En este trabajo demostramos que toda distribución hipergeométrica H(N, X, n) puede ser descrita como suma de pruebas independientes con probabilidades de éxito distintas entre sí. Tal distribución recibe habitualmente el nombre de binomial de Poisson o binomial generalizada.
The paper uses Lévy processes and bivariate Lévy copulae in order to model the behavior of intraday log-returns. Based on assumptions about the form of marginal tail integrals and a Clayton Lévy copula, the model allows for capturing intraday cross-dependency. The model is applied to VaR of the portfolios constructed on stock returns as well as on cryptocurrencies. The proposed method shows fair performance compared to classical time series models.