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In this paper, we propose an iterative splitting method to solve the partial differential equations in option pricing problems. We focus on the Heston stochastic volatility model and the derived two-dimensional partial differential equation…

Computational Engineering, Finance, and Science · Computer Science 2020-03-31 Hongshan Li , Zhongyi Huang

We propose a new high-order alternating direction implicit (ADI) finite difference scheme for the solution of initial-boundary value problems of convection-diffusion type with mixed derivatives and non-constant coefficients, as they arise…

Computational Finance · Quantitative Finance 2017-02-07 Bertram Düring , James Miles

In this paper, we price European Call three different option pricing models, where the volatility is dynamically changing i.e. non constant. In stochastic volatility (SV) models for option pricing a closed form approximation technique is…

Pricing of Securities · Quantitative Finance 2023-09-19 Natasha Latif , Shafqat Ali Shad , Muhammad Usman , Chandan Kumar , Bahman B Motii , MD Mahfuzer Rahman , Khuram Shafi , Zahra Idrees

We consider stochastic volatility models under parameter uncertainty and investigate how model derived prices of European options are affected. We let the pricing parameters evolve dynamically in time within a specified region, and…

Mathematical Finance · Quantitative Finance 2018-07-12 Samuel N. Cohen , Martin Tegnér

Recent years have seen an increased level of interest in pricing equity options under a stochastic volatility model such as the Heston model. Often, simulating a Heston model is difficult, as a standard finite difference scheme may lead to…

Computational Finance · Quantitative Finance 2011-11-28 Ian Iscoe , Asif Lakhany

In American options, the early exercise feature allows the option to be exercised at any time prior to expiration. However, this flexibility introduces a challenge: the pricing model must value the option while simultaneously determining an…

Computational Finance · Quantitative Finance 2026-05-11 Rohan , Siddanth Shetty , Amit N. Kumar

We propose a multi-scale stochastic volatility model in which a fast mean-reverting factor of volatility is built on top of the Heston stochastic volatility model. A singular pertubative expansion is then used to obtain an approximation for…

Pricing of Securities · Quantitative Finance 2012-05-15 Jean-Pierre Fouque , Matthew Lorig

We develop quantum algorithms for pricing Asian and barrier options under the Heston model, a popular stochastic volatility model, and estimate their costs, in terms of T-count, T-depth and number of logical qubits, on instances under…

Quantum Physics · Physics 2024-10-23 Guoming Wang , Angus Kan

We propose a quasi-Monte Carlo algorithm for pricing knock-out and knock-in barrier options under the Heston (1993) stochastic volatility model. This is done by modifying the LT method from Imai and Tan (2006) for the Heston model such that…

Computational Finance · Quantitative Finance 2015-01-23 Nico Achtsis , Ronald Cools , Dirk Nuyens

The Heston stochastic volatility model is a standard model for valuing financial derivatives, since it can be calibrated using semi-analytical formulas and captures the most basic structure of the market for financial derivatives with…

Pricing of Securities · Quantitative Finance 2019-01-29 Daniel Guterding , Wolfram Boenkost

In this paper the valuation problem of a European call option in presence of both stochastic volatility and transaction costs is considered. In the limit of small transaction costs and fast mean reversion, an asymptotic expression for the…

Pricing of Securities · Quantitative Finance 2012-11-20 R. E. Caflisch , G. Gambino , M. Sammartino , C. Sgarra

We present an adaptive approach for valuing the European call option on assets with stochastic volatility. The essential feature of the method is a reduction of uncertainty in latent volatility due to a Bayesian learning procedure. Starting…

Other Condensed Matter · Physics 2008-12-02 Sergei Fedotov , Stephanos Panayides

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

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 develop a novel deep learning approach for pricing European options in diffusion models, that can efficiently handle high-dimensional problems resulting from Markovian approximations of rough volatility models. The option pricing partial…

Computational Finance · Quantitative Finance 2025-04-04 Antonis Papapantoleon , Jasper Rou

In this paper a simple, effective adaptation of Alternating Direction Implicit (ADI) time discretization schemes is proposed for the numerical pricing of American-style options under the Heston model via a partial differential…

Computational Finance · Quantitative Finance 2015-04-07 Tinne Haentjens , Karel in 't Hout

This study focuses on the application of the Heston model to option pricing, employing both theoretical derivations and empirical validations. The Heston model, known for its ability to incorporate stochastic volatility, is derived and…

Computational Finance · Quantitative Finance 2024-10-22 Zheng Cao , Xinhao Lin

A major drawback of the Standard Heston model is that its implied volatility surface does not produce a steep enough smile when looking at short maturities. For that reason, we introduce the Stationary Heston model where we replace the…

Mathematical Finance · Quantitative Finance 2020-07-13 Vincent Lemaire , Thibaut Montes , Gilles Pagès

The Heston stochastic volatility model is a widely used tool in financial mathematics for pricing European options. However, its calibration remains computationally intensive and sensitive to local minima due to the model's nonlinear…

Analysis of PDEs · Mathematics 2026-04-21 Arman Zadgar , Somayeh Fallah , Farshid Mehrdoust , Juan E. Trinidad Segovia

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
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