eba_impairments_2020: Hypothetical Impairment data of 123 European banks which took...

In Martin-Summer-1090/syslosseval: Provide data and functions to support the analysis in Systemic Loss Evaluation

Description

A dataset containing hypothetical impairment data of 123 European banks who took part in the EBA transparency exercise. The data are postulated with reference to the paper "Rules of Thumb for Bank Solvency Stress Tests" by Daniel C. Hardy and Christian Schmiederer. IMF working paper 13/232 (https://www.imf.org/external/pubs/ft/wp/2013/wp13232.pdf). We use the numbers from table 2 in this paper and the assumption that impairment rates will be 2.4 (severe), 4.3 year after the pandemic. The loss rate in the normal scenario is assumed to be 0.3 script stored in the data-raw folder.

Usage

eba_impairments_2020

Format

A data frame with 32290 rows and 8 variables:

LEI_code

LEI_code, legal entity identifyer of a bank. chr.

Country_code

Country_code, ISO-code of the country where the bank is domiciled, chr.

Bank_name

Bank_name, Name of the bank, chr.

Period

Period, Reporting period of the data given as 201912 (31. December 2019). There are three impairment periods in total. num

Scenario

Scenario, reports whether it is the baseline or the stress scenario, chr

Country

Country, Country to which the bank is exposed. This is either a ISO code like AT, DE etc. or it is called Total if it is the overall exposure aggregated across all countries, or there are special abbreviations which are further explained in the EBA metadata in the raw-data folder. They are not relevant for our analysis and not described further here. chr

Exposure

Asset class according to the IRB classification scheme. chr

Impairment_rate

Impairment_rate, the Impairment rate in percentage according to Hardy and Schmieder 2013. num

Source

https://www.eba.europa.eu/risk-analysis-and-data/eu-wide-transparency-exercise

Martin-Summer-1090/syslosseval documentation built on Dec. 17, 2021, 3:14 a.m.