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For backward stochastic Volterra integral equations (BSVIEs, for short), under some mild conditions, the so-called adapted solutions or adapted M-solutions uniquely exist. However, satisfactory regularity of the solutions is difficult to…

Probability · Mathematics 2018-02-13 Tianxiao Wang , Jiongmin Yong

In ordinary turbulence research it has been a long standing tradition to solve the equations in spectral space giving the best possible accuracy. This is indeed a natural choice for incompressible problems with periodic boundaries, but it…

Astrophysics · Physics 2009-11-07 A. Brandenburg , W. Dobler

In this paper, the notion of singular backward stochastic Volterra integral equations (singular BSVIEs for short) in infinite dimensional space is introduced, and the corresponding well-posedness is carefully established. A class of…

Optimization and Control · Mathematics 2023-12-08 Tianxiao Wang , Mengliang Zheng

We find various exact solutions for a new stochastic volatility (SV) model: the transition probability density, European-style option values, and (when it exists) the martingale defect. This may represent the first example of an SV model…

Computational Finance · Quantitative Finance 2019-05-28 Alan L. Lewis

This paper includes an original self contained proof of well-posedness of an initial-boundary value problem involving a non-local parabolic PDE which naturally arises in the study of derivative pricing in a generalized market model. We call…

Mathematical Finance · Quantitative Finance 2014-08-25 Anindya Goswami , Jeeten Patel , Poorva Sevgaonkar

We propose some numerical schemes for forward-backward stochastic differential equations (FBSDEs) based on a new fundamental concept of transposition solutions. These schemes exploit time-splitting methods for the variation of constants…

Numerical Analysis · Mathematics 2018-05-01 Kazufumi Ito , Yufei Zhang , Jun Zou

Calibration of stochastic local volatility (SLV) models to their underlying local volatility model is often performed by numerically solving a two-dimensional non-linear forward Kolmogorov equation. We propose a novel finite volume (FV)…

Numerical Analysis · Mathematics 2016-11-10 Maarten Wyns , Jacques Du Toit

A new method for solving numerically stochastic partial differential equations (SPDEs) with multiple scales is presented. The method combines a spectral method with the heterogeneous multiscale method (HMM) presented in [W. E, D. Liu, and…

Numerical Analysis · Mathematics 2015-05-28 A. Abdulle , G. A. Pavliotis

This paper aims at developing exactly energy-conservative and structure-preserving finite volume schemes for the discretisation of first-order symmetric-hyperbolic and thermodynamically compatible (SHTC) systems of partial differential…

Numerical Analysis · Mathematics 2026-01-01 Alessia Lucca , Michael Dumbser

Current GPU-accelerated supercomputers promise to enable large-scale simulations of turbulent flows. Lattice Boltzmann Methods (LBM) are particularly well-suited to fulfilling this promise due to their intrinsic compatibility with highly…

Computational Physics · Physics 2025-06-30 Adrian Kummerländer , Fedor Bukreev , Yuji Shimojima , Shota Ito , Mathias J. Krause

In this article we consider Bayesian parameter inference for a type of partially observed stochastic Volterra equation (SVE). SVEs are found in many areas such as physics and mathematical finance. In the latter field they can be used to…

Computation · Statistics 2024-02-20 Ajay Jasra , Hamza Ruzayqat , Amin Wu

Semi-Lagrangian (SL) schemes are known as a major numerical tool for solving transport equations with many advantages and have been widely deployed in the fields of computational fluid dynamics, plasma physics modeling, numerical weather…

Numerical Analysis · Mathematics 2023-08-09 Yongsheng Chen , Wei Guo , Xinghui Zhong

The HEat modulated Infinite DImensional Heston (HEIDIH) model and its numerical approximation are introduced and analyzed. This model falls into the general framework of infinite dimensional Heston stochastic volatility models of (F.E.…

Probability · Mathematics 2023-09-11 Fred Espen Benth , Gabriel Lord , Giulia Di Nunno , Andreas Petersson

We present a function-valued stochastic volatility model designed to capture the continuous-time evolution of forward curves in fixed-income or commodity markets. The dynamics of the (logarithmic) forward curves are defined by a…

Mathematical Finance · Quantitative Finance 2024-09-23 Sven Karbach

The partially observed linear Gaussian system of stochastic differential equations with low noise in observations is considered. A kernel-type estimators are used for estimation of the quadratic variation of the derivative of the limit of…

Statistics Theory · Mathematics 2022-11-23 Yury A. Kutoyants

Spike variation technique plays a crucial role in deriving Pontryagin's type maximum principle of optimal controls for differential equations of several types, including ordinary differential equations (ODEs), partial differential equations…

Optimization and Control · Mathematics 2022-09-13 Tianxiao Wang , Jiongmin Yong

In this paper, a stochastic Hamiltonian formulation (SHF) is proposed and applied to dissipative particle dynamics (DPD) simulations. As an extension of Hamiltonian dynamics to stochastic dissipative systems, the SHF provides necessary…

Numerical Analysis · Mathematics 2022-04-26 Linyu Peng , Noriyoshi Arai , Kenji Yasuoka

New large eddy simulation (LES) turbulence models for incompressible magnetohydrodynamics (MHD) derived from the variational multiscale (VMS) formulation for finite element simulations are introduced. The new models include the variational…

Computational Physics · Physics 2015-05-20 David Sondak , John N. Shadid , Assad A. Oberai , Roger P. Pawlowski , Eric C. Cyr , Tom M. Smith

We introduce a new family of high order accurate semi-implicit schemes for the solution of non-linear hyperbolic partial differential equations on unstructured polygonal meshes. The time discretization is based on a splitting between…

Numerical Analysis · Mathematics 2023-09-11 Walter Boscheri , Andrea Chiozzi , Michele Giuliano Carlino , Giulia Bertaglia

In this paper we show that Hilbert space-valued stochastic models are robust with respect to perturbation, due to measurement or approximation errors, in the underlying volatility process. Within the class of stochastic volatility modulated…

Probability · Mathematics 2022-11-30 Fred Espen Benth , Heidar Eyjolfsson