Understanding the Complex Dynamics of Financial Markets through Cellular Automata

rumblecleverAI and Robotics

Dec 1, 2013 (4 years and 7 months ago)


Understanding the Complex

Dynamics of Financial Markets

through Cellular Automata

G. Qiu, D. Kandhai, and P. M. A. Sloot

Faculty of Science, Section Computational Science, University of Amsterdam

Kruislaan 403, 1098 SJ Amsterdam, The Netherlands


We will present a cellular automaton (CA) model for simulating the complex dynamics
of financial markets
. It is well known that the dynamics can be
cterized by some
stylized facts: Fat
tailed distribution of re
term autocorrelation of
return, long
term autocorrelation of volatility (
volatility clustering

Within this model, a financial
market is represented by a two
dimensional lattice where each vertex stands for a trading
agent. According to the typical transaction behavior in real f
inancial markets, agents
only two types are adopted: F
undamentalists and imitators. Our CA model is based on
local interactions and adopts simple rules for representing the behavior of agents and a
simple rule for price updating. It is shown that the mo
del can confirm, in a simple and

manner, the main stylized

observed in empirical financial time series.

Besides, in contrast to other microscopic simulation (MS) models, our results suggest that
it is not necessary to assume a certain network
topology in which agents group together,
e.g. a random graph or a percolation network. L
range agent interactions are formed
from local interactions.


T. Lux and M. Marchesi, Nature, 397 (1999), 498

R. Cont and J.
P. Bouchaud, Macroecon
Dyn. 4 (2000).

G. Iori, J. Econ.
Behav. Organ. vol. 49 (2002).