activity
20132024
most citedA note on the empirical process of strongly dependent stable random variables

3 citations · 8 across the 10 of their papers we have counts for

collaborators

10 papers

math.ST2024

Varentropy Estimation via Nearest Neighbor Graphs

Nikolai Leonenko, Yu Sun, Emanuele Taufer

The Varentropy is a measure of the variability of the information content of random vector and it is invariant under affine transformations. We introduce the statistical estimate o…

q-fin.ST2022

A generalized precision matrix for t-Student distributions in portfolio optimization

Karoline Bax, Emanuele Taufer, Sandra Paterlini

The Markowitz model is still the cornerstone of modern portfolio theory. In particular, when focusing on the minimum-variance portfolio, the covariance matrix or better its inverse…

stat.ME2021

A 2-stage elastic net algorithm for estimation of sparse networks with heavy tailed data

Davide Bernardini, Sandra Paterlini, Emanuele Taufer

We propose a new 2-stage procedure that relies on the elastic net penalty to estimate a network based on partial correlations when data are heavy-tailed. The new estimator allows t…

stat.ME2021

New estimation approaches for graphical models with elastic net penalty

Davide Bernardini, Sandra Paterlini, Emanuele Taufer

In the context of undirected Gaussian graphical models, we introduce three estimators based on elastic net penalty for the underlying dependence graph. Our goal is to estimate the…

stat.ME2018★ 2 cited

A goodness of fit test for the Pareto distribution

Emanuele Taufer, Flavio Santi, Giuseppe Espa +1

The Zenga (1984) inequality curve is constant in p for Type I Pareto distributions. This characterizing behavior will be exploited to obtain graphical and analytical tools for tail…

stat.ME2018

On a property of the inequality curve

Emanuele Taufer, Flavio Santi, Giuseppe Espa +1

The Zenga (1984) inequality curve is constant in p for Type I Pareto distributions. We show that this property holds exactly only for the Pareto distribution and, asymptotically, f…