Forecasting for regulatory credit loss derived from the COVID-19 pandemic: A machine learning approach
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DOI: 10.1016/j.ribaf.2023.101907
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More about this item
Keywords
Machine learning; COVID-19; Internal-rating-based; Credit risk; Defaulted exposures;All these keywords.
JEL classification:
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
- D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
- G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
- G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation
- G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
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