Results 11 to 20 of about 1,024,611 (253)

Uncertainty quantification and Heston model [PDF]

open access: yesJournal of Mathematics in Industry, 2018
In this paper, we study the impact of the parameters involved in Heston model by means of Uncertainty Quantification. The Stochastic Collocation Method already used for example in computational fluid dynamics, has been applied throughout this work in ...
María Suárez-Taboada   +3 more
doaj   +8 more sources

Asymptotic expansion for characteristic function in Heston stochastic volatility model with fast mean-reverting correction [PDF]

open access: greenarXiv, 2013
In this note, we derive the characteristic function expansion for logarithm of the underlying asset price in corrected Heston model as proposed by Fouque and Lorig.
Ankush Agarwal
openalex   +3 more sources

Convergence of Heston to SVI [PDF]

open access: yesarXiv, 2010
In this short note, we prove by an appropriate change of variables that the SVI implied volatility parameterization presented in Gatheral's book and the large-time asymptotic of the Heston implied volatility agree algebraically, thus confirming a ...
Gatheral, Jim, Jacquier, Antoine
core   +2 more sources

FX Smile in the Heston Model [PDF]

open access: yes, 2010
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 exists a fast and
Janek, Agnieszka   +3 more
core   +13 more sources

An extension of Heston's SV model to Stochastic Interest Rates [PDF]

open access: yesJournal of Computational and Applied Mathematics Volume 354, July 2019, Pages 174-182, 2018
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.
de Frutos, Javier, Gaton, Victor
core   +2 more sources

The Heston Riemannian distance function [PDF]

open access: yesarXiv, 2013
The Heston model is a popular stock price model with stochastic volatility that has found numerous applications in practice. In the present paper, we study the Riemannian distance function associated with the Heston model and obtain explicit formulas for
Gulisashvili, Archil, Laurence, Peter
core   +1 more source

Moment explosions in the rough Heston model [PDF]

open access: hybridDecisions in Economics and Finance, 2019
AbstractWe show that the moment explosion time in the rough Heston model, introduced by El Euch and Rosenbaum in 2016, is finite if and only if it is finite for the classical Heston model. Upper and lower bounds for the explosion time are established, as well as an algorithm to compute the explosion time (under some restrictions).
Stefan Gerhold   +2 more
openalex   +4 more sources

Semi-Analytical Option Pricing Under Double Heston Jump-Diffusion Hybrid Model

open access: diamondJournal of Mathematical Sciences and Modelling, 2018
We examine European call options in the jump-diffusion version of the Double Heston stochastic volatility model for the underlying price process to provide a more flexible model for the term structure of volatility.
Rehez Ahlip   +2 more
doaj   +2 more sources

Perfect hedging in rough Heston models [PDF]

open access: yesAnnals of Applied Probability, 2018
Rough volatility models are known to reproduce the behavior of historical volatility data while at the same time fitting the volatility surface remarkably well, with very few parameters. However, managing the risks of derivatives under rough volatility can be intricate since the dynamics involve fractional Brownian motion.
Mathieu Rosenbaum
exaly   +5 more sources

Filtration of parameters of the Heston model

open access: yesСистеми обробки інформації, 2020
In this article we consider the Heston model of the stock price behaviour. While the volatility of the model is the non-linear function of another stochastic unobservable function, that is why we consider linearizing all non-linear functions of the model.
О.А. Кобилін   +2 more
doaj   +3 more sources

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