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  2. Brownian motion - Wikipedia

    en.wikipedia.org/wiki/Brownian_motion

    X is a Brownian motion with respect to P, i.e., the law of X with respect to P is the same as the law of an n-dimensional Brownian motion, i.e., the push-forward measure X ∗ (P) is classical Wiener measure on C 0 ([0, ∞); R n). both X is a martingale with respect to P (and its own natural filtration); and

  3. Wiener process - Wikipedia

    en.wikipedia.org/wiki/Wiener_process

    A single realization of a one-dimensional Wiener process A single realization of a three-dimensional Wiener process. In mathematics, the Wiener process (or Brownian motion, due to its historical connection with the physical process of the same name) is a real-valued continuous-time stochastic process discovered by Norbert Wiener.

  4. Brownian dynamics - Wikipedia

    en.wikipedia.org/wiki/Brownian_dynamics

    In Brownian dynamics, the following equation of motion is used to describe the dynamics of a stochastic system with coordinates = (): [1] [2] [3] ˙ = + (). where: ˙ is the velocity, the dot being a time derivative

  5. Geometric Brownian motion - Wikipedia

    en.wikipedia.org/wiki/Geometric_Brownian_motion

    For the simulation generating the realizations, see below. 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. [1]

  6. Stochastic calculus - Wikipedia

    en.wikipedia.org/wiki/Stochastic_calculus

    The best-known stochastic process to which stochastic calculus is applied is the Wiener process (named in honor of Norbert Wiener), which is used for modeling Brownian motion as described by Louis Bachelier in 1900 and by Albert Einstein in 1905 and other physical diffusion processes in space of particles subject to random forces.

  7. Markov property - Wikipedia

    en.wikipedia.org/wiki/Markov_property

    Two famous classes of Markov process are the Markov chain and Brownian motion. Note that there is a subtle, often overlooked and very important point that is often missed in the plain English statement of the definition. Namely that the statespace of the process is constant through time. The conditional description involves a fixed "bandwidth".

  8. Wiener equation - Wikipedia

    en.wikipedia.org/wiki/Wiener_equation

    A simple mathematical representation of Brownian motion, the Wiener equation, named after Norbert Wiener, [1] assumes the current velocity of a fluid particle fluctuates randomly:

  9. Harmonic measure - Wikipedia

    en.wikipedia.org/wiki/Harmonic_measure

    Returning to the earlier example of Brownian motion, one can show that if B is a Brownian motion in R n starting at x ∈ R n and D ⊂ R n is an open ball centred on x, then the harmonic measure of B on ∂D is invariant under all rotations of D about x and coincides with the normalized surface measure on ∂D