Extreme loss risk in financial turbulence – evidence from the global financial crisis

Purpose – This study aims to examine the stock returns distributions in ten countries in the periods before and after the global financial crisis (GFC) to evaluate how well the empirical distributions conformed to the extreme value theory (EVT) which underlies a family of risk management models. Design/methodology/approach – The authors’ sample consists of the G5 countries and the five leading emerging economies. Parameters of the General Pareto Distribution (GPD) for each country are estimated for the pre‐ and the crisis period. The authors follow a two‐step procedure: a GARCH(1,1) model is fitted to the historical return data by pseudo maximum likelihood method; Hill's GPD tail estimation procedure is employed on the residuals from the first step. Goodness‐of‐fit is evaluated for the empirical distributions. Findings – The authors find that the EVT explains the observed distributions well in both the pre‐GFC and the GFC periods, with the important exceptions of the US and the UK markets in the crisis period. Moreover, the estimated distribution parameters are quite different for the two periods. The results underscore the inadequacy of the quantitative risk models in times of financial turbulence, and the need for prudential exercise of judgment in risk management. Originality/value – The global financial crisis (GFC) provides a unique and historical experiment to evaluate the models of tail distributions. Although the EVT provides a sound basis for modeling extreme risks, the study highlights the fundamental problem of dealing with uncertainty.