A model proposal for IFRS 16 IBR adjustment based on bond market pricing
The Incremental Borrowing Rate (IBR) is generally used by companies for discounting future lease payments and calculating the value of the lease assets and liabilities under IFRS 16. According to this standard, leased asset must be considered as a collateral, and therefore the yield to be used shoul...
| Autores: | , , |
|---|---|
| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2023 |
| País: | España |
| Institución: | Universidad de Sevilla (US) |
| Repositorio: | idUS. Depósito de Investigación de la Universidad de Sevilla |
| OAI Identifier: | oai:idus.us.es:11441/146675 |
| Acceso en línea: | https://hdl.handle.net/11441/146675 https://doi.org/10.1080/1331677X.2022.2106273 |
| Access Level: | acceso abierto |
| Palabra clave: | IFRS 16 Incremental Borrowing Rate (IBR) Loss Given Default (LGD) Yield-to-Maturity (YTM) Bond pricing |
| Sumario: | The Incremental Borrowing Rate (IBR) is generally used by companies for discounting future lease payments and calculating the value of the lease assets and liabilities under IFRS 16. According to this standard, leased asset must be considered as a collateral, and therefore the yield to be used should reflect an adequate Loss-Given Default (LGD), which may vary depending on the estimated recovery rate of the asset (machinery, real estate, vehicles, etc.). There is a lack of accounting and finance literature focused on analysing how a standard IBR should be adjusted to reflect the expected underlying asset LGD in line with IFRS principles. In this context, we propose a model that uses bond quoted information as a basis for introducing an adjustment to the standard “unsecured” IBR. The model consists of replicating the change in a certain bond yield when there is a change in the LGD (usually due to a change in the seniority level). We empirically demonstrate that the model works by using data from real bond quotations (97 outstanding bonds quoted on several secondary markets such as NY, Vienna, Frankfurt and London). The empirical analysis has been performed for two different time periods: pre-COVID 19 and post-COVID 19. |
|---|