Predicting financial stress events: A signal extraction approach

• Based on the signal extraction approach proposed, this paper proposes an early warning system to predict the likelihood of the occurrence of financial stress events.
• We propose three different composite indicators, the summed composite indicator, the extreme composite indicator and the weighted composite indicator.
• The out-of-sample results suggest that for most of the 13 OECD countries, the weighted composite indicator performs better than the two others across all the criteria considered.

The objective of this paper is to propose an early warning system that can predict the likelihood of the occurrence of financial stress events within a given period of time. To achieve this goal, the signal extraction approach proposed by Kaminsky et al. (1998) is used to monitor the evolution of a number of economic indicators that tend to exhibit unusual behavior in the periods preceding a financial stress event. Based on the individual indicators from 13 OECD countries, we propose three different composite indicators, the summed composite indicator, the extreme composite indicator and the weighted composite indicator. The in-sample forecasting results for the 13 OECD countries indicate that the three composite indicators are useful tools for predicting financial stress events, while none of them outperforms the others across all the criteria considered. The out-of-sample forecasting results suggest that for most of the 13 OECD countries, including Canada, the United Kingdom and the United States, the weighted composite indicator performs better than the two others across all the criteria considered.