The study of dependence between random variables is the core of theoretical and applied statistics. Static and dynamic copula models are useful for describing the dependence structure, which is fully encrypted in the copula probability density function. However, these models are not always able...

We are interested in the analysis of the concept of interpretability associated with a ML algorithm. We distinguish between the “How”, i.e., how a black box or a very complex algorithm works, and the “Why”, i.e. why an algorithm produces such a result. These questions appeal to many...

In order to measure the interdependence between different markets, we investigate and compare different measures of dependence including cross-correlation, conditional correlation, concordance and correlation in tails. In the latter case, we use the notion of copula and we define two kinds of...

Business surveys are an important element in the analysis of the short-term economic situation because of the timeliness and nature of the information they convey. Especially, surveys are often involved in econometric models in order to provide an early assessment of the current state of the...

The aim of this research is to explore the econometric features of Bitcoin-USD rates. Various non-Gaussian models are fitted to daily returns in order to underline the unique characteristics of Bitcoin when compared to other more traditional currencies. Market efficiency hypothesis is tested...

In this paper, we focus on the building of an invariant distribution function associated to a non-stationary sample. After discussing some specific problems encountered by non-stationarity inside samples like the 'spurious' long memory effect, we build a sequence of stationary processes...