Geometric Brownian motion by a different Brownian Motion—the model is called a stochastic volatility model. Geometric Brownian motion A geometric Brownian motion (GBM) (also known as exponential Brownian motion) is a continuous-time stochastic process in which the logarithm of the randomly varying quantity follows a Brownian motion (also called a Wiener process) with drift. It is an important example of stochastic processes satisfying a stochastic differential equation (SDE); in particular, it is used in mathematical finance to model stock prices in the Black–Scholes model. A stochastic process "S" is said to follow a GBM if it satisfies the following stochastic differential equation (SDE):
Brownian meander Brownian meander In the mathematical theory of probability, Brownian meander formula_1 is a continuous non-homogeneous Markov process defined as follows: Let formula_2 be a standard one-dimensional Brownian motion, and formula_3, i.e. the last time before "t" = 1 when formula_4 visits formula_5. Then the Brownian meander is defined by the following: In words, let formula_7 be the last time before 1 that a standard Brownian motion visits formula_5. (formula_9 almost surely.) We snip off and discard the trajectory of Brownian motion before formula_7, and scale the remaining part so that it spans a time interval of length 1. The scaling