[Statlist] Research Seminar in Statistics *FRIDAY 9 DECEMBER 2022* GSEM, University of Geneva

[gsem-support-instituts]

Dear All,

We are pleased to invite you to our next Research Seminar.

Looking forward to seeing you,


Organized by Professor Sebastian Engelke on behalf of the Research Center for Statistics (https://www.unige.ch/gsem/en/research/institutes/rcs/)


FRIDAY 9 DECEMBER 2022 at 11:15am, Uni-Mail M 5220 & ONLINE
Zoom research webinar: https://unige.zoom.us/j/92924332087?pwd=U1U1NFk4dTFCRHBMeWYrSDBQcXBiQT09
Meeting ID: 929 2433 2087
Passcode: 399192

Treatment of COVID-19 Recession in Italian Default Rate Projection Model
Ottavia TELVE, Intesa Sanpaulo, Italy
https://it.linkedin.com/in/ottavia-telve-1a182247?original_referer=

ABSTRACT:
Since the onset of the COVID-19 recession, stress testing models have dramatically overpredicted losses. It is not a surprise: all models are trained on past events, but no pattern exists in current industry training data for an equivalent combination of natural disaster, government assistance and loan forbearance as it has happened in 2020 due to COVID-19.

The methodology put in place before the COVID-19 recession is not adequate for describing the link between macro-economic scenarios and the evolution of default rates anymore. The latter applies especially in the Italian system, where the severity of the crisis (in terms of, for example, GDP reduction and unemployment increment) was strongly mitigated with various measures adopted by governments, institutions, and central bank. These actions were adopted to support the economy; hence they did not reveal in an expected increase in company defaults.

In this talk, we show an improved version of the classic Error Correction Model used for the Italian default rates projection before 2020. It will be tested to consider the different behavior between Italian GDP and default rate due to the government measures before and after the pandemic. We illustrate an Italian default rate projection model for Banking Sector, specifically estimated on the 2005Q3-2021Q4 period and with a forecast for the 2022Q1-2023Q4 period, where two different scenarios will be presented.


Visit the website: https://www.unige.ch/gsem/en/research/seminars/rcs/