Impacts of crisis on SME bankruptcy prediction models' performance

被引:21
|
作者
Papik, Mario [1 ]
Papikova, Lenka [1 ]
机构
[1] Comenius Univ, Fac Management, Odbojarov 10,POBox 95, Bratislava 82005, Slovakia
关键词
Bankruptcy model; Accounting information; Crisis; Data mining; Gradient boosting; COVID-19; Prediction; FINANCIAL DISTRESS; DEFAULT PREDICTION; FEATURE-SELECTION; BUSINESS FAILURE; RATIOS;
D O I
10.1016/j.eswa.2022.119072
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Turbulent economic situation, changes in financial reporting, swift legislative changes, or companies' earnings management during the COVID-19 crisis might have impacted the performance of SME bankruptcy prediction models. Due to these circumstances, the performance of existing bankruptcy prediction models might have worsened. The main aim of this study is to analyse the impact of the crisis on the performance of bankruptcy prediction models. Data from 2015 to 2019 was collected for more than 90 000 SMEs to develop prediction models for three periods - two non-crisis periods and one crisis period. One-year, two-year and three-year predictions were made for these three periods via CatBoost, LightGBM and XGBoost methods. The results of this manuscript indicate that the performance of prediction models was significantly weaker during crisis periods than the performance during non-crisis periods. The weaker performance was the most evident for one-year predictions (6.5%). The difference was slightly lower for two-year predictions (4.8%) and three-year pre-dictions (4.1%). Since lower sensitivity levels caused worse performance during crisis periods, it can be assumed that these bankruptcies were unexpected and most probably caused by the crisis. Once the COVID-19 crisis is over, existing bankruptcy models will need to be revalidated and recalibrated.
引用
收藏
页数:17
相关论文
共 50 条
  • [41] SELECTION OF PREDICTORS IN BANKRUPTCY PREDICTION MODELS FOR SLOVAK COMPANIES
    Svabova, Lucia
    Kral, Pavol
    10TH INTERNATIONAL DAYS OF STATISTICS AND ECONOMICS, 2016, : 1759 - 1768
  • [42] PREDICTION BANKRUPTCY MODELS VALIDATION IN SLOVAK BUSINESS ENVIRONMENT
    Delina, Radoslav
    Packova, Miroslava
    E & M EKONOMIE A MANAGEMENT, 2013, 16 (03): : 101 - 112
  • [43] ARE BANKRUPTCY PREDICTION MODELS WORTHWHILE - AN APPLICATION IN SECURITIES ANALYSIS
    ZAVGREN, CV
    FRIEDMAN, GE
    MANAGEMENT INTERNATIONAL REVIEW, 1988, 28 (01) : 34 - 44
  • [44] AdaBoost Models for Corporate Bankruptcy Prediction with Missing Data
    Ligang Zhou
    Kin Keung Lai
    Computational Economics, 2017, 50 : 69 - 94
  • [45] IMPACT OF FINANCIAL RATIOS ON INTERNATIONAL BANKRUPTCY PREDICTION MODELS
    Svabova, Lucia
    Kramarova, Katarina
    Valaskova, Katarina
    GLOBALIZATION AND ITS SOCIO-ECONOMIC CONSEQUENCES, 2018, : 1863 - 1870
  • [46] The development of bankruptcy prediction models in modern Russian economy
    Kazakov, A. V.
    Kolyshkin, A. V.
    VESTNIK SANKT-PETERBURGSKOGO UNIVERSITETA-EKONOMIKA-ST PETERSBURG UNIVERSITY JOURNAL OF ECONOMIC STUDIES, 2018, 34 (02): : 241 - 266
  • [47] THE RESEARCH OF RELIABILITY OF BANKRUPTCY PREDICTION MODELS IN LITHUANIAN COMPANIES
    Krusinskas, Rytis
    Lakstutiene, Ausrine
    Stankeviciene, Jurgita
    TRANSFORMATIONS IN BUSINESS & ECONOMICS, 2014, 13 (02): : 102 - 123
  • [48] Improving the bankruptcy prediction by combining some classification models
    Tran Duc Quynh
    Tran Thi Lan Phuong
    2020 12TH INTERNATIONAL CONFERENCE ON KNOWLEDGE AND SYSTEMS ENGINEERING (IEEE KSE 2020), 2020, : 263 - 268
  • [49] BANKRUPTCY PREDICTION - AN INVESTIGATION OF CASH FLOW BASED MODELS
    AZIZ, A
    EMANUEL, DC
    LAWSON, GH
    JOURNAL OF MANAGEMENT STUDIES, 1988, 25 (05) : 419 - 437
  • [50] The Prediction Ability of New Bankruptcy Models in National Environment
    Kubickova, Dana
    Nulicek, Vladimir
    HRADEC ECONOMIC DAYS, VOL. 9, ISSUE I, 2019, 9 : 499 - 508