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Geometric Brownian Motion


A geometric Brownian motion is a positive stochastic process (S_t) satisfying the stochastic differential equation

 dS_t=muS_tdt+sigmaS_tdW_t,

where (W_t) is a Wiener process, mu is the drift, and sigma is the volatility. Applying Ito's lemma gives the explicit solution

 S_t=S_0exp((mu-1/2sigma^2)t+sigmaW_t).

Consequently, ln(S_t/S_0) has a normal distribution, and S_t has a log-normal distribution. Geometric Brownian motion is the underlying asset model in Black-Scholes theory.

A geometric Brownian motion is related directly to Brownian motion: it is obtained by exponentiating a Brownian motion with linear drift. Equivalently, the natural logarithm of S_t/S_0 is the Brownian motion sigmaW_t plus the deterministic drift (mu-1/2sigma^2)t. Thus geometric Brownian motion has multiplicative, rather than additive, random changes and remains positive when S_0>0.


See also

Black-Scholes Theory, Brownian Motion, Log Normal Distribution, Stochastic Differential Equation, Wiener Process

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References

Samuelson, P. A. "Rational Theory of Warrant Pricing." Industrial Management Rev. 6, 13-31, 1965.Shreve, S. E. Stochastic Calculus for Finance II: Continuous-Time Models. New York: Springer-Verlag, 2004.

Cite this as:

Weisstein, Eric W. "Geometric Brownian Motion." From MathWorld--A Wolfram Resource. https://mathworld.wolfram.com/GeometricBrownianMotion.html

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