We propose a method to extract significant risk interactions between Countries adopting the Graphical Lasso algorithm, used in graph theory to sort out the spurious effect of common components. In this context, the major issue is the definition of the penalization parameter. We propose a search algorithm aimed at the best separation of the variables (expressed in terms of conditional dependence) given an a priori desired partition. The case study focuses on Sovereign Bond Yields over the period 2009–2017. The proposed algorithm is used in systemic risk estimation of the Euro area sovereigns.

Arbia, G., Bramante, R., Facchinetti, S., Zappa, D., Sovereign co-risk measures in the Euro Area, in Book of Short Papers SIS 2018, (Palermo, 20-22 June 2018), Pearson Italia, Palermo 2018: 1429-1434 [http://hdl.handle.net/10807/128690]

Sovereign co-risk measures in the Euro Area

Arbia, Giuseppe;Bramante, Riccardo;Facchinetti, Silvia;Zappa, Diego
2018

Abstract

We propose a method to extract significant risk interactions between Countries adopting the Graphical Lasso algorithm, used in graph theory to sort out the spurious effect of common components. In this context, the major issue is the definition of the penalization parameter. We propose a search algorithm aimed at the best separation of the variables (expressed in terms of conditional dependence) given an a priori desired partition. The case study focuses on Sovereign Bond Yields over the period 2009–2017. The proposed algorithm is used in systemic risk estimation of the Euro area sovereigns.
Inglese
Book of Short Papers SIS 2018
SIS 2018
Palermo
20-giu-2018
22-giu-2018
9788891910233
Pearson Italia
Arbia, G., Bramante, R., Facchinetti, S., Zappa, D., Sovereign co-risk measures in the Euro Area, in Book of Short Papers SIS 2018, (Palermo, 20-22 June 2018), Pearson Italia, Palermo 2018: 1429-1434 [http://hdl.handle.net/10807/128690]
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/10807/128690
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