Corporate Debt as a Put Option: A Structural Credit Risk Framework for Banks Under Dynamic Refinancing Risk
This paper extends the classical Merton structural credit risk model by incorporating dynamic refinancing risk into the measurement of bank default risk. The study addresses a key limitation of traditional structural models, which treat default as a function of asset values relative to liabilities but abstract from debt maturity structure and rollover conditions. The proposed framework integrates an issuance-based refinancing ladder, a market-consistent funding curve, and firm-level balance sheet data within a liquidity-adjusted structural model featuring an endogenous default barrier and a refinancing-adjusted distance-to-default measure. Using bank-level data (1564 daily observations, 2020–2026), the results show that, although the institution remains solvent under conventional structural measures, refinancing exposure materially compresses the effective solvency buffer. Short-term refinancing exposure averages R8.1 billion and reaches approximately R19.6 billion during stress periods; the liquidity-adjusted distance to default averages 1.47 (range 0.46–2.15) and the implied probability of default averages 9.5% (range 1.6–32.2%). A Newey–West heteroskedasticity- and autocorrelation-consistent regression that controls for asset volatility and the underlying solvency ratio confirms that the refinancing ratio has a negative and highly statistically significant partial effect on distance to default (coefficient −1.95, t = −7.41, p < 0.001, N = 1564), isolating the liquidity-adjustment channel from concurrent changes in volatility and balance sheet solvency. Stress testing further reveals nonlinear amplification of default risk when funding and refinancing shocks interact. The findings indicate that bank default risk is driven not only by leverage, but also by the interaction between asset values, liability structure, and funding conditions, with implications for credit risk modelling, stress testing, and prudential risk management.