Reassessing bank monitoring models: an empirical analysis of the value of market signals in the period 2008–2020

One of the major goals of bank supervisors is to predict bank distress events. As the environment changes, it is crucial to reassess and improve the models used in monitoring banks. The financial soundness of banks is traditionally assessed based on accounting ratios. However, the incorporation of market information in these models may significantly improve its ability to predict bank distress. The present paper has two main objectives, the first is to assess if market information adds value to accounting-based monitoring models when the purpose is to detect bank distress situations. Further, it also seeks to understand if the predictive power of market signals increased with transparency requirements. To accomplish this purpose, a total of 81 distress events from a sample of 248 European banks between 2008 and 2020 were analyzed. First, a logit univariate analysis was used to evaluate the relevance of each accounting and market variable. Then, the optimal multivariate accounting-based model to predict distress events was constructed using a stepwise approach. Finally, the previous model was extended to include the relevant market variables. The results support the use of market variables in bank monitoring models. Further, the present study provides evidence that the predictive power of market variables increased after the strengthening of the information requirements set by the Basel agreements. It can be concluded that the results support the use of market information for banking supervisory purposes, especially, in transparent markets.