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

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Operations Research Proceedings 2011

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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.

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References

  1. Banker, R.D.: Maximum likelihood, consistency and DEA: Statistical foundations. Management Science 39 1265–1273 (1993)

    Article  Google Scholar 

  2. Banker, R.D., Natarajan, R.: Evaluating contextual variables affecting productivity using Data Envelopment Analysis. Operations Research 56 48–58 (2008)

    Article  Google Scholar 

  3. Charnes, A., Cooper, W.W., Rhodes, E.: Measuring the efficiency of decision-making units. European Journal of Operational Research 2, 429–444 (1978)

    Article  Google Scholar 

  4. Dusansky, R.,Wilson, P.W.: On the relative efficiency of alternative modes of producing public sector output: The case of the developmentally disabled. European Journal of Operational Research 80 608–628 (1995)

    Article  Google Scholar 

  5. Edirisinghe, N.C.P., Zhang, X.: Portfolio selection under DEA-based relative financial strength indicators: Case of US industries. Journal of the Operational Research Society 59 842–56 (2008)

    Article  Google Scholar 

  6. Fama, E.F.: Efficient capital markets: A review of theory and empirical work. Journal of Finance 25 383-417 (1970)

    Article  Google Scholar 

  7. Huang, M., Li, S.X,: Stochastic DEA models with different types of input-output disturbances. Journal of Productivity Analysis 15 95–113 (2001)

    Google Scholar 

  8. Olesen, O.B., Petersen, N.C.: Chance constrained efficiency evaluation. Management Science 41 442–457 (1995)

    Google Scholar 

  9. Post,T.: Performance evaluation in stochastic environments using mean-variance Data Envelopment Analysis. Operations Research 49 281–292 (2001)

    Article  Google Scholar 

  10. Sengupta, J.K.: Efficiency measurement in stochastic input-output systems. International Journal of Systems Science 13 273–287 (1982)

    Article  Google Scholar 

  11. Wilson, G.W., Jadlow, J.M.: Competition, profit incentives, and technical efficiency in the provision of nuclear medicine services. The Bell Journal of Economics 13 472–482 (1982)

    Article  Google Scholar 

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Correspondence to N. C. P. Edirisinghe .

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Edirisinghe, N.C.P. (2012). Stochastic Programming DEA Model of Fundamental Analysis of Public Firms for Portfolio Selection. In: Klatte, D., Lüthi, HJ., Schmedders, K. (eds) Operations Research Proceedings 2011. Operations Research Proceedings. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29210-1_86

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