The paper deals with a well-known topic in the literature, namely the reactivity of the credit ratings assigned by large international companies (S&P, Moody’s, Fitch) with respect to the evolution of economic conditions and shows that not all credit rating agencies promptly react to changes in the economic cycle. This analysis brings us back to the discussion on the type of rating philosophy: (1) Through The Cycle (TTC) a TTC rating changes more slowly and reflects a long-term measure (Unconditional); (2) Point in Time (PIT): a PIT rating is more reactive and should reflect a short-term measure of risk (Conditional). This subject has been much discussed in the context of prudential regulation of banks and it has been concluded that a TTC approach is preferable in order to avoid pro-cyclical behavior by banks. From an economic governance point of view the same trade-off among more reactive risk measures and the incentive to pro-cyclical behavior also applies to rating agencies BUT there is no such restrictive regulation for rating agencies as for the banks for which it is legitimate to expect different choices in terms of credit rating philosophy. From this point of view, the paper contributes to providing an approach to understanding the behavior of rating agencies. However, it should be noted that the shock taken into consideration, i.e. the one caused by the pandemic, was rather peculiar in terms of the extent of state interventions in support of the economy and of FED and Central Banks for managing and mitigating credit risk. Be careful when using data from the COVID-19 period: due to state interventions, correlations between risk measures and macro conditions have jumped and from a technical point of view, it would be interesting to include the lagged rating in the regression to study the persistence of the ratings.

discussion-67EWGCFM_paper_5825: Are credit ratings agencies done lesson after 2008 global financial crisis- European and US banks’ credit ratings as a result of covid-19 crisis by Patrycja Chodnicka-Jaworska

Uberti Mariacristina
First
;
2023-01-01

Abstract

The paper deals with a well-known topic in the literature, namely the reactivity of the credit ratings assigned by large international companies (S&P, Moody’s, Fitch) with respect to the evolution of economic conditions and shows that not all credit rating agencies promptly react to changes in the economic cycle. This analysis brings us back to the discussion on the type of rating philosophy: (1) Through The Cycle (TTC) a TTC rating changes more slowly and reflects a long-term measure (Unconditional); (2) Point in Time (PIT): a PIT rating is more reactive and should reflect a short-term measure of risk (Conditional). This subject has been much discussed in the context of prudential regulation of banks and it has been concluded that a TTC approach is preferable in order to avoid pro-cyclical behavior by banks. From an economic governance point of view the same trade-off among more reactive risk measures and the incentive to pro-cyclical behavior also applies to rating agencies BUT there is no such restrictive regulation for rating agencies as for the banks for which it is legitimate to expect different choices in terms of credit rating philosophy. From this point of view, the paper contributes to providing an approach to understanding the behavior of rating agencies. However, it should be noted that the shock taken into consideration, i.e. the one caused by the pandemic, was rather peculiar in terms of the extent of state interventions in support of the economy and of FED and Central Banks for managing and mitigating credit risk. Be careful when using data from the COVID-19 period: due to state interventions, correlations between risk measures and macro conditions have jumped and from a technical point of view, it would be interesting to include the lagged rating in the regression to study the persistence of the ratings.
2023
67th EWGCFM Meeting - Euro Working Group for Commodities and Financial Modelling 67th Meeting
Rome
May 4-6, 2023
The Role of Fintech and Artificial Intelligence in Risk Management and Measurement
1
7
https://www.ewgfm.eu/67th-meeting/
Uberti Mariacristina; Casellina Simone
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1919359
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