英文标题：
《Actuarial Applications and Estimation of Extended~CreditRisk$^+$》
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作者：
Jonas Hirz, Uwe Schmock, Pavel V. Shevchenko
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最新提交年份：
2017
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英文摘要：
We introduce an additive stochastic mortality model which allows joint modelling and forecasting of underlying death causes. Parameter families for mortality trends can be chosen freely. As model settings become high dimensional, Markov chain Monte Carlo (MCMC) is used for parameter estimation. We then link our proposed model to an extended version of the credit risk model CreditRisk$^+$. This allows exact risk aggregation via an efficient numerically stable Panjer recursion algorithm and provides numerous applications in credit, life insurance and annuity portfolios to derive P\\&L distributions. Furthermore, the model allows exact (without Monte Carlo simulation error) calculation of risk measures and their sensitivities with respect to model parameters for P\\&L distributions such as value-at-risk and expected shortfall. Numerous examples, including an application to partial internal models under Solvency II, using Austrian and Australian data are shown.
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中文摘要：
我们引入了一个加性随机死亡率模型，该模型允许联合建模和预测潜在的死亡原因。死亡率趋势的参数族可以自由选择。随着模型设置变得高维，马尔可夫链蒙特卡罗（MCMC）被用于参数估计。然后，我们将我们提出的模型链接到信用风险模型CreditRisk$^+$的扩展版本。这允许通过有效的数值稳定Panjer递归算法进行精确的风险聚合，并在信贷、人寿保险和年金投资组合中提供了大量应用，以推导损益分布。此外，该模型允许准确（无蒙特卡罗模拟误差）计算风险度量及其对损益分布模型参数（如风险价值和预期短缺）的敏感性。本文给出了许多例子，包括Solvency II下部分内部模型的应用，使用了奥地利和澳大利亚的数据。
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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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