Abstract:
This paper develops a framework for assessing systemic risks and for predicting (out-of-sample) systemic events, i.e. periods of extreme financial instability with potential real costs. We test the ability of a wide range of stand alone. and composite indicators in predicting systemic events and evaluate them by taking into account policy makers f preferences between false alarms and missing signals. Our results highlight the importance of considering jointly various indicators in a multiva-riate framework. We find that taking into account jointly domestic and global macro-financial vul-nerabilities greatly improves the performance of discrete choice models in forecasting systemic events. Our framework shows a good out-of-sample performance in predicting the last financial cri-sis. Finally, our model would have issued an early warning signal for the United States in 2006Q2, 5 quarters before the emergence of money markets tensions in August 2007.