Option pricing in the model with stochastic volatility driven by Ornstein–Uhlenbeck process. Simulation

We consider a discrete-time approximation of paths of an Ornstein–Uhlenbeck process as a mean for estimation of a price of European call option in the model of financial market with stochastic volatility. The Euler–Maruyama approximation scheme is implemented. We determine the estimates for the opti...

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Main Authors: Sergii Kuchuk-Iatsenko, Yuliya Mishura
Format: Article
Language:English
Published: VTeX 2015-12-01
Series:Modern Stochastics: Theory and Applications
Subjects:
Online Access:https://vmsta.vtex.vmt/doi/10.15559/15-VMSTA43
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author Sergii Kuchuk-Iatsenko
Yuliya Mishura
author_facet Sergii Kuchuk-Iatsenko
Yuliya Mishura
author_sort Sergii Kuchuk-Iatsenko
collection DOAJ
description We consider a discrete-time approximation of paths of an Ornstein–Uhlenbeck process as a mean for estimation of a price of European call option in the model of financial market with stochastic volatility. The Euler–Maruyama approximation scheme is implemented. We determine the estimates for the option price for predetermined sets of parameters. The rate of convergence of the price and an average volatility when discretization intervals tighten are determined. Discretization precision is analyzed for the case where the exact value of the price can be derived.
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spelling doaj.art-4d41638c7c3d485789339d94554ad3312022-12-21T22:38:12ZengVTeXModern Stochastics: Theory and Applications2351-60462351-60542015-12-012435536910.15559/15-VMSTA43Option pricing in the model with stochastic volatility driven by Ornstein–Uhlenbeck process. SimulationSergii Kuchuk-Iatsenko0Yuliya Mishura1Taras Shevchenko National University of Kyiv, Volodymyrska str. 64, 01601, Kyiv, UkraineTaras Shevchenko National University of Kyiv, Volodymyrska str. 64, 01601, Kyiv, UkraineWe consider a discrete-time approximation of paths of an Ornstein–Uhlenbeck process as a mean for estimation of a price of European call option in the model of financial market with stochastic volatility. The Euler–Maruyama approximation scheme is implemented. We determine the estimates for the option price for predetermined sets of parameters. The rate of convergence of the price and an average volatility when discretization intervals tighten are determined. Discretization precision is analyzed for the case where the exact value of the price can be derived.https://vmsta.vtex.vmt/doi/10.15559/15-VMSTA43Financial marketsstochastic volatilityOrnstein–Uhlenbeck processoption pricingdiscrete-time approximationsEuler–Maruyama scheme
spellingShingle Sergii Kuchuk-Iatsenko
Yuliya Mishura
Option pricing in the model with stochastic volatility driven by Ornstein–Uhlenbeck process. Simulation
Modern Stochastics: Theory and Applications
Financial markets
stochastic volatility
Ornstein–Uhlenbeck process
option pricing
discrete-time approximations
Euler–Maruyama scheme
title Option pricing in the model with stochastic volatility driven by Ornstein–Uhlenbeck process. Simulation
title_full Option pricing in the model with stochastic volatility driven by Ornstein–Uhlenbeck process. Simulation
title_fullStr Option pricing in the model with stochastic volatility driven by Ornstein–Uhlenbeck process. Simulation
title_full_unstemmed Option pricing in the model with stochastic volatility driven by Ornstein–Uhlenbeck process. Simulation
title_short Option pricing in the model with stochastic volatility driven by Ornstein–Uhlenbeck process. Simulation
title_sort option pricing in the model with stochastic volatility driven by ornstein uhlenbeck process simulation
topic Financial markets
stochastic volatility
Ornstein–Uhlenbeck process
option pricing
discrete-time approximations
Euler–Maruyama scheme
url https://vmsta.vtex.vmt/doi/10.15559/15-VMSTA43
work_keys_str_mv AT sergiikuchukiatsenko optionpricinginthemodelwithstochasticvolatilitydrivenbyornsteinuhlenbeckprocesssimulation
AT yuliyamishura optionpricinginthemodelwithstochasticvolatilitydrivenbyornsteinuhlenbeckprocesssimulation