Testing for equality between conditional copulas given discretized conditioning events

Alexis Derumigny, Jean David Fermanian, Aleksey Min

Research output: Contribution to journalArticlepeer-review


Several procedures have been recently proposed to test the simplifying assumption for conditional copulas. Instead of considering pointwise conditioning events, we study the constancy of the conditional dependence structure when some covariates belong to general Borel conditioning subsets. We introduce several test statistics based on the equality of conditional Kendall's taus and derive their asymptotic distributions under the null hypothesis. In settings where such conditioning events are not fixed ex ante, we propose a data-driven procedure to recursively build such relevant subsets. This procedure is based on decision trees that maximize the differences between the conditional Kendall's taus, which correspond to the leaves of the trees. Empirical results for such tests are illustrated in the Supplementary Material. Moreover, a study of the conditional dependence between financial stock returns is presented and highlights specific contagion effects of past returns. The last application deals with conditional dependence between coverage amounts in an insurance dataset.

Original languageEnglish
Pages (from-to)1084-1110
Number of pages27
JournalCanadian Journal of Statistics
Issue number4
StatePublished - Dec 2023


  • Conditional copula
  • conditional Kendall's tau
  • decision tree
  • simplifying assumption


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