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In this paper, we derive the price of a European call option of an asset following a normal process assuming stochastic volatility. The volatility is assumed to follow the Cox Ingersoll Ross (CIR) process. We then use the fast Fourier…

Pricing of Securities · Quantitative Finance 2019-10-07 Matta Uma Maheswara Reddy

European options can be priced by solving parabolic partial(-integro) differential equations under stochastic volatility and jump-diffusion models like Heston, Merton, and Bates models. American option prices can be obtained by solving…

Computational Engineering, Finance, and Science · Computer Science 2016-12-04 Maciej Balajewicz , Jari Toivanen

A parsimonious generalization of the Heston model is proposed where the volatility-of-volatility is assumed to be stochastic. We follow the perturbation technique of Fouque et al (2011, CUP) to derive a first order approximation of the…

Pricing of Securities · Quantitative Finance 2017-06-06 Jean-Pierre Fouque , Yuri F. Saporito

The paper investigates the performance of the European option price when the log asset price follows a rich class of Generalized Tempered Stable (GTS) distribution. The GTS distribution is an alternative to Normal distribution and…

Pricing of Securities · Quantitative Finance 2025-02-21 A. H. Nzokem

This paper proposes a numerical method for pricing foreign exchange (FX) options in a model which deals with stochastic interest rates and stochastic volatility of the FX rate. The model considers four stochastic drivers, each represented…

Computational Finance · Quantitative Finance 2019-03-05 Fazlollah Soleymani , Andrey Itkin

Bayesian inference, while foundational to probabilistic reasoning, is often hampered by the computational intractability of posterior distributions, particularly through the challenging evidence integral. Conventional approaches like Markov…

Machine Learning · Computer Science 2025-11-11 Di Zhang

The Heston model stands out from the class of stochastic volatility (SV) models mainly for two reasons. Firstly, the process for the volatility is non-negative and mean-reverting, which is what we observe in the markets. Secondly, there…

Computational Finance · Quantitative Finance 2010-10-11 Agnieszka Janek , Tino Kluge , Rafal Weron , Uwe Wystup

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

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 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

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

Stochastic volatility models based on Gaussian processes, like fractional Brownian motion, are able to reproduce important stylized facts of financial markets such as rich autocorrelation structures, persistence and roughness of sample…

Probability · Mathematics 2022-05-10 Eduardo Abi Jaber

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

Object orientation provides a flexible framework for the implementation of the convolution of arbitrary distributions of real-valued random variables. We discuss an algorithm which is based on the discrete Fourier transformation (DFT) and…

Computation · Statistics 2014-08-07 Peter Ruckdeschel , Matthias Kohl

In the present paper, a decomposition formula for the call price due to Al\`{o}s is transformed into a Taylor type formula containing an infinite series with stochastic terms. The new decomposition may be considered as an alternative to the…

Computational Finance · Quantitative Finance 2019-05-16 Archil Gulisashvili , Raúl Merino , Marc Lagunas , Josep Vives

Geometric Asian options are a type of options where the payoff depends on the geometric mean of the underlying asset over a certain period of time. This paper is concerned with the pricing of such options for the class of Volterra-Heston…

Pricing of Securities · Quantitative Finance 2025-01-14 Florian Aichinger , Sascha Desmettre

In this paper an improved Cuckoo Search Algorithm is developed to allow for an efficient and robust calibration of the Heston option pricing model for American options. Calibration of stochastic volatility models like the Heston is…

Neural and Evolutionary Computing · Computer Science 2015-08-03 Stefan Haring , Ronald Hochreiter

The purpose of this paper is to analyze the problem of option pricing when the short rate follows subdiffusive fractional Merton model. We incorporate the stochastic nature of the short rate in our option valuation model and derive explicit…

Pricing of Securities · Quantitative Finance 2018-05-03 Foad Shokrollahi

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

This paper applies an algorithm for the convolution of compactly supported Legendre series (the CONLeg method) (cf. Hale and Townsend 2014a), to pricing/hedging European-type, early-exercise and discrete-monitored barrier options under a…

Computational Finance · Quantitative Finance 2019-05-06 Tat Lung Chan , Nicholas Hale