英文标题：
《The Credibility Theory applied to backtesting Counterparty Credit Risk》
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作者：
Matteo Formenti
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最新提交年份：
2014
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英文摘要：
  Credibility theory provides tools to obtain better estimates by combining individual data with sample information. We apply the Credibility theory to a Uniform distribution that is used in testing the reliability of forecasting an interest rate for long term horizons. Such empirical exercise is asked by Regulators (CRR, 2013) in validating an Internal Model Method for Counterparty Credit Risk. The main results is that risk managers consider more reliable the output of a test with limited sample size when the Credibility is applied to define a confidence interval.
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中文摘要：
可信性理论通过将个体数据与样本信息相结合，提供了获得更好估计的工具。我们将可信度理论应用于均匀分布，用于测试长期利率预测的可靠性。监管机构（CRR，2013）在验证交易对手信用风险的内部模型方法时，要求进行此类实证研究。主要结果是，当可信度用于定义置信区间时，风险管理者认为样本量有限的测试结果更可靠。
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：Statistical Finance        统计金融
分类描述：Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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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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