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Title:Long Agricultural Futures Prices: ARCH, Long Memory, or Chaos Processes?
Author(s):Wei, Anning; Leuthold, Raymond M.
Subject(s):AFIMA model
correlation dimension
Lyapunov exponent
Abstract:Price series that are 21.5 years long for six agricultural futures markets, corn, soybeans, wheat, hogs, coffee and sugar, possess characteristics consistent with nonlinear dynamics. Three nonlinear models, ARCH, long memory and chaos, are able to produce these symptoms. Using daily, weekly and monthly data for the six markets, each of these models is tested against the martingale difference null, one-by-one. Standard ARCH tests suggest that all series might contain ARCH effects, but further diagnostics show that the series are not ARCH processes, failing to reject the null. A long-memory technique, the AFIMA model, fails to find long-memory structures in the data, except for sugar. This allows chaos analysis to be applied directly to the raw data. Carefully specifying phase space, and utilizing correlation dimension and Lyapunov exponent together, the remaining five price series are found to be chaotic processes.
Issue Date:1998-05
Publisher:Office for Futures and Options Research, Department of Agricultural Economics, College of Agricultural, Consumer, and Environmental Sciences at the University of Illinois at Urbana-Champaign
Series/Report:OFOR Working Paper Series, no. 98-03
Genre:Working / Discussion Paper
Publication Status:published or submitted for publication
Peer Reviewed:not peer reviewed
Date Available in IDEALS:2008-03-18

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