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The Study on Dynamic Conditional Correlation-GARCH Model and its Application

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Bio-Inspired Computing -- Theories and Applications (BIC-TA 2015)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 562))

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Abstract

This paper studies the Dynamic Conditional Correlation-GARCH model with asymmetries in volatilities and applies the model to estimate the time-varying conditional correlations of stock market returns between Greece and other 8 European countries from January 1st, 2001 through October 31st, 2012. The results show that the cross-market correlations have varied over time and there exist asymmetries in volatilities.

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Author information

Authors and Affiliations

  1. College of Economics and Management, Shanghai Maritime University, Shanghai, 201306, China

    Ziyu Li

  2. College of Business Administration, University of New Orleans, New Orleans, LA, 70148, USA

    Atsuyuki Naka

Authors
  1. Ziyu Li
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  2. Atsuyuki Naka
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Corresponding author

Correspondence to Ziyu Li .

Editor information

Editors and Affiliations

  1. Xidian University, Xi'an, China

    Maoguo Gong

  2. Huazhong Univ. of Science and Technology, Wuhan, China

    Pan Linqiang

  3. University of Petroleum, Qingdao, China

    Song Tao

  4. University of Science and Technology of China, Hefei, China

    Ke Tang

  5. Anhui University, Hefei, China

    Xingyi Zhang

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© 2015 Springer-Verlag Berlin Heidelberg

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Li, Z., Naka, A. (2015). The Study on Dynamic Conditional Correlation-GARCH Model and its Application. In: Gong, M., Linqiang, P., Tao, S., Tang, K., Zhang, X. (eds) Bio-Inspired Computing -- Theories and Applications. BIC-TA 2015. Communications in Computer and Information Science, vol 562. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49014-3_22

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  • DOI: https://doi.org/10.1007/978-3-662-49014-3_22

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-49013-6

  • Online ISBN: 978-3-662-49014-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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