The Application and Modeling for Conditional Heteroscedasticity Time Series

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.


Full Text: PDF DOI: 10.5539/mas.v3n6p113

Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.

Modern Applied Science   ISSN 1913-1844 (Print)   ISSN 1913-1852 (Online)

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