Rate of convergence of option prices for approximations of the geometric Ornstein-Uhlenbeck process by Bernoulli jumps of prices on assets

Authors:
Yu. S. Mishura and Ye. Yu. Munchak

Translated by:
N. Semenov

Original publication:
Teoriya Imovirnostei ta Matematichna Statistika, tom **93** (2015).

Journal:
Theor. Probability and Math. Statist. **93** (2016), 137-152

MSC (2010):
Primary 91B24, 91B25, 91G20

DOI:
https://doi.org/10.1090/tpms/999

Published electronically:
February 7, 2017

Full-text PDF

Abstract | References | Similar Articles | Additional Information

Abstract: We consider the discrete approximation scheme for the price of an asset that is modeled by the geometric Ornstein-Uhlenbeck process. The approximation scheme corresponds to Euler type discrete-time approximations where the increments of the Wiener process are changed by independent identically distributed Bernoulli random variables. The rate of convergence of both objective and fair option prices is estimated by using the classical results on the rate of convergence to the normal law of the distribution functions of sums of identically distributed random variables. We analyze option prices and specific changes in a model where the martingale measure is used instead of the objective measure.

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Additional Information

**Yu. S. Mishura**

Affiliation:
Department of Probability Theory, Statistics, and Actuarial Mathematics, Faculty for Mechanics and Mathematics, National Taras Shevchenko University, Academician Glushkov Avenue, 6, Kyiv 03127, Ukraine

Email:
myus@univ.kiev.ua

**Ye. Yu. Munchak**

Affiliation:
Department of Probability Theory, Statistics, and Actuarial Mathematics, Faculty for Mechanics and Mathematics, National Taras Shevchenko University, Academician Glushkov Avenue, 6, Kyiv 03127, Ukraine

Email:
yevheniamunchak@gmail.com

DOI:
https://doi.org/10.1090/tpms/999

Keywords:
Financial market,
rate of convergence,
Ornstein--Uhlenbeck process,
option prices

Received by editor(s):
June 11, 2015

Published electronically:
February 7, 2017

Additional Notes:
This paper was prepared following the talk at the International conference “Probability, Reliability and Stochastic Optimization (PRESTO-2015)” held in Kyiv, Ukraine, April 7–10, 2015

Article copyright:
© Copyright 2017
American Mathematical Society