Long Agricultural Futures Prices: ARCH, Long Memory, or Chaos Processes?

Wei, Anning; Leuthold, Raymond M.

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https://hdl.handle.net/2142/4053 Copy

Description

Title

Long Agricultural Futures Prices: ARCH, Long Memory, or Chaos Processes?

Author(s)

• Wei, Anning
• Leuthold, Raymond M.

Issue Date

1998-05

Keyword(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.

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 Name or Number

OFOR Working Paper Series, no. 98-03

Type of Resource

text

Language

en

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http://hdl.handle.net/2142/4053

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