BFS 2002 

Contributed Talk 
Olivier Scaillet, Michel Denuit
We consider distributional free inference to test for positive quadrant dependence, i.e. for the probability that two variables are imultaneously small (or large) being at least
as great as it would be were they dependent.
Tests for its generalisation in higher dimensions, namely positive orthant dependences, are also analysed. We propose two types of testing procedures. The first procedure is
based on the specification of the dependence concepts in terms of distribution functions,
while the second procedure exploits the copula representation. For each specification a distance test and an intersectionunion test for inequality constraints are developed depending on the definition of null and alternative hypotheses. An empirical illustration is given for US and Danish insurance claim data.
Practical implications for the design of reinsurance treaties are also discussed.
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