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
Language
English