dc.contributorCentro de estudios económicos
dc.creatorSarmiento, Camilo
dc.date.accessioned2023-07-21T16:45:58Z
dc.date.accessioned2023-09-06T21:17:39Z
dc.date.available2023-07-21T16:45:58Z
dc.date.available2023-09-06T21:17:39Z
dc.date.created2023-07-21T16:45:58Z
dc.date.issued2020
dc.identifier1350-4851
dc.identifierhttps://repositorio.escuelaing.edu.co/handle/001/2501
dc.identifier1466-4291
dc.identifierEscuela Colombiana de Ingeniería Julio Garavito
dc.identifierRepositorio digital
dc.identifierhttps://repositorio.escuelaing.edu.co
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/8707365
dc.description.abstractThis paper presents a simple method to estimate the collateral associated with a Aaa tranche. The method is similar to historical simulation in the sense that there are no specific distributional assumptions, and the data fully determine the characteristics of the distribution. Both the transparency and simplicity of our method provide a valuable benchmark to existent tail of the distribution modelling. As a benchmark, our method also serves to validate collateral estimates for Aaa-rated securities as well as to validate capitalization models of financial institutions.
dc.description.abstractEste artículo presenta un método simple para estimar la garantía asociada con un tramo Aaa. El método es similar a la simulación histórica en el sentido de que no hay distribuciones específicas supuestos, y los datos determinan completamente las características de la distribución. Ambos La transparencia y la simplicidad de nuestro método proporcionan un punto de referencia valioso para la cola existente del modelado de distribución. Como punto de referencia, nuestro método también sirve para validar estimaciones de garantías para títulos calificados Aaa así como para validar modelos de capitalización de entidades financieras.
dc.languageeng
dc.publisherWashington D.C.
dc.relation558
dc.relation7
dc.relation555
dc.relation27
dc.relationN/A
dc.relationApplied Economics Letters
dc.relationAgarwal, V., and R. Taffler. 2008. “Comparing the Performance of Market-Based and Accounting-Based Bankruptcy Prediction Models.” Journal of Banking & Finance 32 (8): 1541–1551. doi:10.1016/j.jbankfin.2007.07.014
dc.relationBenmelech, E., and J. Dlugosz (2008) “The Alchemy of CDO Credit Ratings.” Harvard University Working paper
dc.relationBharath, S., and T. Shumway. 2007. “Forecasting Default with the Merton Distance to Default Model.” Review of Financial Studies 21: 1339–1369.
dc.relationBoard of Governors of the Federal Reserve System. 2014. “Supervisory Guidance for Data, Modeling, and Model Risk Management under the Operational Risk Advanced Measurement Approaches.” Basel Coordination Committee Bulletin 14.
dc.relationHendricks, D. 1996. “Evaluating Value-at-Risk Models Using Historical Data.” Frbny Economic Policy Review 2 /april 1996.
dc.relationHull, J., and A. White. 1998. “Incorporating Volatility Updating into the Historical Simulation Method for VAR.” Journal of Risk 1: 5–19. doi:10.21314/JOR.1998.001.
dc.relationLopez, J., and M. Saidenberg. 2000. “Evaluating Credit Risk Models.” Journal of Banking & Finance 24: 151–165. doi:10.1016/S0378-4266(99)00055-2.
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.sourceApplied Economics Letters
dc.titleBenchmarking collateral of triple-a rated securities
dc.typeArtículo de revista


Este ítem pertenece a la siguiente institución