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The Application and Modeling for Conditional Heteroscedasticity Time Series

Author

Listed:
  • Wenfang Su
  • Rui Shan
  • Jun Zhang
  • Yan Gao

Abstract

This article mainly presents the fundamental theory, model and application of conditional heteroscedasticity residual sequence. And it also gives detailed, scientific and exact analysis and research on a financial security example. Then summarizing a conclusion- Financial Securities follows specific rules and tracks through above study. The research indicates that ARCH model only applies to a short-term, auto-correlative heteroscedastic function ,whereas the amended GARCH model has the opposite result, that is, GARCH fits a long-term, auto-correlative heteroscedastic function. Meanwhile, SAS program presents more intuitive, exact tables and figures. All analysis and results show that AR (m)-GARCH fits well.

Suggested Citation

  • Wenfang Su & Rui Shan & Jun Zhang & Yan Gao, 2009. "The Application and Modeling for Conditional Heteroscedasticity Time Series," Modern Applied Science, Canadian Center of Science and Education, vol. 3(6), pages 113-113, June.
    • Handle: RePEc:ibn:masjnl:v:3:y:2009:i:6:p:113
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    References listed on IDEAS

    as
    1. Zhang, Xiaolong, 2007. "Inventory control under temporal demand heteroscedasticity," European Journal of Operational Research, Elsevier, vol. 182(1), pages 127-144, October.
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    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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