Everything You Always Wanted to Know About XVA Model Risk but Were Afraid to Ask
Everything You Always Wanted to Know About XVA Model Risk but Were Afraid to Ask
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您一直想了解但又不敢问的有关 XVA 模型风险的一切
DOI：
10.2139/ssrn.3891120
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发表时间：
2021
期刊：
影响因子：
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通讯作者：
M. Bianchetti
中科院分区：
文献类型：
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作者：
Lorenzo Silotto;Marco Scaringi;M. Bianchetti
估值调整，统称为XVA，在现代衍生品定价中发挥着重要作用。XVA是一种特殊的定价成分，因为它们需要对多个风险因素进行远期模拟，以计算包括抵押品在内的投资组合风险，即使在普通交易的情况下，也会导致重大的模型风险和计算工作量。这项工作分析了最关键的模型风险因素，即XVA最敏感的因素，在准确性和性能之间找到了一个可接受的折衷方案。这项任务是在一个完整的背景下进行的，包括根据真实的市场数据校准的市场标准多曲线G2++模型，变化保证金和ISDA-SIMM动态初始保证金，不同的抵押方案，以及最常见的线性和非线性利率衍生品。此外，我们考虑了一种替代的分析方法XVA的情况下，无抵押掉期。我们发现，一个至关重要的因素是建设一个吝啬的时间网格能够捕捉所有周期性的峰值在担保风险期间产生的风险。为此，我们提出了一个解决方案，以有效地捕捉所有尖峰。此外，我们表明，存在一个参数化，可以在合理的时间内获得准确的结果，这是一个非常重要的功能，为实际应用。为了解决与存在一系列不同参数化相关的估值不确定性，我们根据欧盟审慎估值法规的规定计算XVA的模型风险AVA（额外估值调整）。最后，这项工作可以作为一个手册，包含一个完整的，现实的和强大的建模框架的抵押风险和XVA的实施分步说明。
Valuation adjustments, collectively named XVA, play an important role in modern derivatives pricing. XVA are an exotic pricing component since they require the forward simulation of multiple risk factors in order to compute the portfolio exposure including collateral, leading to a significant model risk and computational effort, even in case of plain vanilla trades. This work analyses the most critical model risk factors, meant as those to which XVA are most sensitive, finding an acceptable compromise between accuracy and performance. This task has been conducted in a complete context including a market standard multi-curve G2++ model calibrated on real market data, both Variation Margin and ISDA-SIMM dynamic Initial Margin, different collateralization schemes, and the most common linear and non-linear interest rates derivatives. Moreover, we considered an alternative analytical approach for XVA in case of uncollateralized Swaps. We show that a crucial element is the construction of a parsimonious time grid capable of capturing all periodical spikes arising in collateralized exposure during the Margin Period of Risk. To this end, we propose a workaround to efficiently capture all spikes. Moreover, we show that there exists a parameterization which allows to obtain accurate results in a reasonable time, which is a very important feature for practical applications. In order to address the valuation uncertainty linked to the existence of a range of different parameterizations, we calculate the Model Risk AVA (Additional Valuation Adjustment) for XVA according to the provisions of the EU Prudent Valuation regulation. Finally, this work can serve as an handbook containing step-by-step instructions for the implementation of a complete, realistic and robust modelling framework of collateralized exposure and XVA.