Relevance of loan characteristics in probability of default prediction for commercial mortgage loans

2019 ◽  
Author(s):  
Nicole Lux
Keyword(s):  
Probability Of Default ◽  
Mortgage Loans ◽  
Default Prediction

scholarly journals Empirics of Korean Shipping Companies’ Default Predictions

Risks ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 159
Author(s):  
Sunghwa Park ◽  
Hyunsok Kim ◽  
Janghan Kwon ◽  
Taeil Kim
Keyword(s):  
Logit Model ◽  
Prediction Models ◽  
Predictive Ability ◽  
Financial Ratios ◽  
Probability Of Default ◽  
Shipping Industry ◽  
Market Participants ◽  
Korean Economy ◽  
Default Prediction ◽  
Financial Characteristics

In this paper, we use a logit model to predict the probability of default for Korean shipping companies. We explore numerous financial ratios to find predictors of a shipping firm’s failure and construct four default prediction models. The results suggest that a model with industry specific indicators outperforms other models in predictive ability. This finding indicates that utilizing information about unique financial characteristics of the shipping industry may enhance the performance of default prediction models. Given the importance of the shipping industry in the Korean economy, this study can benefit both policymakers and market participants.

Effect of the Spread on Housing Mortgage Loans

2018 ◽  
Vol 28 (4) ◽  
pp. 75-88
Author(s):  
Woo Seok Kim
Keyword(s):  
Mortgage Loans

The effect of imperfect data on default prediction validation tests

2012 ◽  
Vol 6 (1) ◽  
pp. 77-96 ◽  
Author(s):  
Heather Russell ◽  
Douglas Dwyer ◽  
Qing Kang Tang
Keyword(s):  
Imperfect Data ◽  
Default Prediction ◽  
Validation Tests
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