Modelling stochastic skew of FX options using SLV models with stochastic spot/vol correlation and correlated jumps

Andrey Itkin ()

Applied Mathematical Finance, 2017, vol. 24, issue 6, 485-519

Abstract: It is known that the implied volatility skew of Forex (FX) options demonstrates a stochastic behaviour which is called stochastic skew. In this paper, we create stochastic skew by assuming the spot/instantaneous variance (InV) correlation to be stochastic. Accordingly, we consider a class of Stochastic Local Volatility (SLV) models with stochastic correlation where all drivers – the spot, InV and their correlation – are modelled by processes. We assume all diffusion components to be fully correlated, as well as all jump components. A new fully implicit splitting finite-difference scheme is proposed for solving forward PIDE which is used when calibrating the model to market prices of the FX options with different strikes and maturities. The scheme is unconditionally stable, of second order of approximation in time and space, and achieves a linear complexity in each spatial direction. The results of simulation obtained by using this model demonstrate the capacity of the presented approach in modelling stochastic skew.

Date: 2017
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Working Paper: Modeling stochastic skew of FX options using SLV models with stochastic spot/vol correlation and correlated jumps (2017)
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DOI: 10.1080/1350486X.2017.1409641

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