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A Kolmogorov-Smirnov Type Test for Positive Quadrant Dependence

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Author Info
Olivier Scaillet (HEC, University of Geneva and FAME)

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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.

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Publisher Info
Paper provided by International Center for Financial Asset Management and Engineering in its series FAME Research Paper Series with number rp128.

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Date of creation: Jan 2005
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Handle: RePEc:fam:rpseri:rp128

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Related research
Keywords: Nonparametric; Positive Quadrant Dependence; Copula; Risk Management; Loss Severity Distribution; Bootstrap; Multiplier Method; Empirical Process;

Find related papers by JEL classification:
C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Hypothesis Testing
D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Mortgages
G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies

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This page was last updated on 2009-11-19.

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