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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

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  • 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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    1. Brock, William A. & Hommes, Cars H., 1998. "Heterogeneous beliefs and routes to chaos in a simple asset pricing model," Journal of Economic Dynamics and Control, Elsevier, vol. 22(8-9), pages 1235-1274, August.
    2. Lux, Thomas, 1998. "The socio-economic dynamics of speculative markets: interacting agents, chaos, and the fat tails of return distributions," Journal of Economic Behavior & Organization, Elsevier, vol. 33(2), pages 143-165, January.
    3. William A. Barnett & A. Ronald Gallant & Melvin J. Hinich & Jochen A. Jungeilges & Daniel T. Kaplan, 2004. "A Single-Blind Controlled Competition Among Tests for Nonlinearity and Chaos," Contributions to Economic Analysis, in: Functional Structure and Approximation in Econometrics, pages 581-615, Emerald Group Publishing Limited.
    4. Barkoulas, John T & Labys, Walter C & Onochie, Joseph I, 1999. "Long Memory In Futures Prices," The Financial Review, Eastern Finance Association, vol. 34(1), pages 91-100, February.
    5. Labys, W C & Lesourd, J B & Badillo, D, 1998. "The existence of metal price cycles," Resources Policy, Elsevier, vol. 24(3), pages 147-155, September.
    6. A. G. Malliaris & Jerome L. Stein, 2005. "Methodological issues in asset pricing: Random walk or chaotic dynamics," World Scientific Book Chapters, in: Economic Uncertainty, Instabilities And Asset Bubbles Selected Essays, chapter 8, pages 85-115, World Scientific Publishing Co. Pte. Ltd..
    7. Lo, Andrew W, 1991. "Long-Term Memory in Stock Market Prices," Econometrica, Econometric Society, vol. 59(5), pages 1279-1313, September.
    8. Nishimura, Kiyohiko G., 1998. "Expectation heterogeneity and price sensitivity," European Economic Review, Elsevier, vol. 42(3-5), pages 619-629, May.
    9. Wang, Jiang, 1994. "A Model of Competitive Stock Trading Volume," Journal of Political Economy, University of Chicago Press, vol. 102(1), pages 127-168, February.
    10. Jiang Wang, 1993. "A Model of Intertemporal Asset Prices Under Asymmetric Information," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 60(2), pages 249-282.
    11. Chiarella, Carl & Dieci, Roberto & Gardini, Laura, 2002. "Speculative behaviour and complex asset price dynamics: a global analysis," Journal of Economic Behavior & Organization, Elsevier, vol. 49(2), pages 173-197, October.
    12. Fernandez-Rodriguez, Fernando & Sosvilla-Rivero, Simon, 1998. "Testing nonlinear forecastability in time series: Theory and evidence from the EMS," Economics Letters, Elsevier, vol. 59(1), pages 49-63, April.
    13. Lux, Thomas, 1995. "Herd Behaviour, Bubbles and Crashes," Economic Journal, Royal Economic Society, vol. 105(431), pages 881-896, July.
    14. Catherine Kyrtsou & Michel Terraza, 2003. "Is it Possible to Study Chaotic and ARCH Behaviour Jointly? Application of a Noisy Mackey–Glass Equation with Heteroskedastic Errors to the Paris Stock Exchange Returns Series," Computational Economics, Springer;Society for Computational Economics, vol. 21(3), pages 257-276, June.
    15. Agnon, Yehuda & Golan, Amos & Shearer, Matthew, 1999. "Nonparametric, nonlinear, short-term forecasting: theory and evidence for nonlinearities in the commodity markets," Economics Letters, Elsevier, vol. 65(3), pages 293-299, December.
    16. 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.
    17. Gaunersdorfer, Andrea, 2000. "Endogenous fluctuations in a simple asset pricing model with heterogeneous agents," Journal of Economic Dynamics and Control, Elsevier, vol. 24(5-7), pages 799-831, June.
    18. M. M. Dacorogna & U. A. Muller & C. Jost & O. V. Pictet & J. R. Ward, 1995. "Heterogeneous real-time trading strategies in the foreign exchange market," The European Journal of Finance, Taylor & Francis Journals, vol. 1(4), pages 383-403.
    19. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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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. Catherine Kyrtsou & Michel Terraza, 2010. "Seasonal Mackey–Glass–GARCH process and short-term dynamics," Empirical Economics, Springer, vol. 38(2), pages 325-345, April.
    3. 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.
    4. Walter Labys, 2005. "Commodity Price Fluctuations: A Century of Analysis," Working Papers Working Paper 2005-01, Regional Research Institute, West Virginia University.
    5. Argel S. Masa & John Francis T. Diaz, 2017. "Long-memory Modelling and Forecasting of the Returns and Volatility of Exchange-traded Notes (ETNs)," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 11(1), pages 23-53, February.
    6. Vogl, Markus, 2022. "Controversy in financial chaos research and nonlinear dynamics: A short literature review," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. Kyrtsou, Catherine & Serletis, Apostolos, 2006. "Univariate tests for nonlinear structure," Journal of Macroeconomics, Elsevier, vol. 28(1), pages 154-168, March.
    14. 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.
    15. repec:rri:wpaper:200501 is not listed on IDEAS
    16. 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.
    17. Zheng, Shuxian & Tan, Zhanglu & Xing, Wanli & Zhou, Xuanru & Zhao, Pei & Yin, Xiuqi & Hu, Han, 2022. "A comparative exploration of the chaotic characteristics of Chinese and international copper futures prices," Resources Policy, Elsevier, vol. 78(C).
    18. John Francis Diaz & Jo-Hui Chen, 2017. "Testing for Long-memory and Chaos in the Returns of Currency Exchange-traded Notes (ETNs)," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 7(4), pages 1-2.
    19. 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.
    20. 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.
    21. 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).
    22. Marisa Faggini & Bruna Bruno & Anna Parziale, 2019. "Does Chaos Matter in Financial Time Series Analysis?," International Journal of Economics and Financial Issues, Econjournals, vol. 9(4), pages 18-24.

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    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;
    All these keywords.

    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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