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Brownian Motion


Brownian motion is both the irregular physical motion of microscopic particles suspended in a fluid and a mathematical stochastic process used to model such motion. The name honors the botanist Robert Brown, who observed the phenomenon in 1827 and reported it the following year (Brown 1828). The mathematical term refers to an idealized stochastic process rather than the motion of any particular particle.

A Brownian motion with initial value x in R is a real-valued stochastic process {B(t):t>=0} that satisfies the following properties:

1. B(0)=x.

2. For all times 0=t_0<=t_1<=t_2<=...<=t_n, the increments B(t_k)-B(t_(k-1)), k=1, ..., n, are independent random variables.

3. For all t>=0, h>0, the increments B(t+h)-B(t) are normally distributed with expectation value zero and variance h.

4. The function t|->B(t) is continuous.

A Brownian motion B(t) is said to be standard if B(0)=0.

A geometric Brownian motion is obtained by exponentiating a standard Brownian motion W_t together with a linear drift. In particular, S_t=S_0exp((mu-1/2sigma^2)t+sigmaW_t) has multiplicative random changes while ln(S_t/S_0) is a scaled Brownian motion with drift.

It is easily shown from the above criteria that a Brownian motion has a number of unique natural invariance properties including scaling invariance and invariance under time inversion. Moreover, any Brownian motion B(t) satisfies a law of large numbers so that

 lim_(t->infty)(B(t))/t=0
(1)

almost surely. Moreover, for every alpha<1/2, a Brownian path is locally Hölder continuous almost surely. This means that, on each finite time interval, there is a random constant C such that

 |B(t)-B(s)|<=C|t-s|^alpha
(2)

for all s and t in the interval. On the other hand, a Brownian path is nowhere differentiable almost surely.

The above definition is extended naturally to get higher-dimensional Brownian motions. More precisely, given independent Brownian motions B_1, ..., B_d which start at x_1, ..., x_d, one can define a stochastic process {beta(t):t>=0} by

 beta(t)=[B_1(t); |; B_d(t)].
(3)

Such a beta is called a d-dimensional Brownian motion which starts at (x_1,...,x_d)^T in R^d.


See also

1-Dimensional Random Walk, Geometric Brownian Motion, Hölder Condition, Independent Statistics, Law of Large Numbers, Normal Distribution, Random Variable, Random Walk, Stochastic Process, Wiener Sausage

Portions of this entry contributed by Christopher Stover

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References

Brown, R. "A Brief Account of Microscopical Observations Made in the Months of June, July and August, 1827, on the Particles Contained in the Pollen of Plants; and on the General Existence of Active Molecules in Organic and Inorganic Bodies." Philos. Mag. 4, 161-173, 1828.Mörters, P. and Peres, Y. Brownian Motion. Cambridge, England: Cambridge University Press, 2010. https://doi.org/10.1017/CBO9780511750489.

Referenced on Wolfram|Alpha

Brownian Motion

Cite this as:

Weisstein, Eric W., with contributions by Christopher Stover. "Brownian Motion." From MathWorld--A Wolfram Resource. https://mathworld.wolfram.com/BrownianMotion.html

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