Asymptotically optimal discretization of hedging strategies with jumps

Abstract

In this work, we consider the hedging error due to discrete trading in models with jumps. Extending an approach developed by Fukasawa [In Stochastic Analysis with Financial Applications (2011) 331-346 Birkhäuser/Springer Basel AG] for continuous processes, we propose a framework enabling us to (asymptotically) optimize the discretization times. More precisely, a discretization rule is said to be optimal if for a given cost function, no strategy has (asymptotically, for large cost) a lower mean square discretization error for a smaller cost. We focus on discretization rules based on hitting times and give explicit expressions for the optimal rules within this class.

Published in at http://dx.doi.org/10.1214/13-AAP940 the Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute of Mathematical Statistics (http://www.imstat.org)

References in corpus (4)

• Estimating the degree of activity of jumps in high frequency data
• Nonparametric tests for pathwise properties of semimartingales
• Variance-optimal hedging for processes with stationary independent increments
• Spectral estimation of the fractional order of a Lévy process

Cited by in corpus (2)

• Almost sure optimal hedging strategy
• Optimal hedging of a perpetual American put with a single trade