An alternative generating mechanism for non-strict bivariate Archimedean copulas via the Lorenz curve of a positive random variable is proposed. Lorenz curves have been extensively studied in economics and statistics to characterize wealth inequality and tail risk. In this paper, these curves...

We propose a methodology to look at violence in particular, and other aspects of quantitative historiography in general, in a way compatible with statistical inference, which needs to accommodate the fat-tailedness of the data and the unreliability of the reports of conflicts. We investigate the...

Statistical analyses on actual data depict operational risk as an extremely heavy-tailed phenomenon, able to generate losses so extreme as to suggest the use of infinite-mean models. But no loss can actually destroy more than the entire value of a bank or of a company, and this upper bound...

We examine statistical pictures of violent conflicts over the last 2000 years, finding techniques for dealing with incompleteness and unreliability of historical data.We introduce a novel approach to apply extreme value theory to fat-tailed variables that have a remote, but nonetheless finite...

We study the problems related to the estimation of the Gini index in presence of a fat-tailed data generating process, i.e. one in the stable distribution class with finite mean but infinite variance (i.e. with tail index α ∈ (1, 2)). We show that, in such a case, the Gini coefficient cannot...

In the current Basel framework, the A-IRB formula, used by banks or other financial institutions to compute their Regulatory Capital to hedge Credit Risk, completely neglects any possible dependence between Probability of Default and Loss Given Default. This happens since it uses a stressed...

The recent economic events driven by the big financial crisis of 2007-08 has cogently put to the fore the limits and drawbacks of the ruling research paradigm in macroeconomics. This volume goes to the root of the problem by offering a workable alternative to the renowned issue of the...