Modelling stock markets by probabilistic 1-d cellular automata
International Journal of Computer Mathematics
Cellular automata, Correlation dimension, Markov chain, transition function
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.
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