Forecasting Bankruptcy More Accurately: A Simple Hazard Model

2001/01/01 by Tyler Shumway · 2,510 citations
Business, Management and Accounting · Chemistry · Economics, Econometrics and Finance · #Actuarial science #Banking stability, regulation, efficiency #Bankruptcy #Bankruptcy prediction #Chemistry #Computer science #Corporate Finance and Governance #Credit Risk and Financial Regulations #Econometrics #Economics #Finance #Hazard #Philosophy #Simple (philosophy)

paper · doi:10.1086/209665

published in The Journal of Business 74(1), 101-124 (University of Chicago Press)

openalex publication_date 2001/01/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05

Abstract

I argue that hazard models are more appropriate than single-period models for forecasting bankruptcy. Single-period models are inconsistent, while hazard models produce consistent estimates. I describe a simple technique for estimating a discrete-time hazard model. I find that about half of the accounting ratios that have been used in previous models are not statistically significant. Moreover, market size, past stock returns, and idiosyncratic returns variability are all strongly related to bankruptcy. I propose a model that uses both accounting ratios and market-driven variables to produce out-of-sample forecasts that are more accurate than those of alternative models. Copyright 2001 by University of Chicago Press.

Cited by

• The Effects of Cultural Values on Bank Failures around the World
• The Politics of Bank Failures: Evidence from Emerging Markets
• Does Other Comprehensive Income Volatility Influence Credit Risk and the Cost of Debt?
• Finance Capitalism and Germany's Rise to Industrial Power
• Auditor‐in‐Charge Characteristics and Going‐concern Reporting
• Contagion without deposit insurance: The South African small bank crisis of 2002/3
• Predicting Distresses using Deep Learning of Text Segments in Annual Reports
• Customer concentration risk and the cost of equity capital
• Does corporate social responsibility reduce financial distress risk?
• Risk management, firm reputation, and the impact of successful cyberattacks on target firms
• Disentangling and Assessing Uncertainties in Multiperiod Corporate Default Risk Predictions
• What explains the dynamics of 100 anomalies?
• Director Histories and the Pattern of Acquisitions
• A Global Model for Bankruptcy Prediction. [europepmc]
• Characterisation of survivability resilience with dynamic stock interdependence in financial networks. [europepmc]
• Using critical slowing down indicators to understand economic growth rate variability and secular stagnation. [europepmc]
• Automated credit assessment framework using ETL process and machine learning. [europepmc]
• Financial crisis early warning of Chinese listed companies based on MD&A text-linguistic feature indicators. [europepmc]
• Predictive modeling of corporate financial risk and its implications for health economics and public health efficiency. [europepmc]
• The Resilience of African Banks in the COVID-19 Crisis: A Study on the Macroprudential Stress Test of Banks in the WAEMU Zone [europepmc]

Related

• Do forecasts of bankruptcy cause bankruptcy? A machine learning sensitivity analysis
• Are Foundation Models Useful for Bankruptcy Prediction?
• Bankruptcy Prediction from 10-K Narratives: Evidence from Interpretable Text Scores and Accounting Baselines
• A Race for Long Horizon Bankruptcy Prediction
• Bankruptcy Prediction of Small and Medium Enterprises Using a Flexible Binary Generalized Extreme Value Model