MODELING STOCK MARKETS BY PROBABILISTIC 1-D CELLULAR-AUTOMATA

The concept of probabilistic cellular automata is introduced in this p aper. The automata are used to model a simple stock market in which th e buying and selling of a stock is governed by a probabilistic transit ion function which is also a function of time. It is possible to apply theories of Markov chain, e.g. absorption time, to this situation. So me popular strategies of investing in a stock market can also be simul ated by the cellular automaton models with appropriate transition func tions.