Optimal transport for model calibration
Ivan Guo, Gregoire Loeper, Jan Obloj, Shiyi Wang
TL;DR
This paper surveys recent advances in using Optimal Transport for model calibration in finance, covering various models and options with practical algorithms and examples.
Contribution
It provides a comprehensive overview of Optimal Transport methods applied to model calibration, including new algorithms and diverse applications in finance.
Findings
Effective algorithms for calibration to European options
Successful calibration of local and stochastic volatility models
Demonstrated applicability on synthetic and real market data
Abstract
We provide a survey of recent results on model calibration by Optimal Transport. We present the general framework and then discuss the calibration of local, and local-stochastic, volatility models to European options, the joint VIX/SPX calibration problem as well as calibration to some path-dependent options. We explain the numerical algorithms and present examples both on synthetic and market data.
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