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Nonlinear and Complex Dynamics in Real Systems

Author

Listed:
  • William Barnett

    (University of Kansas)

  • Apostolos Serletis

    (University of Calgary)

  • Demitre Serletis

    (University of Toronto)

Abstract

This paper was produced for the El-Naschie Symposium on Nonlinear Dynamics in Shanghai in December 2005. In this paper we provide a review of the literature with respect to fluctuations in real systems and chaos. In doing so, we contrast the order and organization hypothesis of real systems with nonlinear chaotic dynamics and discuss some techniques used in distinguishing between stochastic and deterministic behavior. Moreover, we look at the issue of where and when the ideas of chaos could profitably be applied to real systems.

Suggested Citation

  • William Barnett & Apostolos Serletis & Demitre Serletis, 2005. "Nonlinear and Complex Dynamics in Real Systems," GE, Growth, Math methods 0509002, University Library of Munich, Germany.
    • Handle: RePEc:wpa:wuwpge:0509002
    Note: Type of Document - pdf; pages: 6. This conference paper is forthcoming in the El-Naschie Anniversary Issue of the International Journal of Nonlinear Sciences and Numerical Simulation
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    File URL: https://econwpa.ub.uni-muenchen.de/econ-wp/ge/papers/0509/0509002.pdf
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    References listed on IDEAS

    as
    1. Serletis, Apostolos & Gogas, Periklis, 1997. "Chaos in East European black market exchange rates," Research in Economics, Elsevier, vol. 51(4), pages 359-385, December.
    2. William Barnett, 2005. "Monetary Aggregation," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 200510, University of Kansas, Department of Economics, revised Mar 2005.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Mariolis, Theodore, 2010. "Κριτική Έκθεση του "Νόμου της Πτωτικής Τάσης του Ποσοστού Κέρδους" του K. Marx: Κατανομή Εισοδήματος, Επισώρευση Κεφαλαίου και Τεχνολογική Μεταβολή στη Μακρά Περίοδο [Critical Exposition of The Marxian 'Law of the Falling Rate of Profit'," MPRA Paper 22461, University Library of Munich, Germany.
    2. Xu, Weijun & Sun, Qi & Xiao, Weilin, 2012. "A new energy model to capture the behavior of energy price processes," Economic Modelling, Elsevier, vol. 29(5), pages 1585-1591.
    3. John Elder & Apostolos Serletis, 2008. "Long memory in energy futures prices," Review of Financial Economics, John Wiley & Sons, vol. 17(2), pages 146-155.
    4. Don M. Chance & Thomas A. Hanson & Weiping Li & Jayaram Muthuswamy, 2017. "A bias in the volatility smile," Review of Derivatives Research, Springer, vol. 20(1), pages 47-90, April.
    5. Monge, Manuel & Gil-Alana, Luis A. & Pérez de Gracia, Fernando, 2017. "Crude oil price behaviour before and after military conflicts and geopolitical events," Energy, Elsevier, vol. 120(C), pages 79-91.
    6. Orlando Gomes, 2007. "Routes to chaos in macroeconomic theory," Journal of Economic Studies, Emerald Group Publishing, vol. 33(6), pages 437-468, January.
    7. Orlando Gomes, 2006. "Routes to chaos in macroeconomic theory," Journal of Economic Studies, Emerald Group Publishing, vol. 33(6), pages 437-468, November.

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    Keywords

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    JEL classification:

    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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