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Bibliographic Details
Main Authors: Joseph, Benjamin, Loeper, Gregoire, Obloj, Jan
Format: Preprint
Published: 2023
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Online Access:https://arxiv.org/abs/2305.00200
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author Joseph, Benjamin
Loeper, Gregoire
Obloj, Jan
author_facet Joseph, Benjamin
Loeper, Gregoire
Obloj, Jan
contents We develop a non-parametric, semimartingale optimal transport, calibration methodology for local volatility models with stochastic interest rate. The method finds a fully calibrated model which is the closest, in a way that can be defined by a general cost function, to a given reference model. We establish a general duality result which allows to solve the problem by optimising over solutions to a second order fully non-linear Hamilton-Jacobi-Bellman equation. Our methodology is analogous to Guo, Loeper, and Wang, 2022 and Guo, Loeper, Obloj, et al., 2022a but features a novel element of solving for discounted densities, or sub-probability measures. As an example, we apply the method to a sequential calibration problem, where a Vasicek model is already given for the interest rates and we seek to calibrate a stock price's local volatility model with volatility coefficient depending on time, the underlying and the short rate process, and the two processes driven by possibly correlated Brownian motions. The equity model is calibrated to any number of European options prices.
format Preprint
id arxiv_https___arxiv_org_abs_2305_00200
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Calibration of Local Volatility Models with Stochastic Interest Rates using Optimal Transport
Joseph, Benjamin
Loeper, Gregoire
Obloj, Jan
Mathematical Finance
Optimization and Control
We develop a non-parametric, semimartingale optimal transport, calibration methodology for local volatility models with stochastic interest rate. The method finds a fully calibrated model which is the closest, in a way that can be defined by a general cost function, to a given reference model. We establish a general duality result which allows to solve the problem by optimising over solutions to a second order fully non-linear Hamilton-Jacobi-Bellman equation. Our methodology is analogous to Guo, Loeper, and Wang, 2022 and Guo, Loeper, Obloj, et al., 2022a but features a novel element of solving for discounted densities, or sub-probability measures. As an example, we apply the method to a sequential calibration problem, where a Vasicek model is already given for the interest rates and we seek to calibrate a stock price's local volatility model with volatility coefficient depending on time, the underlying and the short rate process, and the two processes driven by possibly correlated Brownian motions. The equity model is calibrated to any number of European options prices.
title Calibration of Local Volatility Models with Stochastic Interest Rates using Optimal Transport
topic Mathematical Finance
Optimization and Control
url https://arxiv.org/abs/2305.00200