Comparing the Performance of Corporate Bankruptcy Prediction Models Based on Imbalanced Financial Data

被引:4
|
作者
Noh, Seol-Hyun [1 ]
机构
[1] Anyang Univ, Dept Stat Data Sci, ICT Convergence Engn, Anyang 14028, South Korea
关键词
corporate bankruptcy; bankruptcy prediction; performance comparison; imbalanced financial data;
D O I
10.3390/su15064794
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Forecasts of corporate defaults are used in various fields across the economy. Several recent studies attempt to forecast corporate bankruptcy using various machine learning techniques. We collected financial information on 13 variables of 1020 companies listed on the KOSPI and KOSDAQ to capture the possibility of corporate bankruptcy. We propose a data processing method for small-sample domestic corporate financial data. We investigate the case of random sampling of non-bankrupt companies versus sampling non-bankrupt companies based on approximate entropy and optimized threshold based on AUC to address the imbalance between the number of bankrupt companies and the number of non-bankrupt companies. We compare the performance measures of corporate bankruptcy prediction models for the small sample data structured in two ways and the full dataset. The experimental results of this study contribute to the selection of an appropriate corporate bankruptcy prediction model.
引用
收藏
页数:17
相关论文
共 50 条
  • [1] Performance of corporate bankruptcy prediction models on imbalanced dataset: The effect of sampling methods
    Zhou, Ligang
    [J]. KNOWLEDGE-BASED SYSTEMS, 2013, 41 : 16 - 25
  • [2] AdaBoost Models for Corporate Bankruptcy Prediction with Missing Data
    Ligang Zhou
    Kin Keung Lai
    [J]. Computational Economics, 2017, 50 : 69 - 94
  • [3] AdaBoost Models for Corporate Bankruptcy Prediction with Missing Data
    Zhou, Ligang
    Lai, Kin Keung
    [J]. COMPUTATIONAL ECONOMICS, 2017, 50 (01) : 69 - 94
  • [4] Comparing the performance of market-based and accounting-based bankruptcy prediction models
    Agarwal, Vineet
    Taffler, Richard
    [J]. JOURNAL OF BANKING & FINANCE, 2008, 32 (08) : 1541 - 1551
  • [5] Bankruptcy prediction using optimal ensemble models under balanced and imbalanced data
    Amirshahi, Bahareh
    Lahmiri, Salim
    [J]. EXPERT SYSTEMS, 2024, 41 (08)
  • [6] Dissimilarity-Based Linear Models for Corporate Bankruptcy Prediction
    Garcia, Vicente
    Marques, Ana I.
    Salvador Sanchez, J.
    Ochoa-Dominguez, Humberto J.
    [J]. COMPUTATIONAL ECONOMICS, 2019, 53 (03) : 1019 - 1031
  • [7] Dissimilarity-Based Linear Models for Corporate Bankruptcy Prediction
    Vicente García
    Ana I. Marqués
    J. Salvador Sánchez
    Humberto J. Ochoa-Domínguez
    [J]. Computational Economics, 2019, 53 : 1019 - 1031
  • [8] Consumer Bankruptcy Prediction Using Balanced and Imbalanced Data
    Brygala, Magdalena
    [J]. RISKS, 2022, 10 (02)
  • [9] FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND PREDICTION OF CORPORATE BANKRUPTCY
    ALTMAN, EI
    [J]. JOURNAL OF FINANCE, 1968, 23 (04): : 589 - 609
  • [10] Financial ratios and prediction on corporate bankruptcy in the Atlantic salmon industry
    Misund, Bard
    [J]. AQUACULTURE ECONOMICS & MANAGEMENT, 2017, 21 (02) : 241 - 260