Zobrazeno 1 - 10
of 7 804
pro vyhledávání: '"A, Jacquier"'
In the present manuscript we address and solve for the first time a nonlocal discrete isoperimetric problem. We consider indeed a generalization of the classical perimeter, what we call a nonlocal bi-axial discrete perimeter, where, not only the exte
Externí odkaz:
http://arxiv.org/abs/2412.13005
Deep learning methods have become a widespread toolbox for pricing and calibration of financial models. While they often provide new directions and research results, their `black box' nature also results in a lack of interpretability. We provide a de
Externí odkaz:
http://arxiv.org/abs/2411.19317
We devise a novel method for nowcasting implied volatility based on neural operators. Better known as implied volatility smoothing in the financial industry, nowcasting of implied volatility means constructing a smooth surface that is consistent with
Externí odkaz:
http://arxiv.org/abs/2406.11520
We pose the problem of metastability for a three--state spin system with conservative dynamics. We consider the Blume--Capel model with the Kawasaki dynamics, we prove that, in a particular region of the parameter plane, the metastable state is the u
Externí odkaz:
http://arxiv.org/abs/2405.09198
Autor:
Vincent, Simon, Guittienne, Philippe, Quigley, Patrick, Sepulchre, Cyrille, Jacquier, Rémy, Bertizzolo, Robert, Baquero-Ruiz, Marcelo, Howling, Alan A., Furno, Ivo
A birdcage resonant helicon antenna is designed, mounted and tested in the toroidal device TORPEX. The birdcage resonant antenna is an alternative to the usual Boswell or half-helical antenna designs commonly used for $\sim$ 10 cm diameter helicon so
Externí odkaz:
http://arxiv.org/abs/2404.05441
One the one hand, rough volatility has been shown to provide a consistent framework to capture the properties of stock price dynamics both under the historical measure and for pricing purposes. On the other hand, market price of volatility risk is a
Externí odkaz:
http://arxiv.org/abs/2403.11897
Classical Physics-informed neural networks (PINNs) approximate solutions to PDEs with the help of deep neural networks trained to satisfy the differential operator and the relevant boundary conditions. We revisit this idea in the quantum computing re
Externí odkaz:
http://arxiv.org/abs/2312.14975
This article provides an understanding of Natural Language Processing techniques in the framework of financial regulation, more specifically in order to perform semantic matching search between rules and policy when no dataset is available for superv
Externí odkaz:
http://arxiv.org/abs/2311.08533
Quantum computing has recently appeared in the headlines of many scientific and popular publications. In the context of quantitative finance, we provide here an overview of its potential.
Comment: 5 pages
Comment: 5 pages
Externí odkaz:
http://arxiv.org/abs/2311.06621
Autor:
Gasteratos, Ioannis, Jacquier, Antoine
We study concentration properties for laws of non-linear Gaussian functionals on metric spaces. Our focus lies on measures with non-Gaussian tail behaviour which are beyond the reach of Talagrand's classical Transportation-Cost Inequalities (TCIs). M
Externí odkaz:
http://arxiv.org/abs/2310.05750