英文标题：
《Markov cubature rules for polynomial processes》
---
作者：
Damir Filipovi\\\'c, Martin Larsson, Sergio Pulido
---
最新提交年份：
2019
---
英文摘要：
We study discretizations of polynomial processes using finite state Markov processes satisfying suitable moment matching conditions. The states of these Markov processes together with their transition probabilities can be interpreted as Markov cubature rules. The polynomial property allows us to study such rules using algebraic techniques. Markov cubature rules aid the tractability of path-dependent tasks such as American option pricing in models where the underlying factors are polynomial processes.
---
中文摘要：
我们利用满足适当矩匹配条件的有限状态马尔可夫过程来研究多项式过程的离散化。这些马尔可夫过程的状态及其转移概率可以解释为马尔可夫容积规则。多项式性质允许我们使用代数技术研究此类规则。马尔可夫容积规则有助于路径相关任务的可处理性，例如在潜在因素为多项式过程的模型中的美式期权定价。
---
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
--
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
--

---
PDF下载：
-->