On Valuation with Stochastic Proportional Hazard Models in Finance

On Valuation with Stochastic Proportional Hazard Models in Finance
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金融中随机比例风险模型的估值

DOI:
10.1142/s0219024913500179
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发表时间:
2013
影响因子:
0.5
通讯作者:
A. Yamazaki
A. Yamazaki
中科院分区:
--
文献类型:
--
作者:
Yamanoi;J;下木なつみ・藤村美穂・竹内和雄;A. Yamazaki

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虽然比例风险模型被认为在分析和估计金融事件风险方面具有统计意义,但现有的分析处理估值问题的文献非常有限。本文采用连续时间环境下的比例风险模型,对估值问题进行了分析处理。这些公式基于广义Edgeworth展开式,给出了估值问题的近似解,广泛适用于评估各种金融产品,如公司债券、信用衍生品、抵押贷款支持证券、储蓄账户和定期存款。此外,这些公式还适用于不仅具有连续过程(例如,高斯过程、仿射过程和二次高斯过程)而且具有不连续过程(例如,L和时变Lévy过程)作为随机协变量的比例风险模型。通过数值算例表明,利用闭合公式等公式可以快速得到非常精确的数值。
While the proportional hazard model is recognized to be statistically meaningful for analyzing and estimating financial event risks, the existing literature that analytically deals with the valuation problems is very limited. In this paper, adopting the proportional hazard model in continuous time setting, we provide an analytical treatment for the valuation problems. The derived formulas, which are based on the generalized Edgeworth expansion and give approximate solutions to the valuation problems, are widely useful for evaluating a variety of financial products such as corporate bonds, credit derivatives, mortgage-backed securities, saving accounts and time deposits. Furthermore, the formulas are applicable to the proportional hazard model having not only continuous processes (e.g., Gaussian, affine, and quadratic Gaussian processes) but also discontinuous processes (e.g., Lévy and time-changed Lévy processes) as stochastic covariates. Through numerical examples, it is demonstrated that very accurate values can be quickly obtained by the formulas such as a closed-form formula.
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