proposed by Chorin (1973). To simulate the diffusion of
vorticity in vortex methods, the positions of the vortices
are given random displacements (a random walk) (Chorin
and Marsden, 1990). The basic idea of the random walk
method is that the random displacements spread out the
vortices like the diffusion process spreads out the
vorticity; 3) Random walk with drift method, the best
forecast of tomorrow's price is today's price plus a drift
term. One could think of the drift as measuring a trend in
the price (perhaps reflecting long-term inflation). Given
the drift is usually assumed to be constant. Related:
Mean reversion; 4) Vector auto regression; an
econometric model used to capture the evolution and the
interdependencies between multiple time series,
generalizing the univariate AR models. All the variables in
a VAR are treated symmetrically by including for each
variable an equation explaining its evolution based on its
own lags and the lags of all the other variables in the
model. Based on this feature, Christopher Sims
advocates the use of VAR models as a theory-free
method to estimate economic relationships, thus being an
alternative to the "incredible identification restrictions" in
structural models (Sim, 1980) Auto regression; a type of
random process which is often used to model and predict
various types of natural and social phenomena; 6)
Moving average, commonly used with time series data to
smooth out short-term fluctuations and highlight longerterm
trends or cycles. Mathematically, a moving average
is a type of convolution and so it is also similar to the lowpass
filter used in signal processing. When used with
non-time series data, a moving average simply acts as a
generic smoothing operation without any specific
connection to time, although typically some kind of
ordering is