CORPORATE DEFAULT PREDICTION MODEL AVERAGING: A NORMATIVE LINEAR POOLING APPROACH

被引：12

作者：

Figini, Silvia ^{[1
]}

Savona, Roberto ^{[2
]}

Vezzoli, Marika ^{[3
]}

机构：

[1] Univ Pavia, Dept Polit & Social Sci, Pavia, Italy

[2] Univ Brescia, Dept Econ & Management, Brescia, Italy

[3] Univ Brescia, Dept Mol & Translat Med, Brescia, Italy

来源：

INTELLIGENT SYSTEMS IN ACCOUNTING FINANCE & MANAGEMENT | 2016年 / 23卷 / 1-2期

关键词：

AUC; competitive models; dominant models; ensemble models; model averaging;

D O I：

10.1002/isaf.1387

中图分类号：

F8 [财政、金融];

学科分类号：

0202 ;

摘要：

Focusing on credit risk modelling, this paper introduces a novel approach for ensemble modelling based on a normative linear pooling. Models are first classified as dominant and competitive, and the pooling is run using the competitive models only. Numerical experiments based on parametric (logit, Bayesian model averaging) and non-parametric (classification tree, random forest, bagging, boosting) model comparison shows that the proposed ensemble performs better than alternative approaches, in particular when different modelling cultures are mixed together (logit and classification tree). Copyright (C) 2016 John Wiley & Sons, Ltd.

引用

页码：6 / 20

页数：15

共 47 条

[1] CREDIT SCORING, STATISTICAL TECHNIQUES AND EVALUATION CRITERIA: A REVIEW OF THE LITERATURE [J].