In the post-pandemic era, the exposure to leveraged finance has emerged as a key factor of vulnerability for banks, coping with increasing inflation and interest rates. For this reason, the growth of the leveraged loans market is receiving significant attention from the Authorities (e.g. ECB, 2022). In this paper, we analyze an original sample of leveraged loans (1699) that combines instrument-specific information and the composition of the syndicates, with a specific focus on the G-SIBs participation from 2014 to 2021. The aim is to identify risk indicators that take into account the G-SIBs exposure to risky leveraged loans, the potential impact of the banks’ size and their interconnectedness. For this purpose, using M-Quantile regression for binary data, it is possible to obtain a first indicator measuring heterogeneity among banks in terms of credit risk exposure, a second indicator that combines the previous one with the banks’ size, and a third indicator as a measure of interconnectedness between banks.

Leveraged finance exposure in the banking system: Systemic risk and interconnectedness / G. De Novellis, P. Musile Tanzi, M.G. Ranalli, E. Stanghellini. - In: JOURNAL OF INTERNATIONAL FINANCIAL MARKETS, INSTITUTIONS & MONEY. - ISSN 1042-4431. - 90:(2024), pp. 101890.1-101890.18. [10.1016/j.intfin.2023.101890]

Leveraged finance exposure in the banking system: Systemic risk and interconnectedness

P. Musile Tanzi
Secondo
;
2024

Abstract

In the post-pandemic era, the exposure to leveraged finance has emerged as a key factor of vulnerability for banks, coping with increasing inflation and interest rates. For this reason, the growth of the leveraged loans market is receiving significant attention from the Authorities (e.g. ECB, 2022). In this paper, we analyze an original sample of leveraged loans (1699) that combines instrument-specific information and the composition of the syndicates, with a specific focus on the G-SIBs participation from 2014 to 2021. The aim is to identify risk indicators that take into account the G-SIBs exposure to risky leveraged loans, the potential impact of the banks’ size and their interconnectedness. For this purpose, using M-Quantile regression for binary data, it is possible to obtain a first indicator measuring heterogeneity among banks in terms of credit risk exposure, a second indicator that combines the previous one with the banks’ size, and a third indicator as a measure of interconnectedness between banks.
Leveraged finance; Syndicated loans; Systemic risk; Interconnectedness; Credit risk exposure
Settore ECON-09/A - Finanza aziendale
Settore ECON-09/B - Economia degli intermediari finanziari
Settore STAT-01/A - Statistica
2024
https://www.sciencedirect.com/science/article/pii/S1042443123001580
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/1189104
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