摘要翻译：
许多种类的不确定因素可能会影响一个经济，例如经济、政治和环境方面的不确定因素。我们用L\'evy过程的随机混合模型来模拟不确定性对经济及其相关金融市场的总体影响。我们假设市场参与者只通过基于噪声市场信息的最佳估计来观察随机混合。不完全信息的概念引入了随机滤波理论的一个元素来构造我们所说的“滤波Esscher鞅”。我们利用这个鞅族建立了定价核模型。我们检验了债券价格模型的例子，我们表明随机混合物的选择对模型的动力学和相关收益率曲线中观察到的运动类型有显著的影响。分析了参数敏感性，推导了期权价格过程。我们通过考虑加权热核方法扩展了一类定价核模型，并建立了由混合马尔可夫过程驱动的模型。
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英文标题：
《Randomised Mixture Models for Pricing Kernels》
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作者：
Andrea Macrina, Priyanka A. Parbhoo
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最新提交年份：
2011
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：General Finance        一般财务
分类描述：Development of general quantitative methodologies with applications in finance
通用定量方法的发展及其在金融中的应用
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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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英文摘要：
  Numerous kinds of uncertainties may affect an economy, e.g. economic, political, and environmental ones. We model the aggregate impact by the uncertainties on an economy and its associated financial market by randomised mixtures of L\'evy processes. We assume that market participants observe the randomised mixtures only through best estimates based on noisy market information. The concept of incomplete information introduces an element of stochastic filtering theory in constructing what we term "filtered Esscher martingales". We make use of this family of martingales to develop pricing kernel models. Examples of bond price models are examined, and we show that the choice of the random mixture has a significant effect on the model dynamics and the types of movements observed in the associated yield curves. Parameter sensitivity is analysed and option price processes are derived. We extend the class of pricing kernel models by considering a weighted heat kernel approach, and develop models driven by mixtures of Markov processes.
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PDF链接：
https://arxiv.org/pdf/1112.2059