We present explicit formulae for the positive and negative moments of an exponential Wiener functional, which is deΓΏned as the integral with respect to time of geometric Brownian motion and plays an important role in several ΓΏelds.
A note on the distribution of integrals of geometric Brownian motion
β Scribed by Rabi Bhattacharya; Enrique Thomann; Edward Waymire
- Publisher
- Elsevier Science
- Year
- 2001
- Tongue
- English
- Weight
- 82 KB
- Volume
- 55
- Category
- Article
- ISSN
- 0167-7152
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β¦ Synopsis
The purpose of this note is to identify an interesting and surprising duality between the equations governing the probability distribution and expected value functional of the stochastic process deΓΏned by At := t 0 exp{Zs} ds; t ΒΏ 0; where {Zs: s ΒΏ 0} is a one-dimensional Brownian motion with drift coe cient and di usion coe cient 2 : In particular, both expected values of the form v(t; x) := Ef(x+At), f homogeneous, as well as the probability density a(t; y) dy := P(At β dy) are shown to be governed by a pair of linear parabolic partial di erential equations. Although the equations are not the backward=forward adjoint pairs one would naturally have in the general theory of Markov processes, unifying and remarkably simple derivations of these equations are provided.
π SIMILAR VOLUMES
Well-known characterizations of the geometric distribution via the independerlce of sortie contrast and the minimurn in a sample of i.i.d, random variables arc illustrated and supplemented, q" 1998 Elsevier Science B.V. All rights reserved.
We study the possibility to control the moments of Wiener integrals of fractional Brownian motion with respect to the L p -norm of the integrand. It turns out that when the self-similarity index H ΒΏ 1 2 , we can have only an upper inequality, and when H Β‘ 1 2 we can have only a lower inequality.