英文标题：
《On strong binomial approximation for stochastic processes and
  applications for financial modelling》
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作者：
Nikolai Dokuchaev
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最新提交年份：
2015
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英文摘要：
  This paper considers binomial approximation of continuous time stochastic processes. It is shown that, under some mild integrability conditions, a process can be approximated in mean square sense and in other strong metrics by binomial processes, i.e., by processes with fixed size binary increments at sampling points. Moreover, this approximation can be causal, i.e., at every time it requires only past historical values of the underlying process. In addition, possibility of approximation of solutions of stochastic differential equations by solutions of ordinary equations with binary noise is established. Some consequences for the financial modelling and options pricing models are discussed.
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中文摘要：
本文研究连续时间随机过程的二项式逼近。结果表明，在一些温和的可积条件下，一个过程可以用二项过程在均方意义上和其他强度量上进行近似，即在采样点用固定大小的二元增量过程进行近似。此外，这种近似可能是因果关系，也就是说，每次它只需要基础过程的过去历史值。此外，还建立了用含有二元噪声的常微分方程的解逼近随机微分方程解的可能性。讨论了金融模型和期权定价模型的一些后果。
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分类信息：

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：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：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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