ATM隐含了ADO-Heston模型的倾斜

Andrey Itkin
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引用次数: 0

摘要

本文类似于[P.]我们构建了粗糙的类赫斯顿波动模型的另一种马尔可夫近似——ado -赫斯顿模型。模型的特征函数CF是一个非定常三维偏微分方程,其中一些系数是时间t和赫斯特指数H的函数。为了复制市场隐含偏差的已知行为,我们对风险的市场价格进行明智的选择,然后找到对数价格和ATM隐含偏差的CF的封闭形式表达式。根据所提供的示例,我们声称ADO-Heston模型(这是一个纯粹的扩散模型,但具有方差过程的随机均值回归速度,或粗糙Heston模型的马尔可夫近似)能够(近似地)再现小$T$时香草隐含偏态的已知行为。我们得出结论,我们的隐含波动率倾斜曲线${\cal S}(T) \propto a(H) T^{b\cdot (H-1/2)}, \, b = const$的行为与自$b \ ne1 $以来的粗糙波动率模型并不完全相同,但似乎足够接近$T$的所有实际值。因此,所提出的马尔可夫模型能够复制相应的粗糙波动率模型的一些特性。对前向启动期权进行了类似的分析,我们发现,当$ t \到$s $时,前向启动期权的ATM隐含偏差可能在任意$s > t$时爆发。然而,这一结果与[E。Alos, D.G. Lorite, 2021]认为马尔可夫近似不能捕捉到这种行为,所以哪一个更接近现实的问题仍然存在。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The ATM implied skew in the ADO-Heston model
In this paper similar to [P. Carr, A. Itkin, 2019] we construct another Markovian approximation of the rough Heston-like volatility model - the ADO-Heston model. The characteristic function (CF) of the model is derived under both risk-neutral and real measures which is an unsteady three-dimensional PDE with some coefficients being functions of the time $t$ and the Hurst exponent $H$. To replicate known behavior of the market implied skew we proceed with a wise choice of the market price of risk, and then find a closed form expression for the CF of the log-price and the ATM implied skew. Based on the provided example, we claim that the ADO-Heston model (which is a pure diffusion model but with a stochastic mean-reversion speed of the variance process, or a Markovian approximation of the rough Heston model) is able (approximately) to reproduce the known behavior of the vanilla implied skew at small $T$. We conclude that the behavior of our implied volatility skew curve ${\cal S}(T) \propto a(H) T^{b\cdot (H-1/2)}, \, b = const$, is not exactly same as in rough volatility models since $b \ne 1$, but seems to be close enough for all practical values of $T$. Thus, the proposed Markovian model is able to replicate some properties of the corresponding rough volatility model. Similar analysis is provided for the forward starting options where we found that the ATM implied skew for the forward starting options can blow-up for any $s > t$ when $T \to s$. This result, however, contradicts to the observation of [E. Alos, D.G. Lorite, 2021] that Markovian approximation is not able to catch this behavior, so remains the question on which one is closer to reality.
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