arrow
Return

When is time continuous?

delete2000-02-01
delete80
PRE
AI
B
Bertsimas, D
L
Leonid Kogan
L
Lo, AW *
DOI:10.1016/S0304-405X(99)00049-5delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
Continuous-time stochastic processes are approximations to physically realizable phenomena. We quantify one aspect of the approximation errors by characterizing the asymptotic distribution of the replication errors that arise from delta-hedging derivative securities in discrete time, and introducing the notion of temporal granularity which measures the extent to which discrete-time implementations of continuous-time models can track the payoff of a derivative security. We show that granularity is a particular function of a derivative contract's terms and the parameters of the underlying stochastic process. Explicit expressions for the granularity of geometric Brownian motion and an Ornstein-Uhlenbeck process for call and put options are derived, and we perform Monte Carlo simulations to illustrate the empirical properties of granularity. (C) 2000 Elsevier Science S.A. All rights reserved. JEL classification. G13.
Keywords:
derivatives
delta hedging
continuous-time models
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Journal of Financial Economics cover
Journal of Financial Economics
IF:
12
Papers:
3.8K
Citations:
5.5W

Organization

No organization information available