英文标题:
《Multivariate Subordination using Generalised Gamma Convolutions with
  Applications to V.G. Processes and Option Pricing》
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作者:
Boris Buchmann, Benjamin Kaehler, Ross Maller, Alexander Szimayer
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最新提交年份:
2016
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英文摘要:
  We unify and extend a number of approaches related to constructing multivariate Variance-Gamma (V.G.) models for option pricing. An overarching model is derived by subordinating multivariate Brownian motion to a subordinator from the Thorin (1977) class of generalised Gamma convolution subordinators. A class of models due to Grigelionis (2007), which contains the well-known Madan-Seneta V.G. model, is of this type, but our multivariate generalization is considerably wider, allowing in particular for processes with infinite variation and a variety of dependencies between the underlying processes. Multivariate classes developed by P\\\'erez-Abreu and Stelzer (2012) and Semeraro (2008) and Guillaume (2013) are also submodels. The new models are shown to be invariant under Esscher transforms, and quite explicit expressions for canonical measures (and transition densities in some cases) are obtained, which permit applications such as option pricing using PIDEs or tree based methodologies. We illustrate with best-of and worst-of European and American options on two assets. 
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中文摘要:
我们统一并扩展了许多与构建期权定价的多元方差伽马(V.G.)模型相关的方法。通过将多元布朗运动从属于Thorin(1977)类广义伽马卷积从属性,导出了一个总体模型。Grigelionis(2007)提出的一类模型,其中包含著名的Madan Seneta V.G.模型,属于这种类型,但我们的多元泛化要广泛得多,特别是考虑到具有无限变化的过程以及基础过程之间的各种依赖性。Pèrez-Abreu和Stelzer(2012年)、Semeraro(2008年)和Guillaume(2013年)开发的多变量类也是子模型。新模型在Esscher变换下是不变性的,并且获得了规范测度(在某些情况下是转移密度)的非常明确的表达式,这允许使用PIDE或基于树的方法进行期权定价等应用。我们用欧洲和美国两种资产的最佳和最差选择来说明。
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分类信息:
一级分类:Quantitative Finance        数量金融学
二级分类:Mathematical Finance        数学金融学
分类描述:Mathematical and analytical methods of finance, including stochastic, probabilistic and functional analysis, algebraic, geometric and other methods
金融的数学和分析方法,包括随机、概率和泛函分析、代数、几何和其他方法
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一级分类:Mathematics        数学
二级分类:Probability        概率
分类描述:Theory and applications of probability and stochastic processes: e.g. central limit theorems, large deviations, stochastic differential equations, models from statistical mechanics, queuing theory
概率论与随机过程的理论与应用:例如中心极限定理,大偏差,随机微分方程,统计力学模型,排队论
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