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20082026
most citedLikelihood-based non-Markovian models from molecular dynamics

57 citations · 266 across the 32 of their papers we have counts for

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Showing 2019Show all

5 papers · 1 filter

q-fin.CP2019

Machine Learning for Pricing American Options in High-Dimensional Markovian and non-Markovian models

Ludovic Goudenège, Andrea Molent, Antonino Zanette

In this paper we propose two efficient techniques which allow one to compute the price of American basket options. In particular, we consider a basket of assets that follow a multi…

q-fin.CP2019

Variance Reduction Applied to Machine Learning for Pricing Bermudan/American Options in High Dimension

Ludovic Goudenège, Andrea Molent, Antonino Zanette

In this paper we propose an efficient method to compute the price of multi-asset American options, based on Machine Learning, Monte Carlo simulations and variance reduction techniq…

q-fin.CP2019

Gaussian Process Regression for Pricing Variable Annuities with Stochastic Volatility and Interest Rate

Ludovic Goudenège, Andrea Molent, Antonino Zanette

In this paper we investigate price and Greeks computation of a Guaranteed Minimum Withdrawal Benefit (GMWB) Variable Annuity (VA) when both stochastic volatility and stochastic int…

math.PR2019

Stochastic phase field -Navier-Stokes vesicle-fluid interaction model

Ludovic Goudenège, Luigi Manca

We consider a stochastic perturbation of the phase field alpha-Navier-Stokes model with vesicle-fluid interaction. It consists in a system of nonlinear evolution partial differenti…

q-fin.GN2019★ 4 cited

Taxation of a GMWB Variable Annuity in a Stochastic Interest Rate Model

Andrea Molent

Modeling taxation of Variable Annuities has been frequently neglected but accounting for it can significantly improve the explanation of the withdrawal dynamics and lead to a bette…