Skip to main contentCBHChiheb Ben Hammouda
Menu
Get in touch

Latest news

Research, teaching, and
community updates.

New publications, emerging research, software, workshops, and other developments—kept separate from my speaking engagements and organizational activities.

13Recent updates
4Research themes represented
2025–26Current news window

News archive

Latest developments

01September 2026

Paper accepted in SIAM Journal on Financial Mathematics

“Quasi-Monte Carlo with Domain Transformation for Efficient Fourier Pricing of Multi-Asset Options,” with Christian Bayer, Antonis Papapantoleon, Michael Samet, and Raúl Tempone, has been accepted for publication in SIAM Journal on Financial Mathematics. The work develops a regularity-preserving domain transformation for randomized quasi-Monte Carlo integration in Fourier space, enabling efficient pricing of options with up to 15 underlying assets.

034 September 2026

ICCF 2026: two minisymposia and five collaborative presentations

At ICCF 2026 at the University of Oxford, I co-organized two minisymposia with Kees Oosterlee: one on stochastic control and learning for decisions under uncertainty in energy and finance, and one on transform methods for computational finance and risk management. The conference also featured five recent works with my students and collaborators, spanning multivariate shortfall risk, rough-Heston pricing, multi-asset option pricing, the damped SWIFT method, and intraday electricity trading.

0431 August 2026

Error-controlled multilevel quadrature for rough-Heston pricing

A new preprint develops single- and multilevel Gauss–Laguerre quadrature methods for Fourier pricing under the rough Heston model. The methods balance fractional-Riccati time-discretization error with Fourier-quadrature error and allocate computational work to meet a prescribed accuracy.

05September 2026

Serving on the Mathematical Institute Advisory Committee

Since September 2026, I have served on Utrecht University’s Mathematical Institute Advisory Committee, contributing to advice on research, education, staff policy, workload, finance, and institutional collaboration.

0627 July 2026

Filtered Markovian projection published in Statistics and Computing

The paper introduces a consistent dimensionality-reduction method for stochastic filtering in reaction networks, combining reduced-variance particle estimation with low-dimensional filtering equations to improve efficiency in large systems.

0723 July 2026

A damped SWIFT method for accurate and efficient European option pricing

A new preprint introduces exponential damping into the SWIFT framework, enabling direct frequency-domain coefficient computation, sharper truncation rules, and improved accuracy with fewer Fourier coefficients.

08June–July 2026

MCQMC and Bachelier World Congress 2026

At MCQMC 2026 in Edinburgh, I co-organized a minisymposium on Monte Carlo methods for stochastic reaction networks and presented Fourier–RQMC work on multivariate shortfall risk. At the Bachelier World Congress in Bologna, I co-organized minisymposia on energy markets and climate finance and on transform methods, and presented work on quasi-Monte Carlo domain transformations for multi-asset option pricing.

09May 2026

Mathematics and Machines: From Brown to Sustainable Finance

A four-day Lorentz Center workshop bringing together mathematical finance, machine learning, sustainable finance, and FinTech through mini-courses, invited talks, industry sessions, and collaborative discussion.

10April 2026

Data-driven stochastic control for renewable producers

A new preprint develops computational methods for intraday electricity trading, connecting stochastic optimal control with data-driven decision-making for renewable energy producers.

11March 2026

SigMA published in Neurocomputing

This work combines path signatures with multi-head attention to learn parameters in fractional Brownian motion-driven stochastic differential equations, balancing estimation accuracy with model complexity.

12February 2026

Fourier-RQMC methods for multivariate shortfall risk

This preprint develops single- and multi-level randomized quasi-Monte Carlo methods for systemic risk measurement and capital allocation before aggregation.

13November 2025

Neural networks for extreme storm-surge prediction

The study investigates data-driven alternatives to expensive hydrodynamic simulations. Weighted losses, convolutional layers, and look-back windows improve the representation of rare coastal extremes.

Related pages

Follow the work in more detail.

Complete publications Talks & recordings Academic activities