Lee, David (2023): Default Forecasting and Credit Valuation Adjustment.
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Abstract
Credit valuation adjustment has acquired a great deal of attention from both theoreticians and practitioners in recent years. This paper presents a model for default forecasting and credit valuation adjustment. The model links distance-to-default, default probability, survival probability, default correlation, and risky valuation together. It captures default risk, credit migration, and wrong way risk simultaneously and naturally. The numerical study shows that the model implied credit spreads and default correlations are very close to the market observed ones, indicating that the model performs quite well. The results may be of interest to regulators, academics, and practitioners.
Item Type: | MPRA Paper |
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Original Title: | Default Forecasting and Credit Valuation Adjustment |
English Title: | Default Forecasting and Credit Valuation Adjustment |
Language: | English |
Keywords: | credit value adjustment (CVA), credit risk modeling, distance to default, default probability, survival probability, asset pricing involving credit risk. |
Subjects: | C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C15 - Statistical Simulation Methods: General C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C53 - Forecasting and Prediction Methods ; Simulation Methods E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles > E37 - Forecasting and Simulation: Models and Applications G - Financial Economics > G1 - General Financial Markets > G12 - Asset Pricing ; Trading Volume ; Bond Interest Rates G - Financial Economics > G1 - General Financial Markets > G13 - Contingent Pricing ; Futures Pricing G - Financial Economics > G1 - General Financial Markets > G17 - Financial Forecasting and Simulation G - Financial Economics > G2 - Financial Institutions and Services > G24 - Investment Banking ; Venture Capital ; Brokerage ; Ratings and Ratings Agencies |
Item ID: | 118578 |
Depositing User: | David Lee |
Date Deposited: | 13 Sep 2023 13:49 |
Last Modified: | 13 Sep 2023 13:50 |
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URI: | https://mpra.ub.uni-muenchen.de/id/eprint/118578 |