Role of Comprehensive Income in Predicting Bankruptcy

Asyrofa Rahmi, Hung Yuan Lu, Deron Liang, Dinda Novitasari, Chih Fong Tsai

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


This study examines the role of comprehensive income and its components, in addition to net income, as inputs to forecast bankruptcy. Using a matched sample of 466 (233 pairs) U.S. bankrupt and non-bankrupt firms from 1993 to 2014, we build a bankruptcy prediction model using random forest classification. Compared with the benchmark model, our proposed model’s accuracy increases by 1.5% and the Type I error decreases by up to 3%. A variable importance analysis reveals that comprehensive income is consistently the most useful variable for bankruptcy prediction. A variable interaction analysis shows that the top interaction pair includes one Altman variable and comprehensive income. Finally, we analyze bankrupt firms that our model identifies but the benchmark model misclassifies; we find that such firm’ other comprehensive income is consistently negative, suggesting that firms’ macroeconomic risk exposure plays a key role in bankruptcy prediction.

Original languageEnglish
Pages (from-to)689-720
Number of pages32
JournalComputational Economics
Issue number2
StatePublished - Aug 2023


  • Altman variables
  • Bankruptcy
  • Comprehensive income
  • Forecasting


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