抄録
Accurate estimation of loss given default is necessary to estimating credit risk. Due to the bi-modal nature of LGD, the two-step LGD estimation model is a promising method for LGD estimation. This study improves the first model in the two-step LGD estimation model using probability machines (random forest, k-nearest neighbors, bagged nearest neighbors, and support vector machines). Furthermore, we compare the predictive performance of each model with traditional logistic regression models. This study confirms that random forest is the best model for developing the first model in the two-step LGD estimation model.
| 本文言語 | English |
|---|---|
| ページ（範囲） | 155-177 |
| ページ数 | 23 |
| ジャーナル | Risk Management |
| 巻 | 22 |
| 号 | 3 |
| DOI | |
| 出版ステータス | Published - 2020 9月 1 |
| 外部発表 | はい |
ASJC Scopus subject areas
- ビジネスおよび国際経営
- 財務
- 経済学、計量経済学
- 戦略と経営