Conditional stochastic dominance tests in dynamic settings
AbstractThis 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.
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Bibliographic InfoPaper provided by Universidad Carlos III, Departamento de Economía in its series Economics Working Papers with number we1029.
Date of creation: Oct 2010
Date of revision:
Empirical processes; Hypothesis testing; Lower partial moments; Martingale difference sequence; P-value transformation; Stochastic dominance;
Other versions of this item:
- Gonzalo, Jesus & Olmo, Jose, 2013. "Conditional stochastic dominance tests in dynamic settings," Discussion Paper Series In Economics And Econometrics 1311, Economics Division, School of Social Sciences, University of Southampton.
- Jose Olmo & Jesus Gonzalo, 2012. "Conditional stochastic dominance tests in dynamic settings," Economics Working Papers we1205, Universidad Carlos III, Departamento de Economía.
- 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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