19 citations · 39 across the 14 of their papers we have counts for
12 papers · 1 filter
Adaptive singular-point method for pricing and hedging surrenderable equity-linked contracts
Andrea Molent, Marcellino Gaudenzi
We propose a deterministic numerical method for pricing and hedging surrenderable equity-linked life-insurance contracts with periodic premiums and fund contributions, maturity and…
Neural Calibration of a Complete Market Model
Andrea Molent, Michel Vellekoop
We propose a neural calibration method to construct a recombining binomial tree directly from a set of given option prices. Rather than estimating a continuous option pricing funct…
Market-Informed Valuation of GMMB Riders with Surrender Options under a Heston Stochastic-Local Volatility Model
Ludovic Goudenege, Andrea Molent, Xiao Wei +1
We develop a market-informed valuation framework for guaranteed minimum maturity benefit (GMMB) riders with rational surrender under the Heston stochastic-local volatility (SLV) mo…
Leveraging Machine Learning for High-Dimensional Option Pricing within the Uncertain Volatility Model
Ludovic Goudenege, Andrea Molent, Antonino Zanette
This paper explores the application of Machine Learning techniques for pricing high-dimensional options within the framework of the Uncertain Volatility Model (UVM). The UVM is a r…
The Life Care Annuity: enhancing product features and refining pricing methods
G. Apicella, A. Molent, M. Gaudenzi
The state-of-the-art proposes Life Care Annuities, that have been recently designed as variable annuity contracts with Long-Term Care payouts and Guaranteed Lifelong Withdrawal Ben…
Backward Hedging for American Options with Transaction Costs
Ludovic Goudenège, Andrea Molent, Antonino Zanette
In this article, we introduce an algorithm called Backward Hedging, designed for hedging European and American options while considering transaction costs. The optimal strategy is…
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…
Computing Credit Valuation Adjustment solving coupled PIDEs in the Bates model
Ludovic Goudenège, Andrea Molent, Antonino Zanette
Credit value adjustment (CVA) is the charge applied by financial institutions to the counterparty to cover the risk of losses on a counterpart default event. In this paper we estim…