Abstract
The rate of default is a measure of the credit risk of a portfolio of loans and is generally considered confidential information. However, the inferred rate of default, (IRD) is an estimate based on publicly reported information. We use the Bulgarian National Bank’s quarterly reports on the credit quality to measure IRD for the major bank groups in Bulgaria. Our estimation is based on current regulations enforcing the IFRS 9 accounting standard in the Bulgarian bank system. Furthermore, focusing on banks of Group 2, we suggest an original methodology for forecasting IRD based on macroeconomic indicators. We report and compare the result of two approaches of estimation: a hybrid ARIMA regression, and an Asymptotic Single Risk Factor model of the Vasicek–Merton type. The general conclusion is that IRD resembles the known characteristics of the confidential rate of default and can be useful for credit risk analysis. In addition, it has the advantage of allowing estimation based on stale financial information and fresh macroeconomic forecasts in an intuitive and manageable way.
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Notes
- 1.
In 2019, with the oncoming of the COVID-2019 pandemic, the Bulgarian government introduced a series of measures that gave the banks the option to postpone the recognition of failing loans as “defaulted”. This has had the effect of “smoothing”, the rates of default, and inferred rates of default during that period. To avoid contamination, we have omitted from consideration all data after December 31, 2019.
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Acknowledgements
This work was supported by UNWE Research Program (Research Grant Nrs. NID NI-17/2021 and NID NI-11/2022).
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Boutchaktchiev, V. (2023). Models for Measuring and Forecasting the Inferred Rate of Default. In: Slavova, A. (eds) New Trends in the Applications of Differential Equations in Sciences. NTADES 2022. Springer Proceedings in Mathematics & Statistics, vol 412. Springer, Cham. https://doi.org/10.1007/978-3-031-21484-4_31
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