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Machine learning methods for solving the equations of dynamical mean-field theory are developed. The method is demonstrated on the three dimensional Hubbard model. The key technical issues are defining a mapping of an input function to an…

Strongly Correlated Electrons · Physics 2015-07-01 Louis-François Arsenault , O. Anatole von Lilienfeld , Andrew J. Millis

We use a powerful extension of the classical method of heat potentials, recently developed by the present author and his collaborators, to solve several significant problems of financial mathematics. We consider the following problems in…

Mathematical Finance · Quantitative Finance 2020-03-17 Alexander Lipton

This paper presents a concurrent global-local numerical method for solving multiscale parabolic equations in divergence form. The proposed method employs hybrid coefficient to provide accurate macroscopic information while preserving…

Numerical Analysis · Mathematics 2026-04-14 Yulei Liao , Yang Liu , Pingbing Ming

Thermal analysis provides deeper insights into electronic chips behavior under different temperature scenarios and enables faster design exploration. However, obtaining detailed and accurate thermal profile on chip is very time-consuming…

Machine Learning · Computer Science 2022-09-13 Rishikesh Ranade , Haiyang He , Jay Pathak , Norman Chang , Akhilesh Kumar , Jimin Wen

A three-level explicit time-split MacCormack scheme is proposed for solving the two-dimensional nonlinear reaction-diffusion equations. The computational cost is reduced thank to the splitting and the explicit MacCormack scheme. Under the…

Numerical Analysis · Mathematics 2020-12-02 Eric Ngondiep

Ensemble Kalman methods solve problems in domains such as filtering and inverse problems with interacting particles that evolve over time. For computationally expensive problems, the cost of attaining a high accuracy quickly becomes…

Numerical Analysis · Mathematics 2025-02-18 Arne Bouillon , Toon Ingelaere , Giovanni Samaey

This paper covers a massive acceleration of Monte-Carlo based pricing method for financial products and financial derivatives. The method is applicable in risk management settings, where a financial product has to be priced under a number…

Computational Engineering, Finance, and Science · Computer Science 2008-09-30 Stefan Dirnstorfer , Andreas J. Grau

A multilevel correction scheme is proposed to solve defective and nodefective of nonsymmetric partial differential operators by the finite element method. The method includes multi correction steps in a sequence of finite element spaces. In…

Numerical Analysis · Mathematics 2016-09-27 Hehu Xie , Zhimin Zhang

Energy companies need efficient procedures to perform market calibration of stochastic models for commodities. If the Black framework is chosen for option pricing, the bottleneck of the market calibration is the computation of the variance…

Pricing of Securities · Quantitative Finance 2021-01-14 Emanuele Fabbiani , Andrea Marziali , Giuseppe De Nicolao

This paper studies bulk-surface splitting methods of first order for (semi-linear) parabolic partial differential equations with dynamic boundary conditions. The proposed Lie splitting scheme is based on a reformulation of the problem as a…

Numerical Analysis · Mathematics 2021-08-19 Robert Altmann , Balázs Kovács , Christoph Zimmer

In this paper we address the problem of the prohibitively large computational cost of existing Markov chain Monte Carlo methods for large--scale applications with high dimensional parameter spaces, e.g. in uncertainty quantification in…

Numerical Analysis · Mathematics 2015-08-11 T. J. Dodwell , C. Ketelsen , R. Scheichl , A. L. Teckentrup

We made a comparative analysis of numerical methods for multidimensional optimization. The main parameter is a number of computations of the test function to reach necessary accuracy, as it is computationally "slow". For complex functions,…

Instrumentation and Methods for Astrophysics · Physics 2013-10-09 Ivan L. Andronov , Maria G. Tkachenko

We study statistical model checking of continuous-time stochastic hybrid systems. The challenge in applying statistical model checking to these systems is that one cannot simulate such systems exactly. We employ the multilevel Monte Carlo…

Systems and Control · Computer Science 2017-06-27 Sadegh Esmaeil Zadeh Soudjani , Rupak Majumdar , Tigran Nagapetyan

In this article, we study the application of Multi-Level Monte Carlo (MLMC) approaches to numerical random homogenization. Our objective is to compute the expectation of some functionals of the homogenized coefficients, or of the…

Numerical Analysis · Mathematics 2013-01-15 Yalchin Efendiev , Cornelia Kronsbein , Frederic Legoll

We propose a multi-index algorithm for the Monte Carlo (MC) discretization of a linear, elliptic PDE with affine-parametric input. We prove an error vs. work analysis which allows a multi-level finite-element approximation in the physical…

Numerical Analysis · Mathematics 2019-07-18 Josef Dick , Michael Feischl , Christoph Schwab

The variational heat equation is a nonlinear, parabolic equation not in divergence form that arises as a model for the dynamics of the director field in a nematic liquid crystal. We present a finite difference scheme for a transformed,…

Numerical Analysis · Mathematics 2017-10-25 G. M. Coclite , J. Ridder , N. H. Risebro

The Multilevel Monte Carlo (MLMC) approach usually works well when estimating the expected value of a quantity which is a Lipschitz function of intermediate quantities, but if it is a discontinuous function it can lead to a much slower…

Numerical Analysis · Mathematics 2023-09-06 Michael B Giles

Coupled nonlinear system of reaction-diffusion equations describing multi-component (species) interactions with heterogeneous coefficients is considered. Finite volume method based approximation for the space is used to construct…

Numerical Analysis · Mathematics 2022-09-13 Maria Vasilyeva , Alexey Sadovski , D. Palaniappan

In this paper we propose an idea of constructing a macro--scale matrix system given a micro--scale matrix linear system. Then the macro--scale system is solved at cheaper computing costs. The method uses the idea of the generalized…

Numerical Analysis · Mathematics 2022-01-27 Kanghun Cho , Roktaek Lim , Dongwoo Sheen

In the framework of uncertainty quantification, we consider a quantity of interest which depends non-smoothly on the high-dimensional parameter representing the uncertainty. We show that, in this situation, the multilevel Monte Carlo…

Numerical Analysis · Mathematics 2017-06-27 Laura Scarabosio
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