The high level of integration of international financial markets highlights the need to accurately assess contagion and systemic risk under different market conditions. To this end, we develop a quantile graphical model to identify the tail conditional dependence structure in multivariate data across different quantiles of the marginal distributions of the variables of interest. To implement the procedure, we consider the Multivariate Asymmetric Laplace distribution and exploit its location-scale mixture representation to build a penalized EM algorithm for estimating the sparse precision matrix of the distribution by means of an L1 penalty. The empirical application is performed on a large set of commodities representative of the energy, agricultural and metal sectors.

Graphical Models for Commodities: A Quantile Approach / Foroni, Beatrice; Merlo, Luca; Petrella, Lea. - (2022), pp. 253-259. ((Intervento presentato al convegno Tenth International Hybrid Conference on MATHEMATICAL AND STATISTICAL METHODS FOR ACTUARIAL SCIENCES AND FINANCE tenutosi a Salerno, Italia [10.1007/978-3-030-99638-3_41].

Graphical Models for Commodities: A Quantile Approach

Beatrice Foroni
Primo
;
Luca Merlo
Secondo
;
Lea Petrella
Ultimo
2022

Abstract

The high level of integration of international financial markets highlights the need to accurately assess contagion and systemic risk under different market conditions. To this end, we develop a quantile graphical model to identify the tail conditional dependence structure in multivariate data across different quantiles of the marginal distributions of the variables of interest. To implement the procedure, we consider the Multivariate Asymmetric Laplace distribution and exploit its location-scale mixture representation to build a penalized EM algorithm for estimating the sparse precision matrix of the distribution by means of an L1 penalty. The empirical application is performed on a large set of commodities representative of the energy, agricultural and metal sectors.
978-3-030-99637-6
978-3-030-99638-3
File allegati a questo prodotto
File Dimensione Formato  
Foroni_Graphical-Models_2022.pdf

solo gestori archivio

Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 126.2 kB
Formato Adobe PDF
126.2 kB Adobe PDF   Visualizza/Apri   Richiedi una copia
Foroni_Bookmatter-MathematicalAndStatisticalMeth_2022.pdf

solo gestori archivio

Note: https://link.springer.com/book/10.1007/978-3-030-99638-3
Tipologia: Altro materiale allegato
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 159.24 kB
Formato Adobe PDF
159.24 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11573/1629398
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact