170 citations · 345 across the 27 of their papers we have counts for
9 papers · 1 filter
Shapley-based Structural Analysis of Neural Calibration for Stochastic Volatility Models
Shaïn Afzali, Serena Della Corte, Antonis Papapantoleon
Neural network-based approaches have emerged as efficient alternatives to traditional optimization-based procedures for the calibration of stochastic volatility models. However, ex…
Quasi-Monte Carlo with Domain Transformation for Efficient Fourier Pricing of Multi-Asset Options
Christian Bayer, Chiheb Ben Hammouda, Antonis Papapantoleon +2
Efficiently pricing multi-asset options poses a significant challenge in quantitative finance. Fourier methods leverage the regularity properties of the integrand in the Fourier do…
A time-stepping deep gradient flow method for option pricing in (rough) diffusion models
Antonis Papapantoleon, Jasper Rou
We develop a novel deep learning approach for pricing European options in diffusion models, that can efficiently handle high-dimensional problems resulting from Markovian approxima…
A deep implicit-explicit minimizing movement method for option pricing in jump-diffusion models
Emmanuil H. Georgoulis, Antonis Papapantoleon, Costas Smaragdakis
We develop a novel deep learning approach for pricing European basket options written on assets that follow jump-diffusion dynamics. The option pricing problem is formulated as a p…
Machine learning for option pricing: an empirical investigation of network architectures
Serena Della Corte, Laurens Van Mieghem, Antonis Papapantoleon +1
We consider the supervised learning problem of learning the price of an option or the implied volatility given appropriate input data (model parameters) and corresponding output da…
Optimal Damping with Hierarchical Adaptive Quadrature for Efficient Fourier Pricing of Multi-Asset Options in Lévy Models
Michael Samet, Christian Bayer, Chiheb Ben Hammouda +2
Efficiently pricing multi-asset options is a challenging problem in quantitative finance. When the characteristic function is available, Fourier-based methods are competitive compa…