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Computer Simulation of Chaotic Systems

T. K. Genger, T. J. Anande, S. Al-Shehri. Published in Information Systems

International Journal of Applied Information Systems
Year of Publication: 2017
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors: T. K. Genger, T. J. Anande, S. Al-Shehri
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  1. T K Genger, T J Anande and S Al-Shehri. Computer Simulation of Chaotic Systems. International Journal of Applied Information Systems 12(1):1-8, April 2017. URL, DOI BibTeX

    	author = "T. K. Genger and T. J. Anande and S. Al-Shehri",
    	title = "Computer Simulation of Chaotic Systems",
    	journal = "International Journal of Applied Information Systems",
    	issue_date = "April 2017",
    	volume = 12,
    	number = 1,
    	month = "Apr",
    	year = 2017,
    	issn = "2249-0868",
    	pages = "1-8",
    	url = "",
    	doi = "10.5120/ijais2017451605",
    	publisher = "Foundation of Computer Science (FCS), NY, USA",
    	address = "New York, USA"


This paper is about the implementation of a software tool to aid the study of chaos theory in the the context of the financial or commodities markets. The main focus of this paper is simulating the movement of oil prices in an attempt to identity chaos when it exists. Models implemented represent certain economically realistic aspects of the oil market. Tests for chaos (Lyapunov exponent test) will be conducted on these models, an attempt will be made to test for chaos in the movement of the price of oil dated from 2006 to 2016. The models implemented here are nonlinear models with the potential of exhibiting chaos for certain parameter values. Shocks will be introduced into the models and their effect on the models will be noted and visualized through the use of a time series or graphs. An Object oriented programming language (Java) was used in building this application, MYSQL database was used to save the data generated by the models and the spiral software development life-cycle was used in structuring, planning and controlling the process of building this application.


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Shocks, Demand & Supply, Mean Reversion, logistic Map, Nonlinear