英文标题：
《Disentangling wrong-way risk: pricing CVA via change of measures and
drift adjustment》
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作者：
Damiano Brigo and Fr\\\'ed\\\'eric Vrins
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最新提交年份：
2016
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英文摘要：
A key driver of Credit Value Adjustment (CVA) is the possible dependency between exposure and counterparty credit risk, known as Wrong-Way Risk (WWR). At this time, addressing WWR in a both sound and tractable way remains challenging: arbitrage-free setups have been proposed by academic research through dynamic models but are computationally intensive and hard to use in practice. Tractable alternatives based on resampling techniques have been proposed by the industry, but they lack mathematical foundations. This probably explains why WWR is not explicitly handled in the Basel III regulatory framework in spite of its acknowledged importance. The purpose of this paper is to propose a new method consisting of an appealing compromise: we start from a stochastic intensity approach and end up with a pricing problem where WWR does not enter the picture explicitly. This result is achieved thanks to a set of changes of measure: the WWR effect is now embedded in the drift of the exposure, and this adjustment can be approximated by a deterministic function without affecting the level of accuracy typically required for CVA figures. The performances of our approach are illustrated through an extensive comparison of Expected Positive Exposure (EPE) profiles and CVA figures produced either by (i) the standard method relying on a full bivariate Monte Carlo framework and (ii) our drift-adjustment approximation. Given the uncertainty inherent to CVA, the proposed method is believed to provide a promising way to handle WWR in a sound and tractable way.
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中文摘要：
信用价值调整（CVA）的一个关键驱动因素是风险敞口和交易对手信用风险之间可能存在的依赖关系，即错误方向风险（WWR）。目前，以合理且易于处理的方式解决WWR仍然具有挑战性：学术研究通过动态模型提出了无套利设置，但计算量大，难以在实践中使用。业界已经提出了基于重采样技术的可行替代方案，但它们缺乏数学基矗这可能解释了为什么《巴塞尔协议III》监管框架没有明确处理WWR，尽管其重要性已得到公认。本文的目的是提出一种新的方法，该方法由一个吸引人的折衷方案组成：我们从一个随机强度方法开始，最终得到一个定价问题，在这个问题中，WWR没有明确进入图片。这一结果是通过一系列测量变化实现的：WWR效应现在嵌入到曝光漂移中，并且这种调整可以通过确定性函数近似，而不会影响CVA图形通常需要的精度水平。通过（i）依赖于全双变量蒙特卡罗框架的标准方法和（ii）漂移调整近似方法产生的预期正暴露（EPE）曲线和CVA曲线的广泛比较，说明了我们方法的性能。考虑到CVA固有的不确定性，所提出的方法被认为是以一种合理且易于处理的方式处理WWR的一种有希望的方法。
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分类信息：

一级分类：Quantitative Finance 数量金融学
二级分类：Mathematical Finance 数学金融学
分类描述：Mathematical and analytical methods of finance, including stochastic, probabilistic and functional analysis, algebraic, geometric and other methods
金融的数学和分析方法，包括随机、概率和泛函分析、代数、几何和其他方法
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