Hedging under rough volatility

TL;DR

This paper reviews hedging strategies in rough volatility models, introduces a general perfect hedging result with minimal assets, and demonstrates significant error reduction in real data back-tests using VIX options and variance swaps.

Contribution

It presents a novel theoretical result showing perfect hedging with just two assets in rough volatility models and validates it with empirical back-test improvements.

Findings

Almost complete bias removal in hedging errors

27% reduction in hedging error compared to traditional models

Effective hedging with only underlying and variance swap

Abstract

In this chapter we first briefly review the existing approaches to hedging in rough volatility models. Next, we present a simple but general result which shows that in a one-factor rough stochastic volatility model, any option may be perfectly hedged with a dynamic portfolio containing the underlying and one other asset such as a variance swap. In the final section we report the results of a back-test experiment using real data, where VIX options are hedged with a forward variance swap. In this experiment, using a rough volatility model allows to almost completely remove the bias and reduce the overall hedging error by a factor of 27% compared to traditional diffusion-based models.