Please use this identifier to cite or link to this item:
Title: Asset classification under the IFRS 9 framework for the construction of a banking investment portfolio
Authors: Brito, Rui Pedro 
Júdice, Pedro Maria Corte-Real Alarcão 
Keywords: Asset Classification, Backtesting, IFRS 9, Derivative-Free Optimization, Sensitivity Analysis, Stochastic Simulation
Issue Date: 29-Apr-2020
Series/Report no.: CeBER Working Paper 2020-06;CeBER Working Paper 2020-06
Abstract: In this paper we perform a quantitative analysis, under the IFRS 9 framework, on the tradeoff of classifying a financial asset at amortized cost versus at fair value. We define and implement a banking impairment model in order to quantify the forward-looking expected credit loss. Based on the suggested impairment model we conduct a backtest on the 10-year Portuguese Government bonds, for the time period from January 2003 to December 2019. The Portuguese bonds’ history constitutes a very rich data set for our experiment, as these bonds have experienced significant downgrades during the 2011-2014 financial crisis. We suggest a quantitative and systematic approach in order to find efficient allocations, in an income/downside comprehensive income bi-dimensional space. Resorting to stochastic simulation, we show a possible approach to mitigate the estimation error ingrained in the proposed bi-objective stochastic model. Finally, we assess the out-of-sample performance of some of the suggested efficient allocations.
Rights: openAccess
Appears in Collections:I&D CeBER - Working Papers

Files in This Item:
File Description SizeFormat
wp-ceber-2020-6-1.pdfWorking Paper CeBER1.66 MBAdobe PDFView/Open
Show full item record

Page view(s)

checked on Feb 24, 2021


checked on Feb 24, 2021

Google ScholarTM


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.