Financial Distress Prediction in Indian Small-Cap Companies: A Longitudinal Analysis Using Altman’s Z-Score Models

Abstract

This study examines financial distress dynamics in Indian small-cap firms using Altman's Z-score and Z''-score models through longitudinal analysis of 30 NSE listed companies observed semi-annually from March 2019 to March 2025. The research addresses critical gaps in emerging market distress prediction literature while capturing the complete COVID-19 pandemic trajectory. Results reveal significant heterogeneity in small-cap financial health: Z-score classifications show 60.5 per cent Safe, 18.5 per cent Grey Zone, and 21.0 per cent Distressed firms, while Z''-score identifies fewer distressed companies (14.9 per cent), yielding moderate inter-model agreement (Cohen's κ = 0.493). The Z-score exhibits 3.8-fold greater temporal volatility than Z''-score due to sales-to-assets ratio sensitivity.

Temporal analysis demonstrates a pronounced V-shaped recovery pattern, from pre-pandemic vulnerability (28.3 per cent distressed) through pandemic crisis peak (36.7 per cent distressed, March 2020) to robust recovery with 61.7 per cent improvement by March 2025. Sectoral analysis reveals statistically significant heterogeneity (ANOVA: F = 15.87, p < 0.001), with defensive sectors (FMCG: 0 per cent; Consumer Durables: 3.8 per cent) contrasting sharply with infrastructure sectors (Power: 100 per cent; Telecommunications: 76.9 per cent). Sector classification explains 32 per cent of distress variance. Findings advance bankruptcy prediction theory through emerging market validation and inform practice via dual-model investment screening, semi-annual credit monitoring and sector differentiated risk assessment. The study challenges conventional small firm fragility assumptions, demonstrating substantial adaptive capacity and resilience among survivors.