We develop a continuous-time structural dynamic model to determine the exact insolvency regions of banks arising from the non-linear interaction between liquidity and credit risk. While existing literature predominantly treats these risks in isolation or via reduced-form specifications, we explicitly model the feedback loop where funding shocks and regulatory constraints force balance-sheet adjustments that can lead to endogenous insolvency. By incorporating Basel III regulatory requirements (LCR and NSFR) into a stochastic optimal control framework, we solve for the exact insolvency boundary using the Hamilton-Jacobi-Bellman (HJB) equation. To bridge the gap between theoretical complexity and supervisory practice, we derive and validate a surrogate analytical approximation function that allows for real-time monitoring. Calibrated using granular balance-sheet data from the Iranian banking sector, our model reveals significant non-linear threshold effects: the joint occurrence of liquidity stress and credit portfolio defaults disproportionately accelerates the transition toward insolvency compared to their individual effects. The proposed surrogate function offers supervisors a computationally efficient tool for stress testing and early warning systems. Our findings provide novel insights into financial frictions in emerging markets and offer a rigorous framework for integrated risk management.
The present paper aims to investigate the relationship between non-performing assets (NPAs) and profitability in Indian commercial banks. Focusing on the major economic disruptions, namely, the global financial crisis, demonetization and the COVID-19 pandemic, it examines their role in structurally reshaping the NPA-profitability nexus.
Our dataset comprised a balanced panel of 30 public and private sector commercial banks in India covering the period from 2004 to 2024. We applied Bai–Perron multiple breakpoint tests and Chow tests to identify regime shifts. Static panel regressions with Heteroskedasticity and Autocorrelation Consistent-corrected ordinary least squares and dynamic system generalized method of moments (GMM) estimations are employed to address heteroskedasticity, autocorrelation and endogeneity. The model incorporates bank-specific factors, market concentration indicators, macroeconomic variables and an interaction term between inflation and broad money (BM).
The findings reveal multiple statistically significant structural breaks corresponding to major economic shocks. NPAs consistently exert a significant negative impact on profitability across all regimes, while bank size positively influences return on assets, particularly during crisis periods. Market concentration yields mixed and regime-dependent effects. The interaction between inflation and BM significantly moderates profitability during transitional phases, highlighting the role of inflation-adjusted liquidity conditions in shaping bank performance.
The findings suggest that bank managers should strengthen credit risk monitoring and adopt proactive asset quality management, especially during periods of inflationary liquidity expansion. The policymakers and regulators can benefit from implementing countercyclical capital buffers and dynamic stress-testing frameworks tailored to structural shocks. However, our results should be interpreted with caution as we excluded foreign banks from our dataset and focused solely on Indian commercial banks, which may limit cross-country generalizability. Future research could extend the framework to comparative emerging-market settings.
To the best of our knowledge, this study is the first attempt to integrate structural break analysis with dynamic GMM estimation and to introduce inflation-adjusted liquidity as a moderating mechanism in the NPA-profitability relationship in an emerging economy context.
Faiza Rehman, Mohammad Ammar Ahsan, S. Akhtar et al.· Journal of Financial Regulat...· 0 citations
This research investigates how liquidity creation induces moral hazard behavior and affects credit quality in Indonesian commercial banks. This study examines the effect of liquidity creation, liquidity risk, and central bank policies on credit risk in Indonesian commercial banks, proxied by the non-performing loan (NPL) ratio. Using panel data from 46 banks listed on the Indonesia Stock Exchange over 2015–2024, we apply the Two-Step System Generalized Method of Moments (SYS-GMM) to address endogeneity inherent in dynamic panel models. Results indicate that liquidity creation has a significant positive effect on NPL, consistent with the moral hazard hypothesis. Liquidity risk (LDR) also significantly and positively affects NPL. Reserve requirements (GWM) and BI-Rate do not produce a direct and significant effect on NPL. Return on assets (ROA) significantly and negatively affects NPL. These results suggest that credit risk in Indonesian commercial banking is predominantly influenced by bank-level intermediation behavior rather than by macroeconomic or policy variables. The research concludes that excess liquidity conditions incentivize aggressive credit expansion without proportionate attention to borrower quality, particularly in an oligopolistic market structure with implicit state guarantees.
