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.
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.
This study examines whether the cash conversion cycle (CCC) supports financial flexibility or instead increases firm vulnerability under economic policy uncertainty (EPU), and tests whether the COVID-19 pandemic altered this relationship for firms with different pre-existing working-capital structures. The study uses a balanced panel of 391 non-financial Indian listed firms over 2014–2024 (4,301 firm-year observations), drawn from the CMIE Prowess database. Firm fixed-effects and random-effects models are estimated with default, firm-clustered, and Driscoll-Kraay standard errors; a difference-in-differences design with firm and year fixed effects is used to exploit the COVID-19 pandemic as an exogenous shock, with firms classified into treatment (above-median pre-pandemic CCC) and control (below-median) groups. The analysis is supplemented with an event-study test of the parallel-trends assumption, a placebo test, a lagged-CCC specification, and a dynamic-panel system GMM model. CCC is not robustly significant for return on assets (ROA) once firm-clustered standard errors are applied (p = 0.264), though a one-year-lagged CCC is significantly positive for both ROA and ROE (p < 0.05); CCC is not significant for return on equity (ROE) in the static specification. EPU is positively associated with ROA at conventional or near-conventional levels across specifications. The CCC × EPU interaction is consistently negative but reaches significance only in the dynamic system-GMM specification for ROA (p = 0.025). An event-study test does not reject parallel pre-trends, and the difference-in-differences and placebo estimates show no significant differential effect for high-CCC firms at the onset of the pandemic, though a significant gap emerges by 2024. Working-capital efficiency appears to operate as a gradual, lagged operational channel rather than an immediate source of profitability or crisis vulnerability. Managers should treat CCC as a medium-term operational lever rather than a short-term crisis response tool, and should prioritise short-term liquidity buffers - proxied here by the current ratio, the most consistently significant predictor of ROA throughout this study. Policymakers should prioritise macroeconomic stability, since EPU itself shows a positive association with ROA, consistent with well-managed firms being better placed to absorb policy uncertainty. The study combines a continuous, time-varying uncertainty measure (EPU) with a discrete exogenous shock (COVID-19) within a single firm-level identification strategy, and is, to our knowledge, among the first studies of Indian working-capital management to combine static fixed-effects estimation with an event-study test of parallel trends, a placebo test, and a system-GMM dynamic-panel specification within one design.
M. Gnanendra, Guruprasad Desai, M. N. Nikhil et al.· SN Business & Economics· 0 citations
This study analyzes the microstructural mechanisms through which the rapidly expanding single-stock leveraged ETFs in the Korean capital market impede the price discovery function and amplify endogenous volatility. Based on a dynamic simulation utilizing the actual market scales of large-cap semiconductor stocks, the results demonstrate that mechanical, pro-cyclical rebalancing concentrated at the market-on-close (MOC) induces directional distortion, systematically driving asset prices away from their fundamental values depending on market conditions. In particular, this study provides evidence that as the assets under management (AUM) of these linked products expand, the liquidity breakdown threshold of the limit order book declines steeply. Consequently, even minor illiquidity frictionscan cause mechanical selling pressure to escalate directly into tail risk. Drawing on these findings, this study offers policy implications to enhance macroprudential stability and prevent the transmission of microstructural risks into systemic risks. Specifically, we propose the introduction of dynamic AUM caps, the normalization of creation fees to mitigate structural conflicts of interest among Authorized Participants (APs), and restrictions on listing ultra-high leveraged products.
Sun-Joong Yoon· Korean Journal of Financial...· 0 citations
We develop a rigorous framework for modeling collateral liquidations in decentralized lending protocols such as Aave and Compound. In contrast to earlier approaches based on constant-product market maker (CPM) assumptions, real-world liquidations are executed through order books with finite depth. This introduces price impact, modifies solvency conditions, and reduces safe loan-to-value ratios. We introduce the Aggregate Value Function, defined directly on the order book, and establish its monotonicity, concavity, and quasi-linearity, following the quasi-linear order book framework. Building on these properties, we derive solvency inequalities and explicit formulas for safe leverage. Our model extends CPM-based theory to discrete liquidity environments and provides foundations for risk management and parameter design in lending protocols.
Matvii Tulupov· Theoretical and Applied Cybe...· 0 citations
Does protection of trademark‐related intangible capital affect firms’ real contracting decisions? We exploit the Federal Trademark Dilution Act of 1996 (FTDA) as a plausibly exogenous strengthening of legal protection to answer the question. In a difference‐in‐differences design using a propensity‐score‐matched sample, treated firms reduce their reliance on operating leases following the reform, with declines ranging from 3.5% to 5.3% of a standard deviation of the outcome variables. The results are robust to event‐study tests showing no differential pre‐trends, placebo tests using a fictitious treatment date, and alternative estimation windows. The decline in leasing is more pronounced among firms with higher pre‐FTDA branding intensity, cash‐flow volatility, R&D intensity, and product‐market fluidity, where lease flexibility is likely more valuable. Treated firms also experience higher average cash flows and lower cash‐flow volatility, while showing no systematic changes in capital expenditures and total leverage. The evidence indicates that stronger trademark protection is associated with both more stable brand‐related cash flows and reduced use of operating lease contracts, consistent with an operating‐stability channel.
C. Cao, Chongyang Chen· The Financial Review· 0 citations
This study investigates the valuation gap between buyers and sellers of insurers' contingent capital, driven by asymmetric exposures to tax benefits, capital injections, and bankruptcy costs. We develop a novel Twin‐Tree Model with Jumps (
TTMJ
) that models the insurer's asset value dynamics by incorporating catastrophe risk, insolvency risk, and contractual features observed in practice. Using U.S. earthquake loss data and a representative real‐world contract, we show that early exercise and net‐worth provisions significantly affect contract tradability by expanding the range of mutually acceptable prices. Our results provide new insights into reconciling valuation asymmetries and offer guidance for designing contingent capital instruments that enhance insurers' financial resilience under catastrophe risk.
Tianran Dai, Chien‐Ling Lo, You-Jia Sun et al.· Journal of Risk and Insuranc...· 0 citations