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Local risk minimization, consistent interest-rate modeling, and applications to life insurance.

机译:最小化本地风险,一致的利率模型以及在人寿保险中的应用。

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摘要

This thesis studies local risk minimization, consistent interest-rate modeling, and their applications to life insurance.;Part I considers local risk minimization, which is one possible approach to price and hedge claims in incomplete markets. In this first part, our two main results are Propositions 3.6 and 4.3: they provide an easy way to compute locally risk-minimizing hedging strategies for common life-insurance products in discrete time and in continuous time, respectively.;Part II considers consistent interest-rate modeling; that is, interest-rate models in which a change in the yield curve can be explained by a change in the state variable, without changing the parameters of the model. In this second part, we present a single-factor interest-rate model (jointly specified under the physical and the risk-neutral probability measures), which allows for observation errors. Our main result is an algorithm to estimate the hidden values of the state variable, as well as the five parameters of our model. We also outline how our results can be extended to the multi-factor case.;Part III combines the results of Parts I and II in a numerical example. In this example, we compute a locally risk-minimizing hedging strategy for a life annuity under stochastic interest rates. We assume that the insurance company is trying to hedge this product by trading zero-coupon bonds of various maturities. Since a perfect hedge is impossible in this case, we obtain (by simulation) the distribution of the cost resulting from the "mis-hedge". This distribution is with respect to the physical probability measure, while most of the existing literature considers it under a risk-neutral measure.
机译:本文研究了局部风险最小化,一致的利率模型及其在人寿保险中的应用。第一部分考虑了局部风险最小化,这是在不完全市场中价格和对冲债权的一种可能方法。在第一部分中,我们的两个主要结果是命题3.6和4.3:它们提供了一种简便的方法来分别计算离散时间和连续时间的普通人寿保险产品的局部风险最小化对冲策略;第二部分考虑了一致的兴趣速率建模;即利率模型,其中收益率曲线的变化可以通过状态变量的变化来解释,而无需更改模型的参数。在第二部分中,我们提出了一个单因素利率模型(在有形和风险中性概率测度下共同指定),该模型允许观察误差。我们的主要结果是一种算法,用于估计状态变量的隐藏值以及模型的五个参数。我们还概述了如何将结果扩展到多因素案例。第三部分在一个数字示例中结合了第一部分和第二部分的结果。在此示例中,我们为随机利率下的年金计算局部风险最小化对冲策略。我们假设保险公司正试图通过交易各种到期的零息债券来对冲该产品。由于在这种情况下不可能进行完美对冲,因此我们(通过模拟)获得了因“对冲”而导致的成本分配。这种分布是相对于物理概率测度而言的,而大多数现有文献认为它是在风险中性测度下进行的。

著录项

  • 作者

    Pansera, Jerome.;

  • 作者单位

    The University of Iowa.;

  • 授予单位 The University of Iowa.;
  • 学科 Mathematics.;Economics Finance.
  • 学位 Ph.D.
  • 年度 2008
  • 页码 306 p.
  • 总页数 306
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 数学;财政、金融;
  • 关键词

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