Conditional Stochastic Dominance Tests In Dynamic Settings
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.
Volume (Year): 55 (2014)
Issue (Month): (08)
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- 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.
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- Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, number 8355, March.
- 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.
- 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. Full references (including those not matched with items on IDEAS)
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