Title

Modelling stock markets by probabilistic 1-d cellular automata

Document Type

Journal article

Source Publication

International Journal of Computer Mathematics

Publication Date

1-1-1994

Volume

53

Issue

3-4

First Page

167

Last Page

176

Keywords

Cellular automata, Correlation dimension, Markov chain, transition function

Abstract

The concept of probabilistic cellular automata is introduced in this paper. The automata are used to model a simple stock market in which the buying and selling of a stock is governed by a probabilistic transition function which is also a function of time. It is possible to apply theories of Markov chain, e.g. absorption time, to this situation. Some popular strategies of investing in a stock market can also be simulated by the cellular automaton models with appropriate transition functions.

DOI

10.1080/00207169408804323

Print ISSN

00207160

Publisher Statement

Copyright © 1994, Taylor & Francis Group, LLC. Access to external full text or publisher's version may require subscription.

Full-text Version

Publisher’s Version

Share

COinS