Conditional stochastic dominance tests in dynamic settings
This paper proposes nonparametric consistent tests of conditional stochastic dominance of arbitrary order in a dynamic setting. The novelty of these tests resides on 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 under the null hypothesis that can be easily approximated by a p-value transformation method. This method has a good finite-sample performance. These tests are applied to determine investment efficiency between US industry portfolios conditional on the performance of the market portfolio. Our analysis suggests that Utilities are the best performing sectors in normal as well as distress episodes of the market.
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- 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.
- Escanciano, Juan Carlos & Delgado, Miguel A., 2011. "Conditional stochastic dominance testing," UC3M Working papers. Economics we1138, Universidad Carlos III de Madrid. Departamento de Economía.
- Garry F. Barrett & Stephen G. Donald, 2003. "Consistent Tests for Stochastic Dominance," Econometrica, Econometric Society, vol. 71(1), pages 71-104, January.
- Scaillet, Olivier & Topaloglou, Nikolas, 2010. "Testing for Stochastic Dominance Efficiency," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(1), pages 169-180.
- Olivier Scaillet & Nikolas Topaloglou, 2005. "Testing for Stochastic Dominance Efficiency," FAME Research Paper Series rp154, International Center for Financial Asset Management and Engineering.
- Nikolas Topaloglou & Olivier Scaillet & University of Geneva, 2006. "Testing foe Stochastic Dominance Efficiency," Computing in Economics and Finance 2006 74, Society for Computational Economics.
- Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, number 8355.
- 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)
When requesting a correction, please mention this item's handle: RePEc:cte:werepe:we1029. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Ana Poveda)
If references are entirely missing, you can add them using this form.