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Conditional Stochastic Dominance Tests In Dynamic Settings

Author

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  • Jesus Gonzalo
  • Jose Olmo

Abstract

This article 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. 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 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.

Suggested Citation

  • Jesus Gonzalo & Jose Olmo, 2014. "Conditional Stochastic Dominance Tests In Dynamic Settings," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 55, pages 819-838, August.
  • Handle: RePEc:wly:iecrev:v:55:y:2014:i::p:819-838
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    File URL: http://hdl.handle.net/10.1111/iere.12072
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    References listed on IDEAS

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    1. Scaillet, Olivier & Topaloglou, Nikolas, 2010. "Testing for Stochastic Dominance Efficiency," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(1), pages 169-180.
    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. Garry F. Barrett & Stephen G. Donald, 2003. "Consistent Tests for Stochastic Dominance," Econometrica, Econometric Society, vol. 71(1), pages 71-104, January.
    4. 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.
    5. 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.
    6. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, number 8355.
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    Citations

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    Cited by:

    1. Stelios Arvanitis & Nikolas Topaloglou, 2015. "Consistent tests for risk seeking behavior: A stochastic dominance approach Abstract We develop non-parametric tests for prospect stochastic dominance Efficiency (PSDE) and Markowitz stochastic domina," Working Papers 201511, Athens University Of Economics and Business, Department of Economics.
    2. E. Agliardi & M. Pinar & T. Stengos, 2014. "Assessing temporal trends and industry contributions to air and water pollution using stochastic dominance," Working Papers wp981, Dipartimento Scienze Economiche, Universita' di Bologna.
    3. repec:eee:ejores:v:261:y:2017:i:2:p:666-678 is not listed on IDEAS
    4. 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.
    5. Olmo, José & Sanso-Navarro, Marcos, 2012. "Forecasting the performance of hedge fund styles," Journal of Banking & Finance, Elsevier, vol. 36(8), pages 2351-2365.
    6. repec:eee:econom:v:198:y:2017:i:2:p:253-270 is not listed on IDEAS

    More about this item

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • G1 - Financial Economics - - General Financial Markets

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