Verlag:
European Central Bank, Frankfurt am Main, Germany
We test whether a simple measure of corporate insolvency based on equity return volatility - and denoted as Distance to Insolvency (DI) - delivers better predictions of corporate default than the widely-used Expected Default Frequency (EDF) measure...
mehr
ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
Signatur:
DS 534
Fernleihe:
keine Fernleihe
We test whether a simple measure of corporate insolvency based on equity return volatility - and denoted as Distance to Insolvency (DI) - delivers better predictions of corporate default than the widely-used Expected Default Frequency (EDF) measure computed by Moody's. We look at the predictive power that current DIs and EDFs have for future defaults, both at a firm-level and at an aggregate level. At the granular level, both DIs and EDFs anticipate corporate defaults, but the DI contains information over and above the EDF, especially at longer forecasting horizons. At an aggregate level the DI shows superior forecasting power compared to the EDF, for horizons between 3 and 12 months. We illustrate the predictive power of the DI measure for the aggregate default rate by examining how corporate defaults would have evolved during the period marked by the spreading of the COVID-19 pandemic had the ECB not implemented the pandemic emergency purchase programme (PEPP).
