We determine the variance-optimal hedge when the logarithm of the underlying price follows a process with stationary independent increments in discrete or continuous time. Although the general solution to this problem is known as backward recursion or backward stochastic differential equation, we show that for this class of processes the optimal endowment and strategy can be expressed more explicitly. The corresponding formulas involve the moment, respectively, cumulant generating function of the underlying process and a Laplace-or Fourier-type representation of the contingent claim. An example illustrates that our formulas are fast and easy to evaluate numerically.
L'accès aux archives du séminaire de probabilités (Strasbourg) (http://portail. mathdoc.fr/SemProba/) implique l'accord avec les conditions générales d'utilisation (http://www.numdam.org/conditions). Toute utilisation commerciale ou impression systématique est constitutive d'une infraction pénale. Toute copie ou impression de ce fichier doit contenir la présente mention de copyright. Article numérisé dans le cadre du programme Numérisation de documents anciens mathématiques http://www.numdam.org/ Closedness of some spaces of stochastic integrals
In a previous paper we introduced a new concept, the notion of E-martingales and we extended the well-known Doob inequality (for 1 < p < +∞) and the Burkholder-Davis-Gundy inequalities (for p = 2) to E-martingales. After showing new Fefferman-type inequalities that involve sharp brackets as well as the space bmo q , we extend the BurkholderDavis-Gundy inequalities (for 1 < p < +∞) to E-martingales. By means of these inequalities we give sufficient conditions for the closedness in L p of a space of stochastic integrals with respect to a fixed 1 d -valued semimartingale, a question which arises naturally in the applications to financial mathematics. Finally we investigate the relation between uniform convergence in probability and semimartingale topology.Mathematics Subject classification (1991): 60G48, 60H05, 90A09
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.