The Breaking Point Behavioural Drivers & Organisational Dynamics of Abandoning Value at Risk (VaR) During Financial Crises: A Comparative Study: GFC 2008 & COVID-19 2020

Value-at-Risk (VaR) has been the primary tool for market risk analysis since the 1990s. However, during the Global Financial Crisis of 2008 and the economic recession caused by COVID-19 in March 2020, financial organizations had to abandon or deactivate their use in a relatively short period. Previous studies mainly explain such situations through failure of the underlying statistical models used or dynamics of the process of crisis escalation; therefore, the process behind model abandonment remains understudied in the field of behavioral and organizational theory. The current study will uncover behavioral and organizational determinants driving the decision to abandon VaR constraints in times of financial crises and make a comparison between these determinants in 2008 and 2020 to see if there is any structural phenomenon underlying the process of model abandonment in times of financial crises, or if it is a crisis-specific contingency. For the purpose of the study, there will be a comparative case analysis of two crises, supplemented by the relevant literature and a survey of 19 individuals on their trust in models and human judgment in times of tranquility and crises. In fact, the same mechanism has governed the abandonment of VaR constraints in times of the two crises despite different initial conditions (internally induced leverage excess in 2008 and exogenous shock in 2020): failure of the governance system, delayed escalation, and manual overrides. The latter is confirmed by the results of the survey, where the trust in the accuracy of the model fell from 52.6% in calm markets to only 5.3% during the crisis, and most of the participants depended on expert judgment rather than models. Thus, model abandonment in times of crises can be regarded as a structural phenomenon from the point of view of behavioral and organizational theory.

Value-at-Risk, financial crises, model risk, algorithm aversion, risk governance

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