{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/83015"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/83015","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Long Agricultural Futures Price Series: ARCH, Long Memory, or Chaos Processes","abstract":"This study has advanced the research methods and procedures of nonlinear dynamics modeling. Some basic properties of ARCH processes have been highlighted since they were not given enough attention in the past and lead to the misuse of the ARCH model. The study has introduced the long memory model, especially the AFIMA model, to agricultural market study for the first time. The study suggests that various linear and nonlinear filters should be used carefully in chaos study since it has been found that they can distort potential chaotic structures in the data. 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