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We formulate a new projection-based reduced-ordered modeling technique for non-linear dynamical systems. The proposed technique, which we refer to as the Adjoint Petrov-Galerkin (APG) method, is derived by decomposing the generalized…

Dynamical Systems · Mathematics 2019-08-30 Eric J. Parish , Christopher Wentland , Karthik Duraisamy

This paper develops some interior penalty $hp$-discontinuous Galerkin ($hp$-DG) methods for the Helmholtz equation in two and three dimensions. The proposed $hp$-DG methods are defined using a sesquilinear form which is not only…

Numerical Analysis · Mathematics 2009-07-21 Xiaobing Feng , Haijun Wu

We design, analyze, and implement a new conservative Discontinuous Galerkin (DG) method for the simulation of solitary wave solutions to the generalized Korteweg-de Vries (KdV) Equation. The key feature of our method is the conservation, at…

Numerical Analysis · Mathematics 2022-11-14 Yanlai Chen , Bo Dong , Rebecca Pereira

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…

Computational Finance · Quantitative Finance 2025-04-04 Antonis Papapantoleon , Jasper Rou

In this paper, we are concerned with a nonlinear optimal control problem of ordinary differential equations. We consider a discretization of the problem with the discontinuous Galerkin method with arbitrary order $r \in \mathbb{N}\cup…

Numerical Analysis · Mathematics 2020-05-25 Woocheol Choi , Young-Pil Choi

In this paper we propose and analyze an interior penalty discontinuous Galerkin (IP-DG) method using piecewise linear polynomials for the elastic Helmholtz equations with the first order absorbing boundary condition. It is proved that the…

Numerical Analysis · Mathematics 2015-01-23 Xiaobing Feng , Cody Lorton

This paper is devoted to the price-storage dynamics in natural gas markets. A novel stochastic path-dependent volatility model is introduced with path-dependence in both price volatility and storage increments. Model calibrations are…

Mathematical Finance · Quantitative Finance 2025-07-22 Jinniao Qiu , Antony Ware , Yang Yang

This paper introduces a new numerical approach that integrates local randomized neural networks (LRNNs) and the hybridized discontinuous Petrov-Galerkin (HDPG) method for solving coupled fluid flow problems. The proposed method partitions…

Numerical Analysis · Mathematics 2023-12-12 Haoning Dang , Fei Wang

This research addresses accurate option pricing by employing models beyond the traditional Black-Scholes framework. While Black-Scholes provides a closed-form solution, it is limited by assumptions of constant volatility, no dividends, and…

Computational Finance · Quantitative Finance 2026-04-08 Karmanpartap Singh Sidhu , Pranshi Saxena

In this paper we introduce a deep learning method for pricing and hedging American-style options. It first computes a candidate optimal stopping policy. From there it derives a lower bound for the price. Then it calculates an upper bound, a…

Computational Finance · Quantitative Finance 2021-03-23 Sebastian Becker , Patrick Cheridito , Arnulf Jentzen

This paper presents a new model for options pricing. The Black-Scholes-Merton (BSM) model plays an important role in financial options pricing. However, the BSM model assumes that the risk-free interest rate, volatility, and equity premium…

Mathematical Finance · Quantitative Finance 2024-08-29 Nicole Hao , Echo Li , Diep Luong-Le

Molecular orbitals based on the linear combination of Gaussian type orbitals are arguably the most employed discretization in quantum chemistry simulations, both on quantum and classical devices. To circumvent a potentially dense two-body…

Computational Physics · Physics 2020-11-03 Fabian M. Faulstich , Xiaojie Wu , Lin Lin

We present an anisotropic $hp-$mesh adaptation strategy using a continuous mesh model for discontinuous Petrov-Galerkin (DPG) finite element schemes with optimal test functions, extending our previous work on $h-$adaptation. The proposed…

Computational Engineering, Finance, and Science · Computer Science 2022-11-22 Ankit Chakraborty , Georg May

We propose a deep learning based discontinuous Galerkin method (D2GM) to solve hyperbolic equations with discontinuous solutions and random uncertainties. The main computational challenges for such problems include discontinuities of the…

Numerical Analysis · Mathematics 2021-07-05 Jingrun Chen , Shi Jin , Liyao Lyu

We consider a family of variational time discretizations that are generalizations of discontinuous Galerkin (dG) and continuous Galerkin-Petrov (cGP) methods. The family is characterized by two parameters. One describes the polynomial…

Numerical Analysis · Mathematics 2021-04-26 Simon Becher , Gunar Matthies

Option contracts can be valued by using the Black-Scholes equation, a partial differential equation with initial conditions. An exact solution for European style options is known. The computation time and the error need to be minimized…

Computational Engineering, Finance, and Science · Computer Science 2014-04-30 Snehanshu Saha , Swati Routh , Bidisha Goswami

Discontinuous Galerkin (DG) methods offer an enormous flexibility regarding local grid refinement and variation of polynomial degrees for a variety of different problem classes. With a focus on diffusion problems, we consider DG…

Numerical Analysis · Mathematics 2013-01-01 Kolja Brix , Claudio Canuto , Wolfgang Dahmen

Continuous Galerkin Petrov time discretization scheme is tested on some Hamiltonian systems including simple harmonic oscillator, Kepler's problem with different eccentricities and molecular dynamics problem. In particular, we implement the…

Numerical Analysis · Mathematics 2015-08-19 M. A. Qureshi , S. Hussain , Ghulam Shabbir

This paper develops a discontinuous Galerkin (DG) finite element differential calculus theory for approximating weak derivatives of Sobolev functions and piecewise Sobolev functions. By introducing numerical one-sided derivatives as…

Numerical Analysis · Mathematics 2013-03-06 Xiaobing Feng , Thomas Lewis , Michael Neilan

We study pricing and hedging under parameter uncertainty for a class of Markov processes which we call generalized affine processes and which includes the Black-Scholes model as well as the constant elasticity of variance (CEV) model as…

Risk Management · Quantitative Finance 2021-11-30 Eva Lütkebohmert , Thorsten Schmidt , Julian Sester
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