英文标题：
《Wrong-Way Bounds in Counterparty Credit Risk Management》
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作者：
Amir Memartoluie, David Saunders, Tony Wirjanto
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最新提交年份：
2015
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英文摘要：
  We study the problem of finding the worst-case joint distribution of a set of risk factors given prescribed multivariate marginals and a nonlinear loss function. We show that when the risk measure is CVaR, and the distributions are discretized, the problem can be conveniently solved using linear programming technique. The method has applications to any situation where marginals are provided, and bounds need to be determined on total portfolio risk. This arises in many financial contexts, including pricing and risk management of exotic options, analysis of structured finance instruments, and aggregation of portfolio risk across risk types. Applications to counterparty credit risk are emphasized, and they include assessing wrong-way risk in the credit valuation adjustment, and counterparty credit risk measurement. Lastly a detailed application of the algorithm for counterparty risk measurement to a real portfolio case is also presented in this paper.
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中文摘要：
我们研究了给定给定多元边际和非线性损失函数的一组风险因素的最坏情况联合分布问题。我们证明，当风险度量为CVaR，且分布离散化时，可以使用线性规划技术方便地解决该问题。该方法适用于任何提供保证金的情况，需要确定总投资组合风险的界限。这在许多金融环境中都会出现，包括奇异期权的定价和风险管理、结构化金融工具的分析，以及跨风险类型组合风险的汇总。强调了对交易对手信用风险的应用，包括评估信用估值调整中的错误方式风险，以及交易对手信用风险度量。最后，本文还详细介绍了交易对手风险度量算法在实际投资组合案例中的应用。
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：Risk Management        风险管理
分类描述：Measurement and management of financial risks in trading, banking, insurance, corporate and other applications
衡量和管理贸易、银行、保险、企业和其他应用中的金融风险
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