A Kolmogorov-Smirnov Type Test for Positive Quadrant Dependence

Olivier Scaillet

FAME Research Paper Series from International Center for Financial Asset Management and Engineering

Abstract: We consider a consistent test, that is similar to a Kolmogorov-Smirnov test, of the complete set of restrictions that relate to the copula representation of positive quadrant dependence. For such a test we propose and justify inference relying on a simulation based multiplier method and a bootstrap method. We also explore the finite sample behaviour of both methods with Monte Carlo experiments. A first empirical illustration is given for US insurance claim data. A second one examines the presence of positive quadrant dependence in life expectancies at birth of males and females among countries.

Keywords: Nonparametric; Positive Quadrant Dependence; Copula; Risk Management; Loss Severity Distribution; Bootstrap; Multiplier Method; Empirical Process (search for similar items in EconPapers)
JEL-codes: C12 D81 G10 G21 G22 (search for similar items in EconPapers)
Date: 2005-01
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-fin and nep-rmg
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Citations: View citations in EconPapers (28)

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