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Related papers: On a Stable Method for Option Pricing: Discontinuo…

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We introduce an automatic variationally stable analysis (AVS) for finite element (FE) computations of scalar-valued convection-diffusion equations with non-constant and highly oscillatory coefficients. In the spirit of least squares FE…

Numerical Analysis · Mathematics 2019-04-16 Victor M. Calo , Albert Romkes , Eirik Valseth

In this paper, a new stabilized discontinuous Galerkin method within a new function space setting is introduced, which involves an extra stabilization term on the normal fluxes across the element interfaces. It is different from the general…

Numerical Analysis · Mathematics 2014-11-25 Zhihao Ge , Jiwei Cao

This paper develops general approaches for pricing various types of American-style Parisian options (down-in/-out, perpetual/finite-maturity) with general payoff functions based on continuous-time Markov chain (CTMC) approximation under…

Computational Finance · Quantitative Finance 2025-03-17 Yuhao Liu , Nian Yang , Gongqiu Zhang

This work presents and compares efficient implementations of high-order discontinuous Galerkin methods: a modal matrix-free discontinuous Galerkin (DG) method, a hybridizable discontinuous Galerkin (HDG) method, and a primal formulation of…

Computational Physics · Physics 2018-12-14 Matteo Franciolini , Krzysztof Fidkowski , Andrea Crivellini

We analyze Galerkin discretizations of a new well-posed mixed space-time variational formulation of parabolic PDEs. For suitable pairs of finite element trial spaces, the resulting Galerkin operators are shown to be uniformly stable. The…

Numerical Analysis · Mathematics 2020-02-07 Rob Stevenson , Jan Westerdiep

Deep learning for option pricing has emerged as a novel methodology for fast computations with applications in calibration and computation of Greeks. However, many of these approaches do not enforce any no-arbitrage conditions, and the…

Computational Finance · Quantitative Finance 2020-07-22 Marc Chataigner , Stéphane Crépey , Matthew Dixon

Design of modern nanostructured semiconductor devices often calls for simulation tools capable of modeling arbitrarily-shaped multiscale geometries. In this work, to this end, a discontinuous Galerkin (DG) method-based framework is…

Computational Physics · Physics 2020-02-03 Liang Chen , Hakan Bagci

Deep neural networks are powerful tools for approximating functions, and they are applied to successfully solve various problems in many fields. In this paper, we propose a neural network-based numerical method to solve partial differential…

Numerical Analysis · Mathematics 2022-02-01 Yong Shang , Fei Wang , Jingbo Sun

In this work we present an analytical model, based on the path-integral formalism of Statistical Mechanics, for pricing options using first-passage time problems involving both fixed and deterministically moving absorbing barriers under…

Mathematical Finance · Quantitative Finance 2018-04-24 Andre Catalao , Rogerio Rosenfeld

In this paper, a variant of discretization of the van Roosbroeck equations in the equilibrium state with the Composite Discontinuous Galerkin Method for the rectangular domain is discussed. It is based on Symmetric Interior Penalty Galerkin…

Numerical Analysis · Mathematics 2020-01-16 Konrad Sakowski , Leszek Marcinkowski , Pawel Strak , Pawel Kempisty , Stanislaw Krukowski

The two-fluid plasma model has a wide range of timescales which must all be numerically resolved regardless of the timescale on which plasma dynamics occurs. The answer to solving numerically stiff systems is generally to utilize…

Numerical Analysis · Mathematics 2024-05-06 Andrew Ho , Uri Shumlak

Entropy stable discontinuous Galerkin (DG) methods improve the robustness of high order DG simulations of nonlinear conservation laws. These methods yield a semi-discrete entropy inequality, and rely on an algebraic flux differencing…

Numerical Analysis · Mathematics 2025-07-03 Jesse Chan

An implicit high-order discontinuous Galerkin (DG) method is developed to find steady-state solution of rarefied gas flow described by the Boltzmann equation with full collision operator. In the physical space, velocity distribution…

Computational Physics · Physics 2019-01-08 Wei Su , Peng Wang , Yonghao Zhang , Lei Wu

In this paper, we develop a new discontinuous Galerkin method for solving several types of partial differential equations (PDEs) with high order spatial derivatives. We combine the advantages of local discontinuous Galerkin (LDG) method and…

Numerical Analysis · Mathematics 2020-03-13 Qi Tao , Yan Xu , Chi-Wang Shu

One popular approach to option pricing in L\'evy models is through solving the related partial integro differential equation (PIDE). For the numerical solution of such equations powerful Galerkin methods have been put forward e.g. by Hilber…

Computational Finance · Quantitative Finance 2016-03-29 Maximilian Gaß , Kathrin Glau

The discontinuous Galerkin (DG) method is an established method for computing approximate solutions of partial differential equations in many applications. Unlike continuous finite elements, in DG methods, numerical fluxes are used to…

Numerical Analysis · Mathematics 2019-12-02 Kenneth Duru , Leonhard Rannabauer , Alice-Agnes Gabriel , Heiner Igel

We develop and analyze an ultraweak formulation of linear PDEs in nondivergence form where the coefficients satisfy the Cordes condition. Based on the ultraweak formulation we propose discontinuous Petrov--Galerkin (DPG) methods. We…

Numerical Analysis · Mathematics 2019-08-27 Thomas Führer

A novel approach for the stabilization of the Spectral-Volume (SV) method based on Dafermos' entropy rate criterion is presented. The method is an adaption of an already existing approach for the stabilization of the Discontinuous-Galerkin…

Numerical Analysis · Mathematics 2025-02-12 Lena Schadt

This study investigates enhancing option pricing by extending the Black-Scholes model to include stochastic volatility and interest rate variability within the Partial Differential Equation (PDE). The PDE is solved using the finite…

Numerical Analysis · Mathematics 2025-04-15 Nikhil Shivakumar Nayak

A new method for stochastic control based on neural networks and using randomisation of discrete random variables is proposed and applied to optimal stopping time problems. The method models directly the policy and does not need the…

Computational Finance · Quantitative Finance 2021-01-11 Thomas Deschatre , Joseph Mikael