Thibaut Montes, PhD

Thibaut Montes, PhD

Senior Machine Learning Researcher

Publications

Stationary Heston model: Calibration and Pricing of exotics using Product Recursive Quantization

Published in Quantitative Finance, 2020

A major drawback of the Standard Heston model is that its implied volatility surface does not produce a steep enough smile when looking at short maturities. For that reason, we introduce the Stationary Heston model where we replace the deterministic initial condition of the volatility by its invariant measure and show, based on calibrated parameters, that this model produce a steeper smile for short maturities than the Standard Heston model. We also present numerical solution based on Product Recursive Quantization for the evaluation of exotic options (Bermudan and Barrier options).

Download here

Quantization-based Bermudan option pricing in the $FX$ world

Published in Journal of Computational Finance, 2019

This paper proposes two numerical solution based on Product Optimal Quantization for the pricing of Foreign Exchange (FX) linked long term Bermudan options e.g. Bermudan Power Reverse Dual Currency options, where we take into account stochastic domestic and foreign interest rates on top of stochastic FX rate, hence we consider a 3-factor model.

Download here

New Weak Error bounds and expansions for Optimal Quantization

Published in Journal of Computational and Applied Mathematics, 2019

We introduce new error bounds in dimension one for optimal quantization based cubature formula for a class of function that allows us to reach weak error of order two. This new results use deeply the local behaviors of optimal quantizers as well as Lr-Ls mismatch distortion results.

Download here