Probability

Brownian Motion

Also known as: Wiener Process

The continuous-time limit of a random walk, with independent normally distributed increments.

W(0) = 0; increments are independent; W(t) - W(s) is normal with mean 0 and variance t - s; paths are continuous.

The properties that matter: variance grows linearly in time, so standard deviation grows like sqrt(t). Paths are continuous everywhere but differentiable nowhere, which is why ordinary calculus fails and Ito calculus exists.

It is a martingale and a Markov process.

Geometric Brownian motion - the standard price model - exponentiates it, giving lognormal prices that stay positive.

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