英文标题：
《A regularity structure for rough volatility》
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作者：
Christian Bayer, Peter K. Friz, Paul Gassiat, Joerg Martin, Benjamin
  Stemper
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最新提交年份：
2017
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英文摘要：
  A new paradigm recently emerged in financial modelling: rough (stochastic) volatility, first observed by Gatheral et al. in high-frequency data, subsequently derived within market microstructure models, also turned out to capture parsimoniously key stylized facts of the entire implied volatility surface, including extreme skews that were thought to be outside the scope of stochastic volatility. On the mathematical side, Markovianity and, partially, semi-martingality are lost. In this paper we show that Hairer\'s regularity structures, a major extension of rough path theory, which caused a revolution in the field of stochastic partial differential equations, also provides a new and powerful tool to analyze rough volatility models.
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中文摘要：
最近，金融建模中出现了一种新的范式：Gatherel等人首先观察到的粗糙（随机）波动率。在高频数据中，随后在市场微观结构模型中衍生出来的数据，也被证明能够捕捉整个隐含波动率表面的关键风格化事实，包括被认为不在随机波动率范围内的极端偏斜。在数学方面，马尔可夫性和部分的半马提尼性都消失了。本文表明，Haier正则结构是粗糙路径理论的一个重要扩展，它在随机偏微分方程领域引起了一场革命，也为分析粗糙波动率模型提供了一个新的有力工具。
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分类信息：

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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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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