Calibration of Local-Stochastic and Path-Dependent Volatility Models to Vanilla and No-Touch Options
Abstract
We propose a generic calibration framework to both vanilla and no-touch options for a large class of continuous semi-martingale models. The method builds upon the forward partial integro-differential equation (PIDE) derived in Hambly et al. (2016), which allows fast computation of up-and-out call prices for the complete set of strikes, barriers and maturities. It also utilises a novel two-states particle method to estimate the Markovian projection of the variance onto the spot and running maximum. We detail a step-by-step procedure for a Heston-type local-stochastic volatility model with local vol-of-vol, as well as two path-dependent volatility models where the local volatility component depends on the running maximum. In numerical tests, we benchmark these new models against standard models for a set of EURUSD market data, all three models are seen to calibrate well within the market no-touch bid--ask.
Keywords
Cite
@article{arxiv.1911.00877,
title = {Calibration of Local-Stochastic and Path-Dependent Volatility Models to Vanilla and No-Touch Options},
author = {Alan Bain and Matthieu Mariapragassam and Christoph Reisinger},
journal= {arXiv preprint arXiv:1911.00877},
year = {2025}
}