial statement data. RFSbased portfolios yield superior out-of-sample performance relative to sector-based ETF portfolios or broader market index.

Keywords

Data Envelopment Analysis Stock Return Portfolio Selection Data Envelopment Analysis Model Public Firm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.College of BusinessUniversity of TennesseeKnoxvilleUSA

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