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连接粗糙波动率模型与Lévy跳跃过程

文章 arXiv papers · 作者: Eduardo Abi Jaber et al.

总结

本研究通过具有快速均值回归和较大波动率波动的均值回归型Heston模型,联系粗糙波动率模型与跳跃模型。研究从超粗糙Heston设定出发,构造一维马尔可夫近似族。时间尺度参数控制回归速度及相关波动率行为,模型还允许Hurst参数超出其原始区间。

随着时间尺度趋近于零,作者根据Hurst参数推导出不同的显式极限状态。对于小于或等于指定阈值的参数值,极限是一族正态逆高斯型Lévy跳跃过程。数值示例显示,反转模型可以生成平值波动率偏斜,其形态类似粗糙、超粗糙和跳跃模型。所述证据为数值结果;文中未提供校准结果、市场样本或实证预测比较。

核心观点

  • 快速均值回归和较大的波动率波动构成粗糙波动率模型与跳跃模型之间的联系。
  • 一维反转型Heston族近似超粗糙Heston动态。
  • 随着反转时间尺度趋近于零,会出现不同的极限状态。
  • 对于足够低的Hurst参数值,极限是正态逆高斯型Lévy过程。
  • 数值示例显示,均值回归型、粗糙、超粗糙和跳跃模型在平值附近具有相似的波动率偏斜。

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# Reconciling rough volatility with jumps


# Reconciling rough volatility with jumps









We reconcile rough volatility models and jump models using a class of reversionary Heston models with fast mean reversions and large vol-of-vols. Starting from hyper-rough Heston models with a Hurst index $H \in (-1/2,1/2)$, we derive a Markovian approximating class of one dimensional reversionary Heston-type models. Such proxies encode a trade-off between an exploding vol-of-vol and a fast mean-reversion speed controlled by a reversionary time-scale $ε>0$ and an unconstrained parameter $H \in \mathbb R$. Sending $ε$ to 0 yields convergence of the reversionary Heston model towards different explicit asymptotic regimes based on the value of the parameter H. In particular, for $H \leq -1/2$, the reversionary Heston model converges to a class of Lévy jump processes of Normal Inverse Gaussian type. Numerical illustrations show that the reversionary Heston model is capable of generating at-the-money skews similar to the ones generated by rough, hyper-rough and jump models.

在遵守原作品许可的前提下,附作者信息全文展示。 许可协议: abstract CC0

此摘要由 Stratmill 研究智能体根据原文撰写,并非原文副本。