Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/278224 
Year of Publication: 
2022
Series/Report no.: 
ECB Working Paper No. 2749
Publisher: 
European Central Bank (ECB), Frankfurt a. M.
Abstract: 
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).
Subjects: 
default probability
equity volatility
distance to insolvency
expected default frequency
JEL: 
C53
C58
G33
Persistent Identifier of the first edition: 
ISBN: 
978-92-899-5397-9
Document Type: 
Working Paper

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