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The aim of this paper is to study the $d$-dimensional stochastic heat equation with a multiplicative Gaussian noise which is white in space and it has the covariance of a fractional Brownian motion with Hurst parameter $% H\in (0,1)$ in…

Probability · Mathematics 2007-05-23 Yaozhong Hu , David Nualart

We treat a stochastic integration theory for a class of Hilbert-valued, volatility-modulated, conditionally Gaussian Volterra processes. We apply techniques from Malliavin calculus to define this stochastic integration as a sum of a…

Probability · Mathematics 2016-03-18 Fred Espen Benth , André Süß

We propose a convolution-FFT method for pricing European options under the Heston model that leverages a continuously differentiable representation of the joint characteristic function. Unlike existing Fourier-based methods that rely on…

Computational Finance · Quantitative Finance 2025-12-08 Xiang Gao , Cody Hyndman

We present a detailed analysis of \emph{observable} moments based parameter estimators for the Heston SDEs jointly driving the rate of returns $R_t$ and the squared volatilities $V_t$. Since volatilities are not directly observable, our…

Computational Finance · Quantitative Finance 2020-03-16 Robert Azencott , Peng Ren , Ilya Timofeyev

We present an option pricing formula for European options in a stochastic volatility model. In particular, the volatility process is defined using a fractional integral of a diffusion process and both the stock price and the volatility…

Pricing of Securities · Quantitative Finance 2020-07-29 Marc Lagunas-Merino , Salvador Ortiz-Latorre

We study a model for induction hardening of steel. The related differential system consists of a time domain vector potential formulation of the Maxwell's equations coupled with an internal energy balance and an ODE for the volume fraction…

Analysis of PDEs · Mathematics 2014-01-10 D. Hoemberg , T. Petzold , E. Rocca

Stochastic volatility models are the backbone of financial engineering. We study both continuous time diffusions as well as discrete time models. We propose two novel approaches to estimating stochastic volatility diffusions, one using…

Quantum Physics · Physics 2025-07-30 Eric Ghysels , Jack Morgan , Hamed Mohammadbagherpoor

We study the invariant distributions of Hammersley's serial harness process in all dimensions and height fluctuations in one dimension. Subject to mild moment assumptions there is essentially one unique invariant distribution, and all other…

Probability · Mathematics 2015-04-28 Timo Seppäläinen , Yun Zhai

We consider assets for which price $X_t$ and squared volatility $Y_t$ are jointly driven by Heston joint stochastic differential equations (SDEs). When the parameters of these SDEs are estimated from $N$ sub-sampled data $(X_{nT}, Y_{nT})$,…

Mathematical Finance · Quantitative Finance 2015-07-22 Robert Azencott , Yutheeka Gadhyan , Roland Glowinski

An implicit variable-step BDF2 scheme is established for solving the space fractional Cahn-Hilliard equation, involving the fractional Laplacian, derived from a gradient flow in the negative order Sobolev space $H^{-\alpha}$,…

Numerical Analysis · Mathematics 2023-06-26 Xuan Zhao , Zhongqin Xue

Numerically "exact" methods addressing the dynamics of coupled electron--phonon systems have been intensively developed. Nevertheless, the corresponding results for the electron mobility $\mu_\mathrm{dc}$ are scarce, even for the…

Strongly Correlated Electrons · Physics 2023-09-12 Veljko Janković

The half filled Hubbard model is studied in the pair approximation of the Cluster Variation Method. The use of the $SO(4)$ symmetry of the model makes possible to give a complete analytical characterization of the ground state, by means of…

Condensed Matter · Physics 2009-10-22 Alessandro Pelizzola

This paper deals with pricing of European and American options, when the underlying asset price follows Heston model, via the interior penalty discontinuous Galerkin finite element method (dGFEM). The advantages of dGFEM space…

Computational Finance · Quantitative Finance 2020-05-28 Sinem Kozpınar , Murat Uzunca , Bülent Karasözen

In this paper, we propose an infinite-dimensional version of the Stein variational gradient descent (iSVGD) method for solving Bayesian inverse problems. The method can generate approximate samples from posteriors efficiently. Based on the…

Numerical Analysis · Mathematics 2026-02-09 Junxiong Jia , Peijun Li , Deyu Meng

Generalised Hydrodynamics (GHD) describes the large-scale inhomogeneous dynamics of integrable (or close to integrable) systems in one dimension of space, based on a central equation for the fluid density or quasi-particle density: the GHD…

Pattern Formation and Solitons · Physics 2025-04-25 Thibault Bonnemain , Vincent Caudrelier , Benjamin Doyon

Recently, the size-dependence of high-order harmonic generation (HHG) in quantum dots has been investigated experimentally. In particular, for longer driving wavelengths and QDs smaller than 3\,nm, HHG was strongly suppressed, however,…

Optics · Physics 2026-03-05 Martin Thümmler , Alexander Croy , Ulf Peschel , Stefanie Gräfe

Differentiable programming is revolutionizing computational science by enabling automatic differentiation (AD) of numerical simulations. While first-order gradients are well-established, second-order derivatives (Hessians) for implicit…

Computational Engineering, Finance, and Science · Computer Science 2025-05-20 Tianju Xue

Developing efficient path integral (PI) methods for atomistic simulations of vibrational spectra in heterogeneous condensed phases and interfaces has long been a challenging task. Here, we present the h-CMD method, short for hybrid centroid…

Chemical Physics · Physics 2025-05-08 Dil K. Limbu , Nathan London , Md Omar Faruque , Mohammad R. Momeni

This paper describes the first steps of development of a new multidimensional time implicit code devoted to the study of hydrodynamical processes in stellar interiors. The code solves the hydrodynamical equations in spherical geometry and…

Instrumentation and Methods for Astrophysics · Physics 2015-05-27 M. Viallet , I. Baraffe , R. Walder

The increasing number of gas-fired units has significantly intensified the coupling between power and gas networks. Traditionally, the nonlinearity and nonconvexity in gas flow equations, together with renewable-induced stochasticity,…

Systems and Control · Electrical Eng. & Systems 2020-06-17 Haizhou Liu , Xinwei Shen , Qinglai Guo , Hongbin Sun , Wenzhi Zhao , Xinyi Zhao