摘要翻译:
本文利用Tweedie的复合泊松模型研究索赔保留问题。我们发展了最大似然和贝叶斯马尔可夫链蒙特卡罗模拟方法来拟合模型,然后比较了不同情景下的估计模型。我们论证的关键点涉及在预测中加入模型不确定性和不加入模型不确定性的情况下储备数量的比较。我们考虑了预测储量的模型选择问题和模型平均解。作为这一过程的一部分,我们还考虑了变量选择的子问题,以获得被拟合模型的简约表示。
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英文标题:
《Model uncertainty in claims reserving within Tweedie's compound Poisson
models》
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作者:
Gareth W. Peters, Pavel V. Shevchenko and Mario V. W\"uthrich
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最新提交年份:
2009
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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:Quantitative Finance 数量金融学
二级分类:Computational Finance 计算金融学
分类描述:Computational methods, including Monte Carlo, PDE, lattice and other numerical methods with applications to financial modeling
计算方法,包括蒙特卡罗,偏微分方程,格子和其他数值方法,并应用于金融建模
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英文摘要:
In this paper we examine the claims reserving problem using Tweedie's compound Poisson model. We develop the maximum likelihood and Bayesian Markov chain Monte Carlo simulation approaches to fit the model and then compare the estimated models under different scenarios. The key point we demonstrate relates to the comparison of reserving quantities with and without model uncertainty incorporated into the prediction. We consider both the model selection problem and the model averaging solutions for the predicted reserves. As a part of this process we also consider the sub problem of variable selection to obtain a parsimonious representation of the model being fitted.
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PDF链接:
https://arxiv.org/pdf/0904.1483