We develop a test of constant central asymmetry between two copulas estimated through their empirical counterpart. We provide inference under standard assumptions for stationary time series. The tie-break bootstrap is used for calculating p-values of the proposed Cram{\'e}r--von Mises test statistic. Finite sample properties are assessed with Monte Carlo experiments. We apply the testing procedure to the US portfolio industry returns during the subprime crisis.
Testing for Constant Central Asymmetry Between Two Copulas
Frattarolo, Lorenzo
2025-01-01
Abstract
We develop a test of constant central asymmetry between two copulas estimated through their empirical counterpart. We provide inference under standard assumptions for stationary time series. The tie-break bootstrap is used for calculating p-values of the proposed Cram{\'e}r--von Mises test statistic. Finite sample properties are assessed with Monte Carlo experiments. We apply the testing procedure to the US portfolio industry returns during the subprime crisis.
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