Testing for Symmetry and Conditional Symmetry Using Asymmetric Kernels

Marcelo Fernandes, Eduardo F. Mendes and Olivier Scaillet
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Eduardo F. Mendes: Northwestern University

No 11-32, Swiss Finance Institute Research Paper Series from Swiss Finance Institute

Abstract: We derive nonparametric tests of symmetry using asymmetric kernels with either shrinking or fixed bandwidths. We show how to extend the approach to examine conditional symmetry by deriving conditions under which our tests are applicable to residuals from semiparametric models with a (sufficiently smooth) nonparametric link function. As a by-product, we prove the consistency of the asymmetric kernel estimator of the derivative of the density function. Simulations show that the asymptotic tests perform well even in very small samples, entailing better size and power properties than some of the existing symmetry tests.

Keywords: asymmetric kernel; gamma kernel; inverse Gaussian kernel; nonparametric testing; reciprocal inverse Gaussian kernel; symmetry. (search for similar items in EconPapers)
JEL-codes: C12 C14 (search for similar items in EconPapers)
Pages: 31 pages
Date: 2011-08
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Citations: View citations in EconPapers (1)

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Related works:
Journal Article: Testing for symmetry and conditional symmetry using asymmetric kernels (2015)
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Persistent link: https://EconPapers.repec.org/RePEc:chf:rpseri:rp1132

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