Scenario design for macrofinancial stress testing

Abstract

This paper provides a novel empirical approach to scenario design for selecting a stress scenario for international macrofinancial variables. The scenario design framework is composed of several building blocks. First, multiple scenarios on the risk factors are generated by simulating a multi-country large Bayesian vector autoregression. Second, we take the perspective of a representative investor who aims to select a severe-yet-plausible scenario for a set of systematic risk factors following a factor-investing strategy. Moreover, we compare the stress scenarios selected under different approaches to measure plausibility (the Mahalanobis distance and entropy pooling under subjective views with a clear economic narrative). Finally, we compare our scenario design approach with a historical scenario approach in terms of its ability to select a stress scenario in the run-up to a rare adverse event such as the Covid-19 pandemic. We give evidence that our framework is suitable for the selection of a proper forward-looking severe-yet-plausible macrofinancial stress scenario.