英文标题：
《Managing counterparty credit risk via BSDEs》
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作者：
Andrew Lesniewski and Anja Richter
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最新提交年份：
2016
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英文摘要：
We discuss a general dynamic replication approach to counterparty credit risk modeling. This leads to a fundamental jump-process backward stochastic differential equation (BSDE) for the credit risk adjusted portfolio value. We then reduce the fundamental BSDE to a continuous BSDE. Depending on the close out value convention, the reduced fundamental BSDE\'s solution can be represented explicitly or through an accurate approximate expression. Furthermore, we discuss practical aspects of the approach, important for the its industry applications: (i) efficient numerical methodology for solving a BSDE driven by a moderate number of Brownian motions, and (ii) factor reduction methodology that allows one to approximately replace a portfolio driven by a large number of risk factors with a portfolio driven by a moderate number of risk factors.
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中文摘要：
我们讨论了交易对手信用风险建模的一般动态复制方法。这导致了信用风险调整后的投资组合价值的基本跳跃过程倒向随机微分方程（BSDE）。然后，我们将基本BSDE简化为连续BSDE。根据收尾值惯例，简化基本BSDE的解可以显式表示或通过精确的近似表达式表示。此外，我们还讨论了该方法的实际方面，这对其工业应用非常重要：（i）求解由中等数量布朗运动驱动的BSDE的有效数值方法，以及（ii）因子缩减方法，该方法允许将由大量风险因素驱动的投资组合近似替换为由中等数量风险因素驱动的投资组合。
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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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一级分类：Mathematics 数学
二级分类：Probability 概率
分类描述：Theory and applications of probability and stochastic processes: e.g. central limit theorems, large deviations, stochastic differential equations, models from statistical mechanics, queuing theory
概率论与随机过程的理论与应用：例如中心极限定理，大偏差，随机微分方程，统计力学模型，排队论
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