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Credit risk is a critical issue that affects banks and companies on a global scale. Possessing the ability to accurately predict the level of credit risk has the potential to help the lender and borrower. This is achieved by alleviating the number of loans provided to borrowers with poor...
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The recovery rate on defaulted corporate bonds has a time-varying distribution. We propose machine learning approaches for intertemporal analysis of U.S. corporate bonds' recovery rates with a large number of predictors. The most informative macroeconomic variables are selected from a broad...
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The COVID-19 crisis has revealed the economic vulnerability of various countries and, thus, has instigated the systematic exploration and forecasting of sovereign default risks. Multivariate statistical and stochastic process-based sovereign default risk forecasting has a 50-year developmental...
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