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Enhancing Valuation of Variable Annuities in Lévy Models with Stochastic Interest Rate
This paper extends the valuation and optimal surrender framework for variable annuities with guaranteed minimum benefits in a L\'evy equity market environment by incorporating a stochastic interest rate described by the Hull-White model.
Backward Hedging for American Options with Transaction Costs
In this article, we introduce an algorithm called Backward Hedging, designed for hedging European and American options while considering transaction costs.
Computing XVA for American basket derivatives by Machine Learning techniques
Moreover, the use of numerical techniques, such as control variates, turns out to be a powerful tool to improve the accuracy of the proposed methods.
Moving average options: Machine Learning and Gauss-Hermite quadrature for a double non-Markovian problem
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 observed on a moving window so, when a long window is considered, the pricing problem becomes high dimensional.
Machine Learning for Pricing American Options in High-Dimensional Markovian and non-Markovian models
The two methods mainly differ in the approach used to compute the continuation value: a single step of binomial tree or integration according to the probability density of the process.
Taxation of a GMWB Variable Annuity in a Stochastic Interest Rate Model
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 better modeling of the financial cost of these insurance products.
