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Conditional stochastic dominance tests in dynamic settings

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  • Jose Olmo
  • Jesus Gonzalo

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Abstract

This paper proposes nonparametric consistent tests of conditional stochastic dominance of arbitrary order in a dynamic setting. The novelty of these tests lies in the nonparametric manner of incorporating the information set into the test. The test allows for general forms of unknown serial and mutual dependence between random variables, and has an asymptotic distribution that can be easily approximated by simulation. This method has good finite-sample performance. These tests are applied to determine the investment efficiency between U S industry portfolios conditional on the dynamics of the market portfolio. The empirical analysis suggests that Telecommunications dominates the other sectoral portfolios under risk aversion.

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Bibliographic Info

Paper provided by Universidad Carlos III, Departamento de Economía in its series Economics Working Papers with number we1205.

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Date of creation: Feb 2012
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Handle: RePEc:cte:werepe:we1205

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Related research

Keywords: Hypothesis testing; Kernel estimation; Lower partial moments; Nonparametric regression; P-value transformation; Stochastic dominance;

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References

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  1. Davidson, R. & Duclos, J.-Y., 1998. "Statistical Inference for Stochastic Dominance and for the Measurement of Poverty and Inequality," G.R.E.Q.A.M. 98a14, Universite Aix-Marseille III.
  2. Kaur, Amarjot & Prakasa Rao, B.L.S. & Singh, Harshinder, 1994. "Testing for Second-Order Stochastic Dominance of Two Distributions," Econometric Theory, Cambridge University Press, vol. 10(05), pages 849-866, December.
  3. Miguel A. Delgado & Juan Carlos Escanciano, 2013. "Conditional Stochastic Dominance Testing," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(1), pages 16-28, January.
  4. Fishburn, Peter C, 1977. "Mean-Risk Analysis with Risk Associated with Below-Target Returns," American Economic Review, American Economic Association, vol. 67(2), pages 116-26, March.
  5. Bollerslev, Tim, 1987. "A Conditionally Heteroskedastic Time Series Model for Speculative Prices and Rates of Return," The Review of Economics and Statistics, MIT Press, vol. 69(3), pages 542-47, August.
  6. Newey, W.K., 1992. "Kernel Estimation of Partial Means and a General Variance Estimator," Working papers 93-3, Massachusetts Institute of Technology (MIT), Department of Economics.
  7. Oliver Linton & Esfandiar Maasoumi & Yoon-Jae Whang, 2005. "Consistent Testing for Stochastic Dominance under General Sampling Schemes," Review of Economic Studies, Oxford University Press, vol. 72(3), pages 735-765.
  8. Delgado, Miguel A. & Carlos Escanciano, J., 2007. "Nonparametric tests for conditional symmetry in dynamic models," Journal of Econometrics, Elsevier, vol. 141(2), pages 652-682, December.
  9. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
  10. Porter, R Burr, 1974. "Semivariance and Stochastic Dominance: A Comparison," American Economic Review, American Economic Association, vol. 64(1), pages 200-04, March.
  11. Kopa, Miloš & Post, Thierry, 2009. "A Portfolio Optimality Test Based on the First-Order Stochastic Dominance Criterion," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 44(05), pages 1103-1124, October.
  12. Scaillet, Olivier & Topaloglou, Nikolas, 2010. "Testing for Stochastic Dominance Efficiency," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(1), pages 169-180.
  13. Garry F. Barrett & Stephen G. Donald, 2003. "Consistent Tests for Stochastic Dominance," Econometrica, Econometric Society, vol. 71(1), pages 71-104, January.
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Cited by:
  1. Agliardi, Elettra & Agliardi, Rossella & Pinar, Mehmet & Stengos, Thanasis & Topaloglou, Nikolas, 2012. "A new country risk index for emerging markets: A stochastic dominance approach," Journal of Empirical Finance, Elsevier, vol. 19(5), pages 741-761.

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