The accuracy of alternative supervisory methodologies for the stress testing of credit risk. (8th June 2020)

• Record Type: Journal Article
• Authors: Jacobs, Michael
• Is Part Of: International journal of financial engineering and risk management. Volume 3:Number 3(2020)
• Page Start: 254
• Page End: 296
• Publication Date: 2020-06-08
• Subjects: stress testing -- Comprehensive Capital Analysis and Review -- CCAR -- Dodd-Frank Act Stress Tests -- DFAST -- credit risk -- financial crisis -- model risk -- capital adequacy -- income before taxes -- extraordinary items; Financial engineering -- Periodicals; Finance -- Mathematical models -- Periodicals; 332
• Languages: English
• ISSNs: 2049-0909

Abstract

Following the financial crisis approaches such as regulatory capital ratios have been supplanted by stress testing as a primary tool for managing systemic risks. Financial institutions are mandated to perform stress testing to forecast performance over stress scenarios. While in parallel supervisors conduct their tress tests to set minimum regulatory capital, nothing is revealed regarding the accuracy of such models. We investigate a modelling framework rather close to that of the regulators, projecting financial statement line items for an aggregated 'average' bank. We assess the accuracy of alternative stress testing models, simple single equation versus complex multiple equation approaches. Results show inaccuracies in stress test model forecasts for multi-equation models that do not account for the dependency structure amongst the model variables. This highlights the public policy need for reconsidering the existent regulatory stress tests, and the need for supervisory models to be subject to model validation standards.