英文标题：
《Rough volatility: evidence from option prices》
---
作者：
Giulia Livieri, Saad Mouti, Andrea Pallavicini and Mathieu Rosenbaum
---
最新提交年份：
2017
---
英文摘要：
It has been recently shown that spot volatilities can be very well modeled by rough stochastic volatility type dynamics. In such models, the log-volatility follows a fractional Brownian motion with Hurst parameter smaller than 1/2. This result has been established using high frequency volatility estimations from historical price data. We revisit this finding by studying implied volatility based approximations of the spot volatility. Using at-the-money options on the S&P500 index with short maturity, we are able to confirm that volatility is rough. The Hurst parameter found here, of order 0.3, is slightly larger than that usually obtained from historical data. This is easily explained from a smoothing effect due to the remaining time to maturity of the considered options.
---
中文摘要：
最近的研究表明，粗随机波动率类型动力学可以很好地模拟现货波动率。在这些模型中，对数波动率遵循分数布朗运动，赫斯特参数小于1/2。这一结果是利用历史价格数据的高频波动率估计得出的。我们通过研究基于隐含波动率的现货波动率近似值来重新审视这一发现。使用短期到期的标准普尔500指数的货币期权，我们可以确认波动性是粗糙的。此处发现的赫斯特参数为0.3级，略大于通常从历史数据中获得的参数。这很容易从所考虑的期权的剩余到期时间所产生的平滑效应来解释。
---
分类信息：

一级分类：Quantitative Finance 数量金融学
二级分类：Statistical Finance 统计金融
分类描述：Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
--
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：
-->