英文标题：
《Importance sampling for jump processes and applications to finance》
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作者：
Laetitia Badouraly Kassim (LJK), J\\\'er\\^ome Lelong (LJK), Imane
Loumrhari (LJK)
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最新提交年份：
2013
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英文摘要：
Adaptive importance sampling techniques are widely known for the Gaussian setting of Brownian driven diffusions. In this work, we want to extend them to jump processes. Our approach relies on a change of the jump intensity combined with the standard exponential tilting for the Brownian motion. The free parameters of our framework are optimized using sample average approximation techniques. We illustrate the efficiency of our method on the valuation of financial derivatives in several jump models.
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中文摘要：
自适应重要性抽样技术因布朗驱动扩散的高斯背景而广为人知。在这项工作中，我们希望将它们扩展到跳转进程。我们的方法依赖于跳跃强度的变化以及布朗运动的标准指数倾斜。我们使用样本平均近似技术优化了框架的自由参数。我们在几个跳跃模型中说明了我们的方法对金融衍生品估值的有效性。
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分类信息：

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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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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一级分类：Quantitative Finance 数量金融学
二级分类：Pricing of Securities 证券定价
分类描述：Valuation and hedging of financial securities, their derivatives, and structured products
金融证券及其衍生产品和结构化产品的估值和套期保值
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