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In this study we define a three-step procedure to relate the self-decomposability of the stationary law of a generalized Ornstein-Uhlenbeck process to the law of the increments of such processes. Based on this procedure and the results of…

Computational Finance · Quantitative Finance 2021-03-25 Piergiacomo Sabino

In this paper, we relax the power parameter of instantaneous variance and develop a new stochastic volatility plus jumps model that generalize the Heston model and 3/2 model as special cases. This model has two distinctive features. First,…

Mathematical Finance · Quantitative Finance 2017-03-20 Wei Lin , Shenghong Li , Shane Chern

In 'A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options', Heston proposes a Stochastic Volatility (SV) model with constant interest rate and derives a semi-explicit valuation formula.…

Computational Finance · Quantitative Finance 2021-03-10 Javier de Frutos , Victor Gaton

Non-equilibrium phenomena occur not only in physical world, but also in finance. In this work, stochastic relaxational dynamics (together with path integrals) is applied to option pricing theory. A recently proposed model (by Ilinski et…

Statistical Mechanics · Physics 2009-10-31 Matthias Otto

The aim of this work is to introduce a new stochastic volatility model for equity derivatives. To overcome some of the well-known problems of the Heston model, and more generally of the affine models, we define a new specification for the…

Pricing of Securities · Quantitative Finance 2014-09-19 José Da Fonseca , Claude Martini

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 present a path integral method to derive closed-form solutions for option prices in a stochastic volatility model. The method is explained in detail for the pricing of a plain vanilla option. The flexibility of our approach is…

Pricing of Securities · Quantitative Finance 2008-12-02 D. Lemmens , M. Wouters , J. Tempere , S. Foulon

This thesis develops a new framework for modelling price processes in finance, such as an equity price or foreign exchange rate. This can be related to the conventional Ito calculus-based framework through the time integral of a price's…

Mathematical Finance · Quantitative Finance 2025-03-21 Ryan McCrickerd

We establish several closed pricing formula for various path-independent payoffs, under an exponential L\'evy model driven by the Variance Gamma process. These formulas take the form of quickly convergent series and are obtained via tools…

Pricing of Securities · Quantitative Finance 2020-06-03 Jean-Philippe Aguilar

In this paper new analytical and numerical approaches to valuating path-dependent options of European type have been developed. The model of stochastic volatility as a basic model has been chosen. For European options we could improve the…

Pricing of Securities · Quantitative Finance 2010-09-24 Yu. A. Kuperin , P. A. Poloskov

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 apply path integration techniques to obtain option pricing with stochastic volatility using a generalized Black-Scholes equation known as the Merton and Garman equation. We numerically simulate the option prices using the technique of…

Condensed Matter · Physics 2007-05-23 Belal E. Baaquie , L. C. Kwek , M. Srikant

Generating realistic synthetic option prices requires implied volatility as an input, yet implied volatility is itself derived from observed option prices, creating a circular dependency that limits synthetic data for machine-learning and…

Computational Finance · Quantitative Finance 2026-05-15 Julia Sun , Zheyu Jin , Jiawei Zhang , Jeffrey D. Varner

We study a nonparametric Bayesian approach to estimation of the volatility function of a stochastic differential equation driven by a gamma process. The volatility function is modelled a priori as piecewise constant, and we specify a gamma…

Statistics Theory · Mathematics 2023-10-18 Denis Belomestny , Shota Gugushvili , Moritz Schauer , Peter Spreij

Rough volatility models are very appealing because of their remarkable fit of both historical and implied volatilities. However, due to the non-Markovian and non-semimartingale nature of the volatility process, there is no simple way to…

Probability · Mathematics 2018-04-12 Eduardo Abi Jaber , Omar El Euch

The use of sequential Monte Carlo within simulation for path-dependent option pricing is proposed and evaluated. Recently, it was shown that explicit solutions and importance sampling are valuable for efficient simulation of spot price and…

Computational Finance · Quantitative Finance 2019-11-13 Michael A. Kouritzin , Anne MacKay

The multidimensional Uncertain Volatility Model leads to robust option pricing problems under joint volatility and correlation uncertainty. Their numerical resolution quickly becomes challenging because the associated stochastic control…

Computational Finance · Quantitative Finance 2026-05-11 Lokman A Abbas-Turki , Jean-François Chassagneux , Jean-Philippe Lemor , Grégoire Loeper , Simon Sananes

In the option valuation literature, the shortcomings of one factor stochastic volatility models have traditionally been addressed by adding jumps to the stock price process. An alternate approach in the context of option pricing and…

Mathematical Finance · Quantitative Finance 2019-12-24 Gifty Malhotra , R. Srivastava , H. C. Taneja

We investigate the problem of pricing derivatives under a fractional stochastic volatility model. We obtain an approximate expression of the derivative price where the stochastic volatility can be composed of deterministic functions of time…

Pricing of Securities · Quantitative Finance 2022-10-28 Yuecai Han , Xudong Zheng

We propose a finite difference scheme to simulate solutions to a certain type of hyperbolic stochastic partial differential equation (HSPDE). These solutions can in turn estimate so called volatility modulated Volterra (VMV) processes and…

Statistics Theory · Mathematics 2016-02-10 Fred Espen Benth , Heidar Eyjolfsson