非现金抵押品
Haircutting Non-cash Collateral
摘要：
削减非现金抵押品已成为危机后影子银行体系和场外衍生品市场改革的关键要素。本文通过对传统的风险价值度量方法进行扩展，并采用双指数跳扩散模型对抵押品市场风险进行分析，建立了一个参数化的折价模型。折让乃针对信用风险计量（包括违约概率、预期亏损或非预期亏损标准）而解决。与通常基于代理数据序列的数据驱动方法相比，该模型能够进行敏感性分析和压力测试，捕捉市场流动性风险，允许特殊风险调整，并结合相关市场信息。主要股票、证券化和公司债券的计算结果显示出在担保协议（例如CSA）和监管资本计算中的潜在用途。
英文摘要：
Haircutting non-cash collateral has become a key element of the post-crisis reform of the shadow banking system and OTC derivatives markets. This article develops a parametric haircut model by expanding haircut definitions beyond the traditional value-at-risk measure and employing a double-exponential jump-diffusion model for collateral market risk. Haircuts are solved to target credit risk measurements, including probability of default, expected loss or unexpected loss criteria. Comparing to data-driven approach typically run on proxy data series, the model enables sensitivity analysis and stress test, captures market liquidity risk, allows idiosyncratic risk adjustments, and incorporates relevant market information. Computational results for main equities, securitization, and corporate bonds show potential for uses in collateral agreements, e.g. CSAs, and for regulatory capital calculations.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
