Local volatility under rough volatility

IF 1.6 3区 经济学 Q3 BUSINESS, FINANCE Mathematical Finance Pub Date : 2023-05-24 DOI:10.1111/mafi.12392
Florian Bourgey, Stefano De Marco, Peter K. Friz, Paolo Pigato
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引用次数: 4

Abstract

Several asymptotic results for the implied volatility generated by a rough volatility model have been obtained in recent years (notably in the small-maturity regime), providing a better understanding of the shapes of the volatility surface induced by rough volatility models, supporting their calibration power to SP500 option data. Rough volatility models also generate a local volatility surface, via the so-called Markovian projection of the stochastic volatility. We complement the existing results on implied volatility by studying the asymptotic behavior of the local volatility surface generated by a class of rough stochastic volatility models, encompassing the rough Bergomi model. Notably, we observe that the celebrated “1/2 skew rule” linking the short-term at-the-money skew of the implied volatility to the short-term at-the-money skew of the local volatility, a consequence of the celebrated “harmonic mean formula” of [Berestycki et al. (2002). Quantitative Finance, 2, 61–69], is replaced by a new rule: the ratio of the at-the-money implied and local volatility skews tends to the constant 1 / ( H + 3 / 2 ) $1/(H + 3/2)$ (as opposed to the constant 1/2), where H is the regularity index of the underlying instantaneous volatility process.

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粗波动下的局部波动
近年来,已经获得了粗糙波动率模型产生的隐含波动率的几个渐近结果(特别是在小期限制度中),提供了对粗糙波动率模型引起的波动率表面形状的更好理解,支持它们对SP500期权数据的校准能力。粗糙波动模型也通过所谓的随机波动的马尔可夫投影生成局部波动面。通过研究包含粗糙Bergomi模型的一类粗糙随机波动率模型所产生的局部波动率曲面的渐近行为,对隐含波动率的已有结果进行了补充。值得注意的是,我们观察到著名的“1/2倾斜规则”将隐含波动率的短期货币倾斜与当地波动率的短期货币倾斜联系起来,这是著名的“调和平均公式”的结果[Berestycki等人(2002)。《定量金融》,2,61-69],被一个新规则所取代:货币隐含波动率和本地波动率的比值趋于常数1/(H+3/2)$1/(H +3/2)$(而不是常数1/2),其中H是潜在瞬时波动过程的规律性指数。
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来源期刊
Mathematical Finance
Mathematical Finance 数学-数学跨学科应用
CiteScore
4.10
自引率
6.20%
发文量
27
审稿时长
>12 weeks
期刊介绍: Mathematical Finance seeks to publish original research articles focused on the development and application of novel mathematical and statistical methods for the analysis of financial problems. The journal welcomes contributions on new statistical methods for the analysis of financial problems. Empirical results will be appropriate to the extent that they illustrate a statistical technique, validate a model or provide insight into a financial problem. Papers whose main contribution rests on empirical results derived with standard approaches will not be considered.
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