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The Study About Long Memory and Volatility Persistence in China Stock Market Based on Fractal Theory and GARCH Model

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Computer, Informatics, Cybernetics and Applications

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 107))

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Abstract

The research to volatility characteristics in financial market is foundation to the problems of capital assets pricing and avoiding strategy of financial risk. This chapter gives the empirical study about the long memory and volatility persistence in China stock market, using fractal spectral density estimation for time series and GARCH model, and gets some conclusions.

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Acknowledgment

This work was supported by Double support plan (school-level special) of Sichuan Agricultural University, 2011.

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Authors and Affiliations

  1. College of Business, Sichun Agricultural University, Dujiangyan, 611830, China

    Liu Cheng, Liu Jiankang & He Guozhu

Authors
  1. Liu Cheng
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  2. Liu Jiankang
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  3. He Guozhu
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Corresponding author

Correspondence to Liu Cheng .

Editor information

Editors and Affiliations

  1. Chinese Academy of Engineering, Beijing, China, People's Republic

    Xingui He

  2. Zhejiang Gongshang University, Beijing, China, People's Republic

    Ertian Hua

  3. Zhejiang Gongshang University, Hangzhou, China, People's Republic

    Yun Lin

  4. , School of Automation, Wuhan University of Technology, East District of Wuhan University, Luoshi Road 122, Wuhan, 4300, China, People's Republic

    Xiaozhu Liu

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© 2012 Springer Science+Business Media B.V.

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Cheng, L., Jiankang, L., Guozhu, H. (2012). The Study About Long Memory and Volatility Persistence in China Stock Market Based on Fractal Theory and GARCH Model. In: He, X., Hua, E., Lin, Y., Liu, X. (eds) Computer, Informatics, Cybernetics and Applications. Lecture Notes in Electrical Engineering, vol 107. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-1839-5_168

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  • DOI: https://doi.org/10.1007/978-94-007-1839-5_168

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  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-007-1838-8

  • Online ISBN: 978-94-007-1839-5

  • eBook Packages: EngineeringEngineering (R0)

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