英文标题：
《Signs of dependence and heavy tails in non-life insurance data》
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作者：
Jonas Alm
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最新提交年份：
2015
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英文摘要：
  In this paper we study data from the yearly reports the four major Swedish non-life insurers have sent to the Swedish Financial Supervisory Authority (FSA). We aim at finding marginal distributions of, and dependence between, losses on the five largest lines of business (LoBs) in order to create models for Solvency Capital Requirement (SCR) calculation. We try to use data in an optimal way by sensibly defining an accounting year loss in terms of actuarial liability predictions, and by pooling observations from several companies when possible to decrease the uncertainty about the underlying distributions and their parameters. We find that dependence between LoBs is weaker in our data than what is assumed in the Solvency II standard formula. We also find dependence between companies that may affect financial stability, and must be taken into account when estimating loss distribution parameters. Moreover, we discuss under what circumstances an insurer is better (or worse) off using an internal model for SCR calculation instead of the standard formula.
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中文摘要：
在本文中，我们研究了瑞典四大非寿险保险公司向瑞典金融监管局（FSA）提交的年度报告中的数据。我们的目标是找到五大业务线（LOB）损失的边际分布以及它们之间的依赖关系，以便创建偿付能力资本要求（SCR）计算模型。我们试图以最佳方式使用数据，通过精算负债预测合理地定义会计年度损失，并在可能的情况下汇集多家公司的观察结果，以减少潜在分布及其参数的不确定性。我们发现，与Solvency II标准公式中的假设相比，我们的数据中LOB之间的依赖性较弱。我们还发现，公司之间的依赖性可能会影响金融稳定，在估计损失分布参数时必须加以考虑。此外，我们还讨论了在什么情况下，保险公司最好（或更糟）使用内部模型来计算SCR，而不是使用标准公式。
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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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