90 citations · 169 across the 8 of their papers we have counts for
10 papers
Selection Confidence Sets for Equally Weighted Portfolios
Davide Ferrari, Alessandro Fulci, Sandra Paterlini
Given a universe of N assets, investors often form equally weighted portfolios (EWPs) by selecting subsets of assets. EWPs are simple, robust, and competitive out-of-sample, yet th…
Sparse Graphical Modelling via the Sorted L-Norm
Riccardo Riccobello, Malgorzata Bogdan, Giovanni Bonaccolto +3
Sparse graphical modelling has attained widespread attention across various academic fields. We propose two new graphical model approaches, Gslope and Tslope, which provide sparse…
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…
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…
Environmental, Social, Governance scores and the Missing pillar -- Why does missing information matter?
Özge Sahin, Karoline Bax, Claudia Czado +1
Environmental, Social, and Governance (ESG) scores measure companies' performance concerning sustainability and societal impact and are organized on three pillars: Environmental (E…
ESG, Risk, and (Tail) Dependence
Karoline Bax, Özge Sahin, Claudia Czado +1
While environmental, social, and governance (ESG) trading activity has been a distinctive feature of financial markets, the debate if ESG scores can also convey information regardi…
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…
Modelling Extremal Dependence for Operational Risk by a Bipartite Graph
Oliver Kley, Claudia Klüppelberg, Sandra Paterlini
We introduce a statistical model for operational losses based on heavy-tailed distributions and bipartite graphs, which captures the event type and business line structure of opera…
Sparse Portfolio Selection via the sorted -Norm
Philipp J. Kremer, Sangkyun Lee, Malgorzata Bogdan +1
We introduce a financial portfolio optimization framework that allows us to automatically select the relevant assets and estimate their weights by relying on a sorted -Norm…
Adaptive Minimax Estimation over Sparse -Hulls
Zhan Wang, Sandra Paterlini, Frank Gao +1
Given a dictionary of initial estimates of the unknown true regression function, we aim to construct linearly aggregated estimators that target the best performance among all…