当比率下降：或有可转换债券的动态方法
When ratios fall: A dynamic approach to contingent convertibles
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中文总结 AI 辅助
本研究针对或有可转换债券，构建纳入监管自由裁量权、幂转换方案等创新的双变量跳扩散模型，经案例验证可提升定价对冲表现并支持短期预测。
中文摘要 AI 辅助
我们提出一种基于发行银行的一级资本比率（CET1，被广泛认可为银行偿付能力指标）的或有可转换债券（CoCo）的新型估值框架。该方法构建了双变量跳扩散模型，捕捉将CET1比率、股价与CoCo债券价格关联起来的动态关系，同时纳入连续市场变动与相关跳风险。该模型通过三项关键创新推进现有文献：（1）用于建模触发决策中监管自由裁量权的混合机制；（2）一类幂转换方案，在保持分析可处理性的同时推广传统方法；（3）克服高频市场数据与低频监管报告间时间差异的方法。我们推导了减记型与股权转换型CoCo债券的半闭式公式，并通过2009年至2023年间的五个案例研究验证模型，其中包含对2023年瑞士信贷倒闭事件的深入分析。结果表明，该模型在定价与对冲表现上有显著提升，同时凸显其可适应数据的特性，能够实现短期预测。
英文摘要
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.
