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Bibliographic Details
Main Authors: Friz, Peter K., Gatheral, Jim
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2406.16131
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author Friz, Peter K.
Gatheral, Jim
author_facet Friz, Peter K.
Gatheral, Jim
contents The skew-stickiness-ratio (SSR), examined in detail by Bergomi in his book, is critically important to options traders, especially market makers. We present a model-free expression for the SSR in terms of the characteristic function. In the diffusion setting, it is well-known that the short-term limit of the SSR is 2; a corollary of our results is that this limit is $H+3/2$ where $H$ is the Hurst exponent of the volatility process. The general formula for the SSR simplifies and becomes particularly tractable in the affine forward variance case. We explain the qualitative behavior of the SSR with respect to the shape of the forward variance curve, and thus also path-dependence of the SSR.
format Preprint
id arxiv_https___arxiv_org_abs_2406_16131
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Computing the SSR
Friz, Peter K.
Gatheral, Jim
Mathematical Finance
Computational Finance
The skew-stickiness-ratio (SSR), examined in detail by Bergomi in his book, is critically important to options traders, especially market makers. We present a model-free expression for the SSR in terms of the characteristic function. In the diffusion setting, it is well-known that the short-term limit of the SSR is 2; a corollary of our results is that this limit is $H+3/2$ where $H$ is the Hurst exponent of the volatility process. The general formula for the SSR simplifies and becomes particularly tractable in the affine forward variance case. We explain the qualitative behavior of the SSR with respect to the shape of the forward variance curve, and thus also path-dependence of the SSR.
title Computing the SSR
topic Mathematical Finance
Computational Finance
url https://arxiv.org/abs/2406.16131