Semi-Static Variance-Optimal Hedging in Stochastic Volatility Models with Fourier Representation

TL;DR

This paper develops a Fourier-based method for variance-optimal semi-static hedging in complex stochastic volatility models, enabling explicit strategies for derivatives like variance swaps in both affine and non-affine models.

Contribution

It introduces a Fourier approach to derive explicit formulas for hedging errors and strategies in multidimensional stochastic volatility models, including non-affine cases.

Findings

Explicit formulas for hedging errors and strategies in stochastic volatility models.

Application to variance swaps in Heston and 3/2 models.

Extension of variance-optimal hedging to non-affine models.

Abstract

In a financial market model, we consider the variance-optimal semi-static hedging of a given contingent claim, a generalization of the classic variance-optimal hedging. To obtain a tractable formula for the expected squared hedging error and the optimal hedging strategy, we use a Fourier approach in a general multidimensional semimartingale factor model. As a special case, we recover existing results for variance-optimal hedging in affine stochastic volatility models. We apply the theory to set up a variance-optimal semi-static hedging strategy for a variance swap in both the Heston and the 3/2-model, the latter of which is a non-affine stochastic volatility model.