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Detecting Chaotic Behavior in Agricultural Exchange-traded Funds

Jo-Hui Chen, Batsukh Tushigmaa, Yu-Fang Huang


This study investigates the chaos effect of agricultural exchange-traded funds (ETFs) using Brock, Dechert, and Scheinkman test, rescaled range analysis, and correlation dimension analysis. The standardized residuals from generalized autoregressive conditional heteroskedasticity models are fitted into eight ETFs and examined in each case for evidence of chaotic behavior. This study also examines whether or not the ETFs are consistent with the chaos effect based on the underlying random data with trend-reinforcing series. Research results outline the financial insights for the agricultural ETF field of investment forecasting to eliminate trading emotions, while pursuing considerable profitable experience for investors.


Agricultural ETF; Chaos Effect; Brock Dechert Scheinkman Test; Rescaled Range Analysis; Correlation Dimension Analysis

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、Bacsi, Z. (1997). “Modelling Chaotic Behaviour in Agricultural Prices Using a Discrete Deterministic Nonlinear Price Model,” Agricultural Systems, 55 (3), 445-459.

、Beck S. (2001). “Autoregressive Conditional Heteroscedasticity in Commodity Spot Prices”, Journal of Applied Econometrics, 16(2), 115-132.

、Benhabib, J. and Nishimura, K. (1979). “The Hopf Bifurcation and the Existence and Stability of Closed Orbits in Multi Sector Models of Optimal Economic Growth,” Journal of Economic Theory, 21, 421–444.

、Brock, W. A., W. Dechert, and Scheinkman J. (1987). “A Test for Independence Based on the Correlation Dimension,” Working paper, University of Winconsin at Madison, University of Houston, and University of Chicago.

、Brock, W. A., Dechert, W. D., Scheinkman, J. A. and Lebaron, B. (1996). “A Test for Independence Based on the Correlation Dimension," Econometric Reviews, 15 (3), 197-235.

、Chappell, D. and Panagiotidis, T. (2005). “Using the Correlation Dimension to Detect Nonlinear Dynamics: Evidence from the Athens Stock Exchange,” Finance Letters, 3 (4), 29-32.

、Chatrath, A., Adrangi, B., and Dhanda, K. K. (2001). “Are Commodity Prices Chaotic?,” Agricultural Economics, 27, 123–137.

、Day, R. H. (1992). “Complex Economic Dynamics: Obvious in History, Generic in Theory, Elusive in Data”, Journal of Applied Econometrics, 7, 9-23.

、DeCoster, G.P., Labys, W.C., Mitchell, D.W. (1992). “Evidence of Chaos in Commodity Futures Prices,” Journal of Futures Markets, 12, 291–305.

、Dickey, D.A. and Fuller, W.A. (1979). “Distribution of the Estimators for Autoregressive Time Series with a Unit Root,” Journal of the American Statistical Association, 74, 427-431.

、Djavanshir, G. R. and Khorramshahgol, R. (2006), “Applications of Chaos Theory for Mitigating Risks in Telecommunication Systems Planning in Global Competitive Market,” Journal of Global Competitiveness, 14(1), 15-24.

、Grandmont, J. M. (1988). “Nonlinear Economic Dynamics,” NY, Academic Press.

、Grassberger, P. and Procaccia, I. (1983). “Measuring the Strangeness of Strange Attractors,” Physical Review, 9, 189-208.

、Guegan, D. and Leroux, J. (2007). “Local Lyapunov Exponents: A New Way to Predict Chaotic,” Topics on Chaotic Systems, Systems World, in press.

、Hurst, H. E. (1951). “Long-term Storage Capacity of Reservoirs,” Transactions of the American Society of Civil Engineers, 116, 770–799.

、Ilan, G., Li, G. and MaCann, C. (2011). “Futures-based Commodities ETFs,” Securities Litigation and Consulting Group, Inc.

、Inamura Y., Kimata, T., Kimura, T. and Mutto, T. (2011). “Recent Surge in International Commodity Prices-impact of Financialization of Commodities and Globally Accommodative Monetary Conditions,” Bank of Japan Review, 2011-E-2.

、Kohzadi, N., Boyd, M. S., Kermanshahi, B., and Kaastra, I. (1996). “A Comparison of Artificial Neural Network and Time Series Models for Forecasting Commodity Prices”, Neurocomputing, 10, 169-181.

、LeBaron, B. (1994). “Chaos and Nonlinear Forecastability in Economics and Finance,” Philosophical Transactions of Royal Society of London Series a Physical Sciences and Engineering, 348, 397- 404.

、Mahmoodzadeh, S., Shahrabi, J., Pariazar, M. and Zaeri, M. S. (2007). “Project Selection by Using Fuzzy AHP and TOPSIS Technique,” World Academy of Science, Engineering and Technology, 30, 333-338.

、Moore, M. J. and Cullen, U. (1995). “Speculative Efficiency on the London Metal Exchange,” The Manchester School, 63, 235-256.

、Tang, K. and Xiong, W. (2010). “Index Investment and Financialization of Commodities”, Princeton University and NBER Working Paper.

、Tse, Yiuman (2012). “The Relationship among Agricultural Futures, ETFs, and the US Stock Market,” Review of Futures Markets, 20 (2), 141-159.

、Wolff, R. C. L. (1992). “Local Lyapunov Exponents: Looking Closely at Chaos,” Journal of the Royal Statistical Society, 54, 353-371.

、Wang, W., Vrijling J. K., Pieter H. A., Gelder, V., and Ma, J. (2005). “Testing for Nonlinearity of Streamflow Processes at Different Timescales,” Journal of Hydrology, 322, 1-22.

、Yang, S. and Brorsen, B. W. (1993). “Non-linear Dynamics of Daily Futures Prices: Conditional Heteroskedasticity or Chaos?,” Journal of Futures Markets, 13(2), 175-191.



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