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Fast pricing of American-style options has been a difficult problem since it was first introduced to financial markets in 1970s, especially when the underlying stocks' prices follow some jump-diffusion processes. In this paper, we propose a…

Computational Finance · Quantitative Finance 2013-05-21 Helin Zhu , Fan Ye , Enlu Zhou

In the first part of this thesis, we focus on American options in the Heston model. We first give an analytical characterization of the value function of an American option as the unique solution of the associated (degenerate) parabolic…

Probability · Mathematics 2019-11-13 Giulia Terenzi

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

The Cheyette model is a quasi-Gaussian volatility interest rate model widely used to price interest rate derivatives such as European and Bermudan Swaptions for which Monte Carlo simulation has become the industry standard. In low…

We present a novel approach for parameter calibration of the Heston model for pricing an Asian put option, namely space mapping. Since few parameters of the Heston model can be directly extracted from real market data, calibration to real…

Numerical Analysis · Mathematics 2025-01-27 Anna Clevenhaus , Claudia Totzeck , Matthias Ehrhardt

American and Bermudan-type financial instruments are often priced with specific Monte Carlo techniques whose efficiency critically depends on the effective dimensionality of the problem and the available computational power. In our work we…

Pricing of Securities · Quantitative Finance 2021-05-04 Riccardo Aiolfi , Nicola Moreni , Marco Bianchetti , Marco Scaringi , Filippo Fogliani

In this paper, we discuss the application of quasi-Monte Carlo methods to the Heston model. We base our algorithms on the Broadie-Kaya algorithm, an exact simulation scheme for the Heston model. As the joint transition densities are not…

Computational Finance · Quantitative Finance 2012-05-04 Jan Baldeaux , Dale Roberts

Despite the empirical success of the rough Bergomi (rBergomi) model in modeling volatility dynamics, its practical use remains challenging due to high computational complexity in both pricing and calibration arising from its non-Markovian…

Computational Finance · Quantitative Finance 2026-04-09 Changqing Teng , Guanglian Li

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

This paper develops a new dual approach to compute the hedging portfolio of a Bermudan option and its initial value. It gives a "purely dual" algorithm following the spirit of Rogers (2010) in the sense that it only relies on the dual…

Mathematical Finance · Quantitative Finance 2024-10-18 Aurélien Alfonsi , Ahmed Kebaier , Jérôme Lelong

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

In this paper, the valuation of European and path-dependent options in foreign exchange (FX) markets is considered when the currency exchange rate evolves according to the Heston model combined with the Cox-Ingersoll-Ross dynamics for the…

Computational Finance · Quantitative Finance 2016-04-06 Andrei Cozma , Christoph Reisinger

We derive a new high-order compact finite difference scheme for option pricing in stochastic volatility jump models, e.g. in Bates model. In such models the option price is determined as the solution of a partial integro-differential…

Computational Finance · Quantitative Finance 2019-02-25 Bertram Düring , Alexander Pitkin

This study investigates the application of machine learning algorithms, particularly in the context of pricing American options using Monte Carlo simulations. Traditional models, such as the Black-Scholes-Merton framework, often fail to…

Machine Learning · Computer Science 2024-09-06 Prudence Djagba , Callixte Ndizihiwe

Model risk arises from the misspecification of probabilistic models used for pricing and hedging derivatives. While model risk for European-style claims has been widely studied, much less attention has been given to American-style…

Mathematical Finance · Quantitative Finance 2026-03-23 Luna Rigby , Rüdiger Frey , Erik Schlögl

High performance computing (HPC) is a very attractive and relatively new area of research, which gives promising results in many applications. In this paper HPC is used for pricing of American options. Although the American options are very…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-05-02 Verche Cvetanoska , Toni Stojanovski

We consider Heston's (1993) stochastic volatility model for valuation of European options to which (semi) closed form solutions are available and are given in terms of characteristic functions. We prove that the class of scale-parameter…

Pricing of Securities · Quantitative Finance 2021-01-12 Ben Boukai

In this article we consider the problem of pricing and hedging high-dimensional Asian basket options by Quasi-Monte Carlo simulation. We assume a Black-Scholes market with time-dependent volatilities and show how to compute the deltas by…

Pricing of Securities · Quantitative Finance 2015-06-29 Nicola Cufaro Petroni , Piergiacomo Sabino

In this article we propose a novel approach to reduce the computational complexity of various approximation methods for pricing discrete time American options. Given a sequence of continuation values estimates corresponding to different…

Computational Finance · Quantitative Finance 2013-12-30 Denis Belomestny , Fabian Dickmann , Tigran Nagapetyan

We show that deliberately introducing a nested simulation stage can lead to significant variance reductions when comparing two stopping times by Monte Carlo. We derive the optimal number of nested simulations and prove that the algorithm is…

Computational Finance · Quantitative Finance 2014-02-04 Fabian Dickmann , Nikolaus Schweizer