Multifactor Risk Attribution Applied to Systemic, Climate and Geopolitical Tail Risks for the Eurozone Banking Sector
The aim of this work is to introduce an innovative methodology for performing risk attribution within a multifactor risk framework. We applied this analysis to the assessment of systemic, climate, and geopolitical risks relative to a representative sample of Eurozone banks between 2011 and 2022. Com...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-09-01
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| Series: | Risks |
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| Online Access: | https://www.mdpi.com/2227-9091/11/10/173 |
| _version_ | 1797572341752922112 |
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| author | Giulia Bettin Gian Marco Mensi Maria Cristina Recchioni |
| author_facet | Giulia Bettin Gian Marco Mensi Maria Cristina Recchioni |
| author_sort | Giulia Bettin |
| collection | DOAJ |
| description | The aim of this work is to introduce an innovative methodology for performing risk attribution within a multifactor risk framework. We applied this analysis to the assessment of systemic, climate, and geopolitical risks relative to a representative sample of Eurozone banks between 2011 and 2022. Comparing the results to the output of a bivariate approach, we found that contemporaneous tail crises generate combined equity losses exceeding partial analysis estimates. We then attributed the combined risk to each factor and to the effect of their interaction by employing our proposed frequency-based approach. For our computations, we used multivariate GARCH, Monte Carlo simulations, and a suite of Eurozone-specific factors. Our results show that total combined risk is on average 18% higher than traditional systemic risk estimates, that climate risk more than doubled in our period of analysis, and that geopolitical risk surged to over 5% of total combined risk. Our climate risk estimate is in line with the results of the 2022 European Central Bank climate stress test, and our geopolitical risk measure shows a positive correlation with the GPRD and Threats index. |
| first_indexed | 2024-03-10T20:54:53Z |
| format | Article |
| id | doaj.art-9441819481c34e37bdc24168f64b0ead |
| institution | Directory Open Access Journal |
| issn | 2227-9091 |
| language | English |
| last_indexed | 2024-03-10T20:54:53Z |
| publishDate | 2023-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Risks |
| spelling | doaj.art-9441819481c34e37bdc24168f64b0ead2023-11-19T18:00:54ZengMDPI AGRisks2227-90912023-09-01111017310.3390/risks11100173Multifactor Risk Attribution Applied to Systemic, Climate and Geopolitical Tail Risks for the Eurozone Banking SectorGiulia Bettin0Gian Marco Mensi1Maria Cristina Recchioni2Department of Economic and Social Sciences, Università Politecnica delle Marche, 60121 Ancona, ItalyDepartment of Economic and Social Sciences, Università Politecnica delle Marche, 60121 Ancona, ItalyDepartment of Economic and Social Sciences, Università Politecnica delle Marche, 60121 Ancona, ItalyThe aim of this work is to introduce an innovative methodology for performing risk attribution within a multifactor risk framework. We applied this analysis to the assessment of systemic, climate, and geopolitical risks relative to a representative sample of Eurozone banks between 2011 and 2022. Comparing the results to the output of a bivariate approach, we found that contemporaneous tail crises generate combined equity losses exceeding partial analysis estimates. We then attributed the combined risk to each factor and to the effect of their interaction by employing our proposed frequency-based approach. For our computations, we used multivariate GARCH, Monte Carlo simulations, and a suite of Eurozone-specific factors. Our results show that total combined risk is on average 18% higher than traditional systemic risk estimates, that climate risk more than doubled in our period of analysis, and that geopolitical risk surged to over 5% of total combined risk. Our climate risk estimate is in line with the results of the 2022 European Central Bank climate stress test, and our geopolitical risk measure shows a positive correlation with the GPRD and Threats index.https://www.mdpi.com/2227-9091/11/10/173risk attributionclimate riskgeopolitical risksystemic riskmultifactor modelsrisk management |
| spellingShingle | Giulia Bettin Gian Marco Mensi Maria Cristina Recchioni Multifactor Risk Attribution Applied to Systemic, Climate and Geopolitical Tail Risks for the Eurozone Banking Sector Risks risk attribution climate risk geopolitical risk systemic risk multifactor models risk management |
| title | Multifactor Risk Attribution Applied to Systemic, Climate and Geopolitical Tail Risks for the Eurozone Banking Sector |
| title_full | Multifactor Risk Attribution Applied to Systemic, Climate and Geopolitical Tail Risks for the Eurozone Banking Sector |
| title_fullStr | Multifactor Risk Attribution Applied to Systemic, Climate and Geopolitical Tail Risks for the Eurozone Banking Sector |
| title_full_unstemmed | Multifactor Risk Attribution Applied to Systemic, Climate and Geopolitical Tail Risks for the Eurozone Banking Sector |
| title_short | Multifactor Risk Attribution Applied to Systemic, Climate and Geopolitical Tail Risks for the Eurozone Banking Sector |
| title_sort | multifactor risk attribution applied to systemic climate and geopolitical tail risks for the eurozone banking sector |
| topic | risk attribution climate risk geopolitical risk systemic risk multifactor models risk management |
| url | https://www.mdpi.com/2227-9091/11/10/173 |
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