Updating Bankruptcy Forecast Using Higher Frequency Data

This paper suggests ways of improving bankruptcy forecast by supplementing outdated financial variables of a lower frequency with readily available macro variables of a higher frequency. We empirically show that our suggested framework performs better in forecasting corporate default for medium sized firms in Korea. Financial institutions and regulatory authorities may use our framework to monitor expected losses on loan portfolios more accurately and more up to date.