Measuring the Impact of Transition Risk on Financial Markets: A Joint VaR‐ES Approach

ABSTRACT Based on a joint quantile and expected shortfall semiparametric methodology, we propose a novel approach to forecasting market risk conditioned to transition risk exposure. This method allows us to forecast two climate‐related financial risk measures called and , being jointly elicitable, that capture the dependence of the European extreme bank returns on changes in carbon returns at extreme quantiles representing green and brown states. We evaluate our approach using a novel backtesting procedure and introduce related measures ( and ). The main evidence states that the measure presents the highest risk for the brown (green) state due to the presence of carbon cost (carbon risk premium) in Ph.II (Ph.III) of the EU Emissions Trading System. Furthermore, we found the highest (lowest) financial risk forecasts for in green (brown) states during COVID‐19. These results offer important implications for investors and policymakers regarding the effects of transition risk on the European financial system.