7 papers
Computing XVA for American basket derivatives by Machine Learning techniques
Ludovic Goudenege, Andrea Molent, Antonino Zanette
Total value adjustment (XVA) is the change in value to be added to the price of a derivative to account for the bilateral default risk and the funding costs. In this paper, we comp…
Moving average options: Machine Learning and Gauss-Hermite quadrature for a double non-Markovian problem
Ludovic Goudenège, Andrea Molent, Antonino Zanette
Evaluating moving average options is a tough computational challenge for the energy and commodity market as the payoff of the option depends on the prices of a certain underlying o…
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…
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…
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…
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…