SIAM Journal on Financial Mathematics, Volume 11, Issue 4, Page 1098-1136, January 2020.
We design a metamodel for the loss distribution ${\mathcal L}$ of a large credit risk portfolio in the Gaussian copula model. Our procedure is twofold. We first apply the Wiener chaos decomposition on the normal systemic economic factor and derive a truncated loss ${\mathcal{L}_{I}}$ at some order $I$. Then, we provide a Gaussian approximation ${\mathcal{L}_{I}^{{G}}}$ of the associated truncated loss. Such an approach is motivated by the fact that we are dealing with large portfolios. Our procedure significantly reduces the computational time needed for sampling the loss and therefore for estimating risk measures. The accuracy and effectiveness of our method are confirmed by numerical examples.

中文翻译：

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高斯Copula模型中大型信用风险投资组合的元模型

SIAM金融数学杂志，第11卷，第4期，第1098-1136页，2020年1月。
我们为高斯copula模型中的大型信用风险投资组合的损失分布$ {\ mathcal L} $设计了一个元模型。我们的过程是双重的。我们首先将Wiener混沌分解应用于正常的系统经济因素，并以某个阶次$ I $得出截断的损失$ {\ mathcal {L} _ {I}} $。然后，我们提供相关的截断损耗的高斯近似值$ {\ mathcal {L} _ {I} ^ {{G}}} $。我们正在处理大型投资组合这一事实激励了这种方法。我们的程序大大减少了采样损失并因此估计风险度量所需的计算时间。数值例子证实了我们方法的准确性和有效性。