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This paper presents closed-form analytical formulas for pricing volatility and variance derivatives with nonlinear payoffs under discrete-time observations. The analysis is based on a probabilistic approach assuming that the underlying…

Statistics Theory · Mathematics 2025-06-19 Nontawat Bunchak , Udomsak Rakwongwan , Phiraphat Sutthimat

We present a discrete time stochastic volatility model in which the conditional distribution of the logreturns is a Variance-Gamma, that is a normal variance-mean mixture with Gamma mixing density. We assume that the Gamma mixing density is…

Pricing of Securities · Quantitative Finance 2014-05-29 Lorenzo Mercuri , Fabio Bellini

We derive a semi-analytical pricing formula for European VIX call options under the Heston-Hawkes stochastic volatility model introduced in arXiv:2210.15343. This arbitrage-free model incorporates the volatility clustering feature by adding…

Mathematical Finance · Quantitative Finance 2024-06-21 Oriol Zamora Font

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 present an option pricing formula for European options in a stochastic volatility model. In particular, the volatility process is defined using a fractional integral of a diffusion process and both the stock price and the volatility…

Pricing of Securities · Quantitative Finance 2020-07-29 Marc Lagunas-Merino , Salvador Ortiz-Latorre

We consider closed-form approximations for European put option prices within the Heston and GARCH diffusion stochastic volatility models with time-dependent parameters. Our methodology involves writing the put option price as an expectation…

Mathematical Finance · Quantitative Finance 2024-02-06 Kaustav Das , Nicolas Langrené

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

In this paper, we consider three stochastic-volatility models, each characterized by distinct dynamics of instantaneous volatility: (1) a CIR process for squared volatility (i.e., the classical Heston model); (2) a mean-reverting lognormal…

Pricing of Securities · Quantitative Finance 2025-10-14 V. Perederiy

We study a market model in which the volatility of the stock may jump at a random time from a fixed value to another fixed value. This model was already described in the literature. We present a new approach to the problem, based on partial…

Statistical Mechanics · Physics 2008-12-02 Miquel Montero

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

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 equity and foreign exchange markets the risk-neutral dynamics of the underlying asset are commonly represented by stochastic volatility models with jumps. In this paper we consider a dense subclass of such models and develop analytically…

Pricing of Securities · Quantitative Finance 2010-10-11 Aleksandar Mijatović , Martijn Pistorius

We consider assets for which price $X_t$ and squared volatility $Y_t$ are jointly driven by Heston joint stochastic differential equations (SDEs). When the parameters of these SDEs are estimated from $N$ sub-sampled data $(X_{nT}, Y_{nT})$,…

Mathematical Finance · Quantitative Finance 2015-07-22 Robert Azencott , Yutheeka Gadhyan , Roland Glowinski

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

This paper investigates the pricing and hedging of variance swaps under a $3/2$ volatility model. Explicit pricing and hedging formulas of variance swaps are obtained under the benchmark approach, which only requires the existence of the…

Pricing of Securities · Quantitative Finance 2014-11-04 Leunglung Chan , Eckhard Platen

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 work, we consider the issue of pricing exchange options and spread options with stochastic interest rates. We provide the closed form solution for the exchange option price when interest rate is stochastic. Our result holds when…

Condensed Matter · Physics 2007-05-23 Craig Liu , D. F. Wang

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

In this paper, we extend the 3/2-model for VIX studied by Goard and Mazur (2013) and introduce the generalized 3/2 and 1/2 classes of volatility processes. Under these models, we study the pricing of European and American VIX options and,…

Pricing of Securities · Quantitative Finance 2017-07-18 Jerome Detemple , Yerkin Kitapbayev

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