Manuele Leonelli (IE University)
Friday 6th November, 2020 15:00-16:00 Zoom
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Meeting ID: 859 7333 5962
Diagonal distributions are an extension of marginal distributions, which can be used to summarize and efficiently visualize the main features of multivariate distributions in arbitrary dimensions. The main diagonal is studied in detail, which consists of a mean-constrained univariate distribution function on [0; 1], whose variance connects with Spearman's rho, and whose mass at the endpoints 0 and 1 offers insights on the strength of tail dependence. To learn about the main diagonal density from data, histogram and kernel-based methods that take advantage of auxiliary information in the form of a moment constraint to which diagonal distributions must obey are introduced. An application is given illustrating how diagonal densities can be used in order to contrast the diversification of a portfolio based on FAANG stocks against one based on crypto-assets.