Jeffry Fauzan, Dewi Hanggraeni· Eduvest - Journal Of Univers...· 0 citations
We propose a novel valuation framework for contingent convertible (CoCo) bonds based on the issuing bank's Common Equity Tier 1 (CET1) ratio, which is widely acknowledged as an indicator of a bank's solvency. Our approach develops a bivariate jump-diffusion model that captures the dynamic relationship linking the CET1 ratios, share prices, and CoCo bond prices, incorporating both continuous market movements and correlated jump risk. The model advances existing literature through three key innovations: (1) a hybrid mechanism for modeling regulatory discretion in trigger decisions, (2) a class of power conversion schemes that generalizes traditional approaches while maintaining analytical tractability, and (3) a method to overcome the temporal discrepancy between high-frequency market data and low-frequency regulatory reporting. We derive semi-closed form formulas for both write-down and equity-convertible CoCo bonds and validate our model through five case studies spanning from 2009 to 2023, including an in-depth analysis of the 2023 Credit Suisse collapse. The results demonstrate a significant improvement in pricing and hedging performance while highlighting the model's data-adaptive nature that enables short-term predictions.
This study proposes a closed-system linear ordinary differential equation (ODE) model to analyse and predict the dynamics of liquid assets and outstanding loans in credit union liquidity risk management. Using 40 quarterly observations (2015–2024) obtained from the Central Finance Facility (CFF) of the Ghana Co-operative Credit Unions Association (CUA), the study formulates a two-state deterministic model governed by the asset-to-loan transition rate α, the loan-to-asset recovery rate β, and the loan default rate δ. Closed-form solutions are derived using the Laplace transform technique, and discrete quarterly prediction equations are obtained using a first-order Taylor expansion. Stability analysis confirms that the system is asymptotically stable when α, β, and δ are positive. Model performance is evaluated using root mean square error (RMSE), mean absolute percentage error (MAPE), and the Scatter Index (SI). The optimal asset prediction model corresponds to α = 0.0869 (MAPE = 14.27%), and the optimal loan model to ω = 0.91 (RMSE = 225,548.63). Additionally, three machine-learning models—Support Vector Regression (SVR), XGBoost, and Random Forest—are employed to generate eight-quarter-ahead forecasts (2025–2026). SVR achieves the best out-of-sample performance for forecasting both assets (MAPE = 2.92%) and loans (MAPE = 3.70%). The study concludes that the ODE-based closed liquidity model provides an analytically rigorous and practically interpretable framework for credit union liquidity planning, and that SVR-based forecasting offers a useful complement for short-term projections.
C. Mensah, L. Brew, Monica Crankson· Asian Research Journal of Ma...· 0 citations
Modern resolution and prudential regimes increasingly wind up a distressed firm not at a single hard threshold but through a graduated, state-dependent process. We study how the design of such a regime shapes the trade-off between shareholder value and financial stability for a firm whose surplus follows a general diffusion. Forced liquidation is modelled in reduced form, arriving at a surplus-dependent hazard rate that rises as the firm's position deteriorates. The framework has three regions: an unregulated region where dividends may be paid, a regulated region where solvency requirements prohibit distributions, and a distress region in which the firm faces the liquidation hazard. To quantify shareholder value we solve the resulting singular stochastic control problem: which is to maximise the expected present value of distributions until liquidation. We establish a verification theorem, prove that a barrier strategy is optimal, and obtain tractable expressions for the value function and the expected survival time, so that alternative designs can be compared at low cost. We show that a distress region placed solely below or solely above the classical ruin threshold does not consistently improve both shareholder value and firm survival, whereas combining the two yields a Pareto improvement. Regulatory design is decisive.
Benjamin Avanzi, Bernard Wong, Jinxia Zhu· 0 citations
This paper analyses the short-run dynamic relationship between monetary policy and banking market structure in Colombia during a period of post-pandemic inflation and aggressive policy tightening. Using monthly credit portfolio data for 2017–2024, we compute several concentration indicators (the Herfindahl–Hirschman Index (HHI), CRk ratios, and a dominance index) and employ three complementary identification strategies to evaluate the causal effect of monetary policy innovations on banking concentration. First, a structural VAR model identified through sign restrictions finds that contractionary shocks are associated with a short-run increase in banking concentration (median peak response: +0.60 HHI points at h = 3; 90% credible set: [+0.12, +1.16]), contrasting with the negative short-run response obtained under recursive reduced-form identification. Second, an extended VAR including credit portfolio growth as a mechanism variable confirms that contractionary shocks compress aggregate lending but do not generate robust, persistent changes in concentration. Third, local projections with regime-interaction terms formally test the nonlinear mechanisms discussed in the literature and find evidence of state-dependent transmission: the concentration response is larger in the low-inflation regime and attenuates during high-inflation episodes. All estimated effects are transitory and horizon-sensitive, reinforcing a cautious interpretation. The paper contributes new evidence from an emerging economy on the structural consequences of monetary policy and highlights the importance of identification assumptions in determining the direction of this effect.
Yoly Tatiana Polania Cerinza, Osval Armando Ibáñez-Díaz, H. Guerrero-Sierra et al.· Journal of Risk and Financia...· 0 citations