Author
Listed:
- Bruce Rishel
(Poisson Consulting, LLC, West Friendship, MD 21794, USA)
- Melissa Rishel
(Poisson Consulting, LLC, West Friendship, MD 21794, USA)
Abstract
The most widely used bankruptcy predictor, Altman’s Z-Score, assigns a positive coefficient to asset turnover; faster firms are rated safer. Under crisis conditions, that assumption reverses. We introduce the Solvency Margin (SM), a diagnostic calculable from standard financial statements that measures, in dollars, how far an organization is from the threshold where operations become impossible. Unlike static liquidity ratios, the SM yields a concrete speed limit: the maximum operating velocity at which an organization can survive a defined shock. We validated the SM against pre-crisis financial data across three crises in two domains. Regarding the automotive sector, SM computed from FY2019 filings showed directional predictive power among ten major automakers in both the 2021 semiconductor shortage (ρ = 0.50, p = 0.14) and the 2020 COVID-19 pandemic (ρ = 0.53, p = 0.12; ρ = 0.70, p = 0.036 excluding one governance-driven outlier). With reference to the 2023 U.S. banking crisis, SM augmented with a Deposit Stability Factor predicted crisis outcomes among eighteen regional banks (Spearman ρ = 0.62, p = 0.006), correctly ranking three of four failed institutions in the bottom three positions. Monte Carlo simulation (450,000+ runs) confirmed threshold behavior. We present a five-step calculation method and a three-lever decision framework for practitioners.
Suggested Citation
Bruce Rishel & Melissa Rishel, 2026.
"The Solvency Margin: A Speed-Limit Metric for Capital-Constrained Organizations Under Stress,"
JRFM, MDPI, vol. 19(6), pages 1-25, May.
Handle:
RePEc:gam:jjrfmx:v:19:y:2026:i:6:p:396-:d:1955327
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