Brownian motion definition
Examples of Brownian motion in a sentence
Motivated by an attempt to model the fluctuations of asset prices, Brownian motion (i.e., the continuous-time random walk process [▇▇▇▇▇▇ 2004]) was first introduced by ▇▇▇▇▇▇▇▇▇ [1900] to price an option.
Therefore the intensity of fluctuations in scattered light (due to Brownian motion of particles in solution) are analysed by an autocorrelation method to yield a diffusion constant and ultimately a particle size expressed as the mean hydrodynamic diameter (▇▇▇▇, S.T. et al., 1994).
Therefore, in the absence of CICR, computationally inexpensive simulations of Markovian stochastic channel gating can be combined with deterministic models of Ca2+ diffusion and binding (either compartment-based or spatially resolved), leading to computationally inexpensive methods that avoid simulations of particle-based Brownian motion and stochastic reactions [7, 27-30].
In the GBM model, the proportional price changes are exponentially generated by a Brownian motion.
Systolic and hyper-systolic algorithms for the gravitational N-body problem, with an application to Brownian motion.
Sixty five years later, ▇▇▇▇▇▇▇▇▇ [1965] replaced ▇▇▇▇▇▇▇▇▇’▇ assumptions on asset price with a geometric form, called the geo- metric Brownian motion (GBM).
Its movement can be de- scribed by a multivariate geometric Brownian motion (GBM) [▇▇▇▇▇▇▇▇▇ 1965]: dCi(t) = µiCi(t)dt + σiCi(t)dWi(t), i = 1, .
The Variance-Gamma Lévy process is a pure jump and infinite activity Lévy process which can be understood as an extension of the Brownian motion which its drift subjected to random time changes under a gamma process, see ▇▇▇▇▇ and ▇▇▇▇▇▇ (1990) and ▇▇▇▇▇▇ (2007), among others, for more details.
Excess heat increases the Brownian motion and could result in microcoagulum and coagulum due to particle agglomeration.
A firm has assets-in-place that generate operating cash flow at the rate of Yt, which is publicly observable and for t ě 0, evolves according to dYt = µ(Yt)dt ` ν(Yt)dZt ` ζ(Yt−)dNt, (2) where µ(Yt) and ν(Yt) are general functions that satisfy the standard regularity conditions; tZtutě0 is a Brownian motion; tNtutě0 is a Poisson process with intensity λ(Yt) ą 0; and ζ(Yt−) is the jump size given the Poisson event.