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尾部 Copula 的双样本检验及股票指数应用AI 解读

A novel, general two-sample hypothesis testing procedure is established for testing the equality of tail copulas associated with bivariate data.More precisely, using a martingale transformation of a natural twosample tail copula process, a test process is constructed, which is shown to converge in distribution to a standard Wiener process.Hence, from this test process a myriad of asymptotically distribution-free twosample tests can be obtained.The good finite-sample behavior…

Let $(X_{1},Y_{1}),\ldots,(X_{n},Y_{n})$ be an i.i.d. sample from a bivariate distribution function that lies in the max-domain of attraction of an extreme value distribution. The asymptotic joint distribution of the standardized component-wise maxima $\bigvee_{i=1}^{n}X_{i}$ and $\bigvee_{i=1}^{n}Y_{i}$ is then characterized by the marginal extreme value indices and the tail copula $R$. We propose a procedure for constructing asymptotically distribution-free goodness-of-fit…