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Statistical Inadequacy of GARCH Models for Asian Stock Markets

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  • Kian-Ping Lim

    (Kian-Ping Lim (corresponding author) and Venus Khim-Sen Liew are at the Labuan School of International Business and Finance, Universiti Malaysia Sabah, Malaysia. E–mail: kianping@ums.edu.my)

  • Melvin J. Hinich

    (Melvin J. Hinich is at the Applied Research Laboratories, University of Texas at Austin.)

  • Venus Khim-Sen Liew

Abstract

This study employs the Hinich portmanteau bicorrelation test (Hinich 1996; Hinich and Patterson 1995) as a diagnostic tool to determine the adequacy of Generalised Autoregressive Conditional Heteroscedasticity (GARCH) models for eight Asian stock markets. The bicorrelation test results demonstrate that this type of model cannot provide an adequate characterisation for the underlying process of all the selected Asian stock markets. Further investigation using the windowed test procedure reveals that the violation of the covariance stationarity assumption as required by the GARCH process is due to the presence of transient epochs of dependencies in the data. The inadequacy of GARCH models has strong implications for the pricing of stock index options, portfolios selection, development of optimal hedging techniques and risk management.

Suggested Citation

  • Kian-Ping Lim & Melvin J. Hinich & Venus Khim-Sen Liew, 2005. "Statistical Inadequacy of GARCH Models for Asian Stock Markets," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 4(3), pages 263-279, December.
  • Handle: RePEc:sae:emffin:v:4:y:2005:i:3:p:263-279
    DOI: 10.1177/097265270500400303
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    5. Ehsan Ahmed & J. Barkley Rosser Jr. & Jamshed Y. Uppal, 2010. "Emerging Markets and Stock Market Bubbles: Nonlinear Speculation?," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 46(4), pages 23-40, January.

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