5 papers
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…
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…
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…
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…
A bootstrap test to detect prominent Granger-causalities across frequencies
Matteo Farné, Angela Montanari
Granger-causality in the frequency domain is an emerging tool to analyze the causal relationship between two time series. We propose a bootstrap test on unconditional and condition…