We consider the problem of pricing contingent claims on a stock
whose price process is modelled by a geometric Lévy process, in exact analogy
with the ubiquitous geometric Brownian motion model. Because the noise process
has jumps of random sizes, such a market is incomplete and there is not a
unique equivalent martingale measure. We study several approaches to pricing
options which all make use of an equivalent martingale measure that is in
different respects "closest" to the underlying canonical measure, the main ones
being the Föllmer-Schweizer minimal measure and the martingale measure which
has minimum relative entropy with respect to the canonical measure. It is shown
that the minimum relative entropy measure is that constructed via the Esscher
transform, while the Föllmer-Schweizer measure corresponds to another natural
analogue of the classical Black-Scholes measure.
@article{1029962753,
author = {Chan, Terence},
title = {Pricing contingent claims on stocks driven by L\'evy
processes},
journal = {Ann. Appl. Probab.},
volume = {9},
number = {1},
year = {1999},
pages = { 504-528},
language = {en},
url = {http://dml.mathdoc.fr/item/1029962753}
}
Chan, Terence. Pricing contingent claims on stocks driven by Lévy
processes. Ann. Appl. Probab., Tome 9 (1999) no. 1, pp. 504-528. http://gdmltest.u-ga.fr/item/1029962753/