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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 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 St is said to follow a GBM if it satisfies the following stochastic differential equation (SDE): where W t {displaystyle W_{t}} is a Wiener process or Brownian motion, and μ {displaystyle mu } ('the percentage drift') and σ {displaystyle sigma } ('the percentage volatility') are constants.

[ "Stochastic differential equation", "Diffusion process", "Brownian motion", "Martingale representation theorem", "Brownian model of financial markets", "Reflection principle (Wiener process)", "Reflected Brownian motion", "Wiener sausage", "Brownian web", "Brownian excursion", "Novikov's condition", "Variance gamma process", "Brownian meander", "Long-range dependency", "Brownian tree", "McKean–Vlasov process", "Itō isometry" ]
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