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.
Original language | English |
---|---|
Title of host publication | Book of Short Papers SIS 2018 |
Pages | 1429-1434 |
Number of pages | 6 |
Publication status | Published - 2018 |
Event | SIS 2018 - Palermo Duration: 20 Jun 2018 → 22 Jun 2018 |
Conference
Conference | SIS 2018 |
---|---|
City | Palermo |
Period | 20/6/18 → 22/6/18 |
Keywords
- Graphical Lasso algorithm
- Network dependence
- Systemic risk