Gencer, Murat and Unal, Gazanfer (2016): Testing NonLinear Dynamics, Long Memory and Chaotic Behaviour of Energy Commodities.

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Abstract
This paper contains a set of tests for nonlinearities in energy commodity prices. The tests comprise both standart diagnostic tests for revealing nonlinearities. The latter test procedures make use of models in chaos theory, socalled longmemory models and some asymmetric adjustment models. Empirical tests are carried our with daily data for crude oil, heating oil, gasoline and natural gas time series covering the period 20102015. Test result showed that there are strong nonlinearities in the data. The test for chaos, however, is weak or nonexisting. The evidence on long memory (in terms of rescaled range and fractional differencing) is somewhat stronger altough not very compelling.
Item Type:  MPRA Paper 

Original Title:  Testing NonLinear Dynamics, Long Memory and Chaotic Behaviour of Energy Commodities 
English Title:  Testing NonLinear Dynamics, Long Memory and Chaotic Behaviour of Energy Commodities 
Language:  English 
Keywords:  Energy commodities, Lyapunov exponents, Correlation dimension, chaos, long memory 
Subjects:  C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C15  Statistical Simulation Methods: General C  Mathematical and Quantitative Methods > C5  Econometric Modeling > C58  Financial Econometrics C  Mathematical and Quantitative Methods > C6  Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C63  Computational Techniques ; Simulation Modeling 
Item ID:  74115 
Depositing User:  Mr Murat Gencer 
Date Deposited:  04 Oct 2016 14:11 
Last Modified:  01 Oct 2019 17:35 
References:  Abarbanel H.D.I., Brown R. and M. B. Kennel, 1991, Variations of Lyapunov exponents on a strange attractor, Journal of Nonlinear Science 1, 175199. Abarbanel H.D.I., Brown R. and M. B. Kennel, 1992, Local Lyapunov exponents computed from observed data, Journal of Nonlinear Science 2, 343365. Abarbanel, H. D. I., 1996, Analysis of Observed Chaotic Data. Springer. New York. Adrangi, B., Chatrath, C., 2001, Chaos in oil prices? Evidence from futures market Energy Economics 23 405425 Bask, M. and Gençay, R., 1998, Testing chaotic dynamics via Lyapunov exponents, Physica D 114, 12. Bask, M., 1998, Deterministic chaos in exchange rates?, Umeå Economic Studies No 465c, Department of Economics, Umea University , Sweden BenSaida, A., 2014, Noisy chaos in intraday financial data: Evidence from the American index. Appl Math Compu., 226, 258–65 BenSaida, A., 2015, A practical test for noisy chaotic dynamics, ScienceDirect, SoftwareX 3–4, 1–5 Brock, W., Dechert, W., Scheinkman, J. and B. LeBaron, 1996, A test for independence based on the correlation dimension, Econometric Reviews 15, 197235. Chatrath, A., Adrangi, B., Dhanda, K., 2002, Are commodity prices chaotic? Agricultural economics 27 123137 Dechert W. and Gençay, R.,1992, Lyapunov exponents as a nonparametric diagnostic for stability analysis, Journal of Applied Econometrics 7, S41S60. Dechert W. and R. Gençay, 2000, Is the largest Lyapunov exponent preverved in embedded dynamics?, Physics Letters A 276, 5964. Eckmann J. P., Kamphorst S. O., D. Ruelle, and S. Ciliberto, 1986, Lyapunov exponents from time series, Phys. Rev. A, 34, no. 6, pp. 49714979 Eckmann, J. P. and D. Ruelle, 1985, Ergodic theory of chaos and strange attractors. Reviews of Modern Physics, 57, 617650. Gençay, R. and W. Dechert, 1992 , An algorithm for the n Lyapunov exponents of an ndimensional unknown dynamical system, Physica D 59, 142157. Gençay, R. and W. Dechert, 1996, The identification of spurious Lyapunov exponents in Jacobian algorithms, Studies in Nonlinear Dynamics and Econometrics 1, 145154. Gençay, R., 1996, A statistical framework for testing chaotic dynamics via Lyapunov exponents, Physica D 89, 261266. Grassberger, P. and I. Procaccia, 1983, Characterization of Strange Attractors, Physical Review Letters 50, 346394. Gunay S., 2015, Chaotic Structure of the BRIC Countries and Turkey’s Stock Market. International Journal of Economics and Financial Issues, 5(2), 515522. Kantz H. and Schreiber T., 2004, Nonlinear time series analysis. Cambridge University Press, 2nd edition. Panas, E., Ninni, V, 2000, Are oil markets chaotic? A nonlinear dynamic analysis Energy Economics 22 549568 Rosenstein, M., Collins, J.J. and De Luca, C.,1993, A practical method for calculating largest Lyapunov exponents from small data sets, Physica D 65, 117134. Schuster H. G., 1995, Deterministic Chaos: an introduction’, VCH Verlasgesellschaft, Germany. The MathWorks, Inc., 2015, MATLABR—The Language of TechnicalComputing, Natick, Massachusetts, URL http://www.mathworks.com/products/matlab. Wolf, A., Swift, B., Swinney, and Vastano, J., 1985, Determining Lyapunov exponents from a time series, Physica D 16, 285317. 
URI:  https://mpra.ub.unimuenchen.de/id/eprint/74115 