IDEAS home Printed from
   My bibliography  Save this article

Intraday volatility and periodicity in the Malaysian stock returns


  • Haniff, Mohd Nizal
  • Pok, Wee Ching


Many empirical studies using high-frequency intraday data from a variety of markets indicate that PGARCH models give superior return volatility forecasts than those produced from standard GARCH models. This paper investigates into modelling approaches of four versions of PGARCH models of high-frequency data of Bursa Malaysia, in particular where the intraday volatility of double U-shaped pattern. It is examined through half-hourly dummy variables, quarterly-hourly dummy variables, Fourier Functional Form (FFF) based variables and spline-based variables. The non-periodic GARCH models, i.e., GARCH, EGARCH and TARCH are used for comparison of performance of best fit. The analysis show that among the four versions of PGARCH models, the half-dummy and the spline-based versions perform the best. EGARCH produced consistently superior results to other GARCH specifications.

Suggested Citation

  • Haniff, Mohd Nizal & Pok, Wee Ching, 2010. "Intraday volatility and periodicity in the Malaysian stock returns," Research in International Business and Finance, Elsevier, vol. 24(3), pages 329-343, September.
  • Handle: RePEc:eee:riibaf:v:24:y:2010:i:3:p:329-343

    Download full text from publisher

    File URL:
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    1. Evans, Kevin P. & Speight, Alan E.H., 2010. "Intraday periodicity, calendar and announcement effects in Euro exchