3 papers
q-fin.CP2026
Calibrating the Heston model with deep differential networks
Giovanni Amici, Marco Morandotti, Chen Zhang
We propose a gradient-based deep learning framework to calibrate the Heston option pricing model (Heston, 1993). Our neural network, henceforth deep differential network (DDN), lea…
math.OC2026
Stratified adaptive sampling for derivative-free stochastic trust-region optimization
Giovanni Amici, Sara Shashaani, Pranav Jain
There is emerging evidence that trust-region (TR) algorithms are very effective at solving derivative-free nonconvex stochastic optimization problems in which the objective functio…
q-fin.PR2025
Multivariate Lévy models: calibration and pricing
Giovanni Amici, Paolo Brandimarte, Francesco Messeri +1
The goal of this paper is to investigate how the marginal and dependence structures of a variety of multivariate Lévy models affect calibration and pricing. To this aim, we study…