Abstract
Orientation Market events during the coronavirus disease 2019 (COVID-19) pandemic exposed flaws in the econometric models used to derive International Financial Reporting Standards (IFRS) 9 impairments. Models were unable to capture the level of government intervention or predict the economic recovery process because of the unprecedented nature of the pandemic.Research purpose This study examines the causes of the challenges experienced with the IFRS 9 models during the pandemic and approaches to minimise this risk in the future.Motivation for the study Structural correlation breaks forced banks to replace the IFRS 9 models with expert overlays or rapidly rebuild the models to reduce impairment volatility and manage the impact on earnings. Expert judgement may lead to biased outcomes.Research approach/design and method Behavioural finance theory suggests that emotion and cognitive biases often lead to irrational investment decisions with disastrous consequences to the market. The link between market sentiment and economic outcomes is tested with natural language processing. Archimedean copulas are used to compare the dependence structures of market variables between different stress periods.Main findings Market sentiment is closely related to the trends observed in major macroeconomic indicators. The nature of the dependence structures differs between stress periods.Practical/managerial implications Sentiment may be a valuable exogenous variable to incorporate into economic forecast models. Learnings from one stress period are not necessarily applicable to another.Contribution/value-add Government intervention and market sentiment had a significant impact on the economic outcomes and correlation breaks observed during the pandemic. Developing bespoke models for the different phases of the economic cycle may not necessarily lead to improved outcomes.