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Related papers: A High Order Method for Pricing of Financial Deriv…

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We describe the pricing and hedging of financial options without the use of probability using rough paths. By encoding the volatility of assets in an enhancement of the price trajectory, we give a pathwise presentation of the replication of…

Mathematical Finance · Quantitative Finance 2020-07-09 John Armstrong , Claudio Bellani , Damiano Brigo , Thomas Cass

This paper proposes a new hybrid high-order discretization for the biharmonic problem and the corresponding eigenvalue problem. The discrete ansatz space includes degrees of freedom in $n-2$ dimensional submanifolds (e.g., nodal values in…

Numerical Analysis · Mathematics 2026-04-06 Yizhou Liang , Ngoc Tien Tran

This paper deals with the numerical solution of the Heston partial differential equation that plays an important role in financial option pricing, Heston (1993, Rev. Finan. Stud. 6). A feature of this time-dependent, two-dimensional…

Numerical Analysis · Mathematics 2011-04-11 K. J. in 't Hout , S. Foulon

Finite-difference methods are widely used for zeroth-order optimization in settings where gradient information is unavailable or expensive to compute. These procedures mimic first-order strategies by approximating gradients through function…

Optimization and Control · Mathematics 2025-05-27 Marco Rando , Cesare Molinari , Lorenzo Rosasco , Silvia Villa

We develop a high-order, explicit method for acoustic scattering in three space dimensions based on a combined-field time-domain integral equation. The spatial discretization, of Nystr\"om type, uses Gaussian quadrature on panels combined…

Numerical Analysis · Mathematics 2020-01-29 Alex H. Barnett , Leslie Greengard , Tom Hagstrom

High-order derivatives of analytic functions are expressible as Cauchy integrals over circular contours, which can very effectively be approximated, e.g., by trapezoidal sums. Whereas analytically each radius r up to the radius of…

Numerical Analysis · Mathematics 2011-04-04 Folkmar Bornemann

Numerical solving differential equations with fractional derivatives requires elimination of the singularity which is inherent in the standard definition of fractional derivatives. The method of integration by parts to eliminate this…

Numerical Analysis · Mathematics 2022-01-26 Pavel B. Dubovski , Jeffrey A. Slepoi

Solving complex partial differential equations is vital in the physical sciences, but often requires computationally expensive numerical methods. Reduced-order models (ROMs) address this by exploiting dimensionality reduction to create fast…

Machine Learning · Computer Science 2026-05-19 Robert Stephany , William Michael Anderson , Youngsoo Choi

When modeling scientific and industrial problems, geometries are typically modeled by explicit boundary representations obtained from computer-aided design software. Unfitted (also known as embedded or immersed) finite element methods offer…

Computational Engineering, Finance, and Science · Computer Science 2024-05-24 Pere A. Martorell , Santiago Badia

This is a study of certain finite element methods designed for convection-dominated, time-dependent partial differential equations. Specifically, we analyze high order space-time tensor product finite element discretizations, used in a…

Numerical Analysis · Mathematics 2013-10-30 Randolph E. Bank , Maximilian S. Metti

Variational regularization techniques are dominant in the field of mathematical imaging. A drawback of these techniques is that they are dependent on a number of parameters which have to be set by the user. A by now common strategy to…

Optimization and Control · Mathematics 2020-12-10 Matthias J. Ehrhardt , Lindon Roberts

We introduce signature payoffs, a family of path-dependent derivatives that are given in terms of the signature of the price path of the underlying asset. We show that these derivatives are dense in the space of continuous payoffs, a result…

Computational Finance · Quantitative Finance 2018-09-26 Imanol Perez Arribas

The problem of optimal recovering high-order mixed derivatives of bivariate functions with finite smoothness is studied. Based on the truncation method, an algorithm for numerical differentiation is constructed, which is order-optimal both…

Numerical Analysis · Mathematics 2024-07-08 Y. V. Semenova , S. G. Solodky

The goal of this paper is to investigate an approach for derivative-free optimization that has not received sufficient attention in the literature and is yet one of the simplest to implement and parallelize. It consists of computing…

Optimization and Control · Mathematics 2021-02-22 Hao-Jun Michael Shi , Melody Qiming Xuan , Figen Oztoprak , Jorge Nocedal

Financial derivatives pricing aims to find the fair value of a financial contract on an underlying asset. Here we consider option pricing in the partial differential equations framework. The contemporary models lead to one-dimensional or…

Computational Finance · Quantitative Finance 2015-04-07 Karel in 't Hout , Jari Toivanen

Cox-Ingersoll-Ross (CIR) processes are extensively used in state-of-the-art models for the approximative pricing of financial derivatives. In particular, CIR processes are day after day employed to model instantaneous variances (squared…

Numerical Analysis · Mathematics 2021-11-02 Mario Hefter , Arnulf Jentzen

This paper introduces a semi-analytical method for pricing American options on assets (stocks, ETFs) that pay discrete and/or continuous dividends. The problem is notoriously complex because discrete dividends create abrupt price drops and…

Pricing of Securities · Quantitative Finance 2026-01-06 Andrey Itkin

In this study, we propose a genuine fourth-order compact finite difference scheme for solving biharmonic equations with Dirichlet boundary conditions in both two and three dimensions. In the 2D case, we build upon the high-order compact…

Numerical Analysis · Mathematics 2024-09-04 Kejia Pan , Jin Li , Zhilin Li , Kang Fu

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

The change of numeraire gives very important computational simplification in option pricing. This technique reduces the number of sources of risks that need to be accounted for and so it is useful in pricing complicated derivatives that…

Pricing of Securities · Quantitative Finance 2014-07-22 Hyong-chol O , Yong-hwa Ro , Ning Wan