Calibration of Local-Stochastic Volatility Models by Optimal Transport
Mathematical Finance
2021-07-22 v4 Optimization and Control
Abstract
In this paper, we study a semi-martingale optimal transport problem and its application to the calibration of Local-Stochastic Volatility (LSV) models. Rather than considering the classical constraints on marginal distributions at initial and final time, we optimise our cost function given the prices of a finite number of European options. We formulate the problem as a convex optimisation problem, for which we provide a PDE formulation along with its dual counterpart. Then we solve numerically the dual problem, which involves a fully non-linear Hamilton-Jacobi-Bellman equation. The method is tested by calibrating a Heston-like LSV model with simulated data and foreign exchange market data.
Keywords
Cite
@article{arxiv.1906.06478,
title = {Calibration of Local-Stochastic Volatility Models by Optimal Transport},
author = {Ivan Guo and Gregoire Loeper and Shiyi Wang},
journal= {arXiv preprint arXiv:1906.06478},
year = {2021}
}