activity
20172025
most citedEuropean banks' business models and their credit risk: A cluster analysis in a high-dimensional context

24 citations · 56 across the 8 of their papers we have counts for

collaborators

8 papers

stat.AP2025

The Impact of Climatic Factors on Respiratory Pharmaceutical Demand: A Comparison of Forecasting Models for Greece

Viviana Schisa, Matteo Farnè

Climate change is increasingly recognized as a driver of health-related outcomes, yet its impact on pharmaceutical demand remains largely understudied. As environmental conditions…

math.ST2022

Large covariance matrix estimation via penalized log-det heuristics

Enrico Bernardi, Matteo Farnè

This paper provides a comprehensive estimation framework for large covariance matrices via a log-det heuristics augmented by a nuclear norm plus -norm penalty. We develop…

stat.ME2021

Robust selection of predictors and conditional outlier detection in a perturbed large-dimensional regression context

Matteo Farnè, Angelos Vouldis

This paper presents a fast methodology, called ROBOUT, to identify outliers in a response variable conditional on a set of linearly related predictors, retrieved from a large granu…

math.ST2021

Large factor model estimation by nuclear norm plus norm penalization

Matteo Farnè, Angela Montanari

This paper provides a comprehensive estimation framework via nuclear norm plus norm penalization for high-dimensional approximate factor models with a sparse residual covaria…

math.ST2021

An algebraic estimator for large spectral density matrices

Matteo Barigozzi, Matteo Farnè

We propose a new estimator of high-dimensional spectral density matrices, called UNshrunk ALgebraic Spectral Estimator (UNALSE), under the assumption of an underlying low rank plus…

stat.AP2019★ 24 cited

European banks' business models and their credit risk: A cluster analysis in a high-dimensional context

Matteo Farnè, Angelos T. Vouldis

In this paper, we investigate the credit risk in the loan portfolio of banks following different business models. We develop a data-driven methodology for identifying the business…