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Noisy chaotic dynamics in commodity markets

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  • Catherine Kyrtsou

    ()

  • Walter C. Labys

    ()

  • Michel Terraza

    ()

Abstract

The nonlinear testing and modeling of economic and financial time series has increased substantially in recent years, enabling us to better understand market and price behavior, risk and the formation of expectations. Such tests have also been applied to commodity market behavior, providing evidence of heteroskedasticity, chaos, long memory, cyclicity, etc. The present evaluation of futures price behavior confirms that the resulting price movements can be random, suggesting noisy chaotic behavior. Prices could thus follow a mean process that is dynamic chaotic, coupled with a variance that follows a GARCH process. Our conclusion is that models of this type could be constructed to assist in forecasting prices in the short run but not over long run time periods. Copyright Springer-Verlag 2004

Suggested Citation

  • Catherine Kyrtsou & Walter C. Labys & Michel Terraza, 2004. "Noisy chaotic dynamics in commodity markets," Empirical Economics, Springer, vol. 29(3), pages 489-502, September.
  • Handle: RePEc:spr:empeco:v:29:y:2004:i:3:p:489-502
    DOI: 10.1007/s00181-003-0180-6
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Kyrtsou, Catherine & Labys, Walter C., 2007. "Detecting positive feedback in multivariate time series: The case of metal prices and US inflation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 377(1), pages 227-229.
    2. Kyrtsou, Catherine & Malliaris, Anastasios G. & Serletis, Apostolos, 2009. "Energy sector pricing: On the role of neglected nonlinearity," Energy Economics, Elsevier, vol. 31(3), pages 492-502, May.
    3. Resende, Marcelo & Zeidan, Rodrigo M., 2008. "Expectations and chaotic dynamics: Empirical evidence on exchange rates," Economics Letters, Elsevier, vol. 99(1), pages 33-35, April.
    4. Kyrtsou, Catherine & Serletis, Apostolos, 2006. "Univariate tests for nonlinear structure," Journal of Macroeconomics, Elsevier, vol. 28(1), pages 154-168, March.
    5. Kyrtsou, Catherine & Malliaris, Anastasios G., 2009. "The impact of information signals on market prices when agents have non-linear trading rules," Economic Modelling, Elsevier, vol. 26(1), pages 167-176, January.
    6. repec:spt:apfiba:v:7:y:2017:i:4:f:7_4_2 is not listed on IDEAS
    7. Constantinos VORLOW & Antonios ANTONIOU & Catherine KYRTSOU, 2004. "Surrogate Data Analysis and Stochastic Chaotic Modelling: Application to Stock Exchange Returns Series," Computing in Economics and Finance 2004 27, Society for Computational Economics.
    8. Catherine Kyrtsou & Michel Terraza, 2010. "Seasonal Mackey–Glass–GARCH process and short-term dynamics," Empirical Economics, Springer, vol. 38(2), pages 325-345, April.
    9. Walter C. Labys, 2003. "New Directions in the Modeling and Forecasting of Commodity Markets," Mondes en développement, De Boeck Université, vol. 122(2), pages 3-19.
    10. Walter Labys, 2005. "Commodity Price Fluctuations: A Century of Analysis," Working Papers Working Paper 2005-01, Regional Research Institute, West Virginia University.
    11. Yankou Diasso, 2014. "Dynamique du prix international du coton : aléas, aversion au risque et chaos," Recherches économiques de Louvain, De Boeck Université, vol. 80(4), pages 53-86.
    12. Kyrtsou, Catherine & Terraza, Michel, 2002. "Stochastic chaos or ARCH effects in stock series?: A comparative study," International Review of Financial Analysis, Elsevier, vol. 11(4), pages 407-431.
    13. Rachida Hennani, 2015. "Can the Lasota(1977)’s model compete with the Mackey-Glass(1977)’s model in nonlinear modelling of financial time series?," Working Papers 15-09, LAMETA, Universtiy of Montpellier, revised Jun 2015.
    14. Marisa Faggini, 2011. "Chaotic Time Series Analysis in Economics: Balance and Perspectives," Working papers 25, Former Department of Economics and Public Finance "G. Prato", University of Torino.
    15. Kyrtsou, Catherine & Labys, Walter C., 2006. "Evidence for chaotic dependence between US inflation and commodity prices," Journal of Macroeconomics, Elsevier, vol. 28(1), pages 256-266, March.
    16. repec:rri:wpaper:200501 is not listed on IDEAS
    17. Anagnostidis, Panagiotis & Emmanouilides, Christos J., 2015. "Nonlinearity in high-frequency stock returns: Evidence from the Athens Stock Exchange," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 421(C), pages 473-487.
    18. Claude Diebolt & Catherine Kyrtsou, 2006. "Non-Linear Perspectives for Population and Output Dynamics: New Evidence for Cliometrics," Working Papers 06-02, Association Française de Cliométrie (AFC).

    More about this item

    Keywords

    Commodity futures prices; risk and price expectations; noisy chaotic processes; correlation dimension analysis; nonlinear models; short term price forecasting; C22; E31; E32;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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