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1. Complex systems of moving and interacting objects are ubiquitous in the natural and social sciences. Predicting their behavior often requires models that mimic these systems with sufficient accuracy, while accounting for their inherent…

Quantitative Methods · Quantitative Biology 2014-12-02 Jonathan R. Potts , Marie Auger-Méthé , Karl Mokross , Mark A. Lewis

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 introduce a novel multi-factor Heston-based stochastic volatility model, which is able to reproduce consistently typical multi-dimensional FX vanilla markets, while retaining the (semi)-analytical tractability typical of affine models…

Pricing of Securities · Quantitative Finance 2015-03-20 Alvise De Col , Alessandro Gnoatto , Martino Grasselli

We give an analytical characterization of the price function of an American option in Heston-type models. Our approach is based on variational inequalities and extends recent results of Daskalopoulos and Feehan (2011). We study the…

Probability · Mathematics 2018-12-12 Damien Lamberton , Giulia Terenzi

New results on the convexity of geodesic-length functions on Teichm\"{u}ller space are presented. A formula for the Hessian of geodesic-length is presented. New bounds for the gradient and Hessian of geodesic-length are described. A…

Differential Geometry · Mathematics 2007-05-23 Scott A. Wolpert

We present a number of related comparison results, which allow to compare moment explosion times, moment generating functions and critical moments between rough and non-rough Heston models of stochastic volatility. All results are based on…

Mathematical Finance · Quantitative Finance 2019-06-10 Martin Keller-Ressel , Assad Majid

We propose a new, data-driven approach for efficient pricing of - fixed- and float-strike - discrete arithmetic Asian and Lookback options when the underlying process is driven by the Heston model dynamics. The method proposed in this…

Computational Finance · Quantitative Finance 2024-02-19 Leonardo Perotti , Lech A. Grzelak

We present an analytic approach to solve a degenerate parabolic problem associated to the Heston model, which is widely used in mathematical finance to derive the price of an European option on an risky asset with stochastic volatility. We…

Analysis of PDEs · Mathematics 2014-06-10 A. Canale , R. M. Mininni , A. Rhandi

We investigate the general problem of how to model the kinematics of stock prices without considering the dynamical causes of motion. We propose a stochastic process with long-range correlated absolute returns. We find that the model is…

Disordered Systems and Neural Networks · Physics 2008-12-02 M. Serva , U. L. Fulco , M. L. Lyra , G. M. Viswanathan

Continuous-time approximation of Stochastic Gradient Descent (SGD) is a crucial tool to study its escaping behaviors from stationary points. However, existing stochastic differential equation (SDE) models fail to fully capture these…

Machine Learning · Statistics 2025-06-04 Xiang Li , Zebang Shen , Liang Zhang , Niao He

We study the Heston model for pricing European options on stocks with stochastic volatility. This is a Black\--Scholes\--type equation whose spatial domain for the logarithmic stock price $x\in \RR$ and the variance $v\in (0,\infty)$ is the…

Analysis of PDEs · Mathematics 2017-11-15 Bénédicte Alziary , Peter Takáč

In this paper, we consider option pricing in a framework of the fractional Heston-type model with $H>1/2$. As it is impossible to obtain an explicit formula for the expectation $\mathbb E f(S_T)$ in this case, where $S_T$ is the asset price…

Probability · Mathematics 2019-07-04 Yuliya Mishura , Anton Yurchenko-Tytarenko

We propose to study the Hessian metric of a functional on the space of probability measures endowed with the Wasserstein $2$-metric. We name it transport Hessian metric, which contains and extends the classical Wasserstein-$2$ metric. We…

Differential Geometry · Mathematics 2021-08-02 Wuchen Li

A characterization of the proximal normal cone is obtained and a separation theorem for convex subsets of Riemannian manifolds is established. Moreover, the convexity of the distance function $d_S$ for a convex subset $S$ in the cases where…

Differential Geometry · Mathematics 2018-05-08 S. Khajehpour , M. R. Pouryayevali

We describe the precise structure of the distributional Hessian of the distance function from a point of a Riemannian manifold. In doing this we also discuss some geometrical properties of the cutlocus of a point and we compare some…

Differential Geometry · Mathematics 2016-01-20 Carlo Mantegazza , Giovanni Mascellani , Gennady Uraltsev

We give quantitative estimates for the rate of convergence of Riemannian stochastic gradient descent (RSGD) to Riemannian gradient flow and to a diffusion process, the so-called Riemannian stochastic modified flow (RSMF). Using tools from…

Machine Learning · Computer Science 2025-03-10 Benjamin Gess , Sebastian Kassing , Nimit Rana

In this paper similar to [P. Carr, A. Itkin, 2019] we construct another Markovian approximation of the rough Heston-like volatility model - the ADO-Heston model. The characteristic function (CF) of the model is derived under both…

Computational Finance · Quantitative Finance 2023-09-27 Andrey Itkin

We study distance functions from geodesics to points on Riemannian surfaces with H\"older continuous Gauss curvature, and prove a finiteness principle in the spirit of Whitney extension theory for such functions. Our result can be viewed as…

Differential Geometry · Mathematics 2024-01-23 Rotem Assouline

This work deals with the one-dimensional Stefan problem with a general time-dependent boundary condition at the fixed boundary. Stochastic solutions are obtained using discrete random walks, and the results are compared with analytic…

Analysis of PDEs · Mathematics 2023-02-06 M. Ogren

We consider rough stochastic volatility models where the variance process satisfies a stochastic Volterra equation with the fractional kernel, as in the rough Bergomi and the rough Heston model. In particular, the variance process is…

Computational Finance · Quantitative Finance 2022-07-19 Christian Bayer , Simon Breneis
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