AI 中文总结
本文提出基于弹性停止莱维过程的多信用校准模型，通过添加共同复合泊松跳跃因子实现简约多信用建模，在CDX北美高收益及投资级面板上的样本外误差更低，且优于单因子高斯copula等基准模型。
AI 中文摘要
本文采用弹性停止莱维过程对信用违约互换及指数分层产品进行校准：当潜在的谱正困境过程的运行上确界越过独立指数障碍时，每家公司发生违约，该构造产生具有完全不可达违约时间的考克斯模型，同时保留结构方法的可解释性和显式公式。通过为每家公司的潜在驱动因子添加单一共同复合泊松跳跃因子，得到一个简约的多信用模型，可实现同时违约，该模型通过精确的维纳-霍普夫蒙特卡洛方案定价。其可处理性基于我们证明的单名称结果：相位型跳跃下违约概率拉普拉斯变换的有限部分分式公式。在每日CDX北美高收益及投资级面板上，我们的驱动因子在6个模型中实现了最低的样本外误差，且能再现违约前夕名称的反转利差曲线，而莱维子过程显然无法做到这一点。在指数层面，当依赖参数固定时，两参数依赖结构可缩小独立边际所留下的分层定价缺口的73%至89%；若重新标记至分层报价，该比例可达95%。我们的框架在两个指数上均优于单因子高斯copula模型及Duffie-Gârleanu的仿射强度基准模型。
英文摘要
We calibrate credit default swaps and index tranches with elastically stopped Lévy processes: each firm defaults when the running supremum of a latent, spectrally positive distress process crosses an independent exponential barrier. This yields a Cox construction with totally inaccessible default times, while retaining the interpretability and explicit formulas of a structural approach. Adding a single common compound Poisson jump factor to every firm's latent driver gives a parsimonious multi-credit model with simultaneous defaults, which is priced by an exact Wiener--Hopf Monte Carlo scheme. Its tractability rests on a single-name result we prove: a finite partial-fraction formula for the Laplace transform of the default probability under phase-type jumps. On daily CDX North American High-Yield and Investment-Grade panels, our drivers attain the lowest out-of-sample errors in a six-model field and reproduce the inverted spread curves of names heading into default, which a Lévy subordinator provably does not. At the index level, the two-parameter dependence structure closes $73\%$ to $89\%$ of the tranche pricing gap left by independent marginals with the dependence parameters frozen, and up to $95\%$ once re-marked to tranche quotes; our framework dominates a single-factor Gaussian copula and the affine intensity benchmark of Duffie--Gârleanu on both indices.
Comments36 pages, 12 tables, 2 figures
