Tootfinder

A time-stepping deep gradient flow method for option pricing in (rough) diffusion models
Antonis Papapantoleon, Jasper Rou
https://arxiv.org/abs/2403.00746

A time-stepping deep gradient flow method for option pricing in (rough) diffusion models
We develop a novel deep learning approach for pricing European options in diffusion models, that can efficiently handle high-dimensional problems resulting from Markovian approximations of rough volatility models. The option pricing partial differential equation is reformulated as an energy minimization problem, which is approximated in a time-stepping fashion by deep artificial neural networks. The proposed scheme respects the asymptotic behavior of option prices for large levels of moneyness,…

Improved model-free bounds for multi-asset options using option-implied information and deep learning
Evangelia Dragazi, Shuaiqiang Liu, Antonis Papapantoleon
https://arxiv.org/abs/2404.02343

Improved model-free bounds for multi-asset options using option-implied information and deep learning
We consider the computation of model-free bounds for multi-asset options in a setting that combines dependence uncertainty with additional information on the dependence structure. More specifically, we consider the setting where the marginal distributions are known and partial information, in the form of known prices for multi-asset options, is also available in the market. We provide a fundamental theorem of asset pricing in this setting, as well as a superhedging duality that allows to transf…

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Background discrimination with a Micromegas detector prototype and veto system for BabyIAXO
K. Altenm\"uller, J. F. Castel, S. Cebri\'an, T. Dafni, D. D\'iez-Iba\~nez, A. Ezquerro, E. Ferrer-Ribas, J. Galan, J. Galindo, J. A. Garc\'ia, A. Giganon, C. Goblin, I. G. Irastorza, C. Loiseau, G. Luz\'on, X. F. Navick, C. Margalejo, H. Mirallas, L. Obis, A. Ortiz de Sol\'orzano, T. Papaevangelou, O. P\'erez, A. Quintana, J. Ruz, J. K. Vogel

Background discrimination with a Micromegas detector prototype and veto system for BabyIAXO
In this paper we present measurements performed with a Micromegas X-ray detector setup. The detector is a prototype in the context of the BabyIAXO helioscope, which is under construction to search for an emission of the hypothetical axion particle from the sun. An important component of such a helioscope is a low background X-ray detector with a high efficiency in the 1-10 keV energy range. The goal of the measurement was to study techniques for background discrimination. In addition to common …

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Quasi-Monte Carlo for Efficient Fourier Pricing of Multi-Asset Options
Christian Bayer, Chiheb Ben Hammouda, Antonis Papapantoleon, Michael Samet, Ra\'ul Tempone
https://arxiv.org/abs/2403.02832

Quasi-Monte Carlo for Efficient Fourier Pricing of Multi-Asset Options
Efficiently pricing multi-asset options poses a significant challenge in quantitative finance. The Monte Carlo (MC) method remains the prevalent choice for pricing engines; however, its slow convergence rate impedes its practical application. Fourier methods leverage the knowledge of the characteristic function to accurately and rapidly value options with up to two assets. Nevertheless, they face hurdles in the high-dimensional settings due to the tensor product (TP) structure of commonly emplo…