A new approach for credit scoring by directly maximizing the Kolmogorov-Smirnov statistic

DOI10.1016/j.csda.2018.10.004OpenAlexW2896798207MaRDI QIDQ1727903

Xianqiang Yang

Publication date: 21 February 2019

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2018.10.004

zbMATH Keywords

isotonic regressioncredit scoringKolmogorov-Smirnov statisticIMO algorithm

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Applications of statistics to actuarial sciences and financial mathematics (62P05) Credit risk (91G40)

Related Items (2)

Model averaging prediction by \(K\)-fold cross-validation ⋮ Prediction Using Many Samples with Models Possibly Containing Partially Shared Parameters

Uses Software

• isotone

Cites Work

• A note on iterative marginal optimization: a simple algorithm for maximum rank correlation estimation
• The effect of link misspecification on binary regression inference
• Rank estimators for monotonic index models
• Regression analysis under link violation
• Recent developments in consumer credit risk assessment
• Benchmarking state-of-the-art classification algorithms for credit scoring
• Minimum Kolmogorov–Smirnov test statistic parameter estimates
• Good practice in retail credit scorecard assessment
• Maximum Likelihood Estimation of Misspecified Models

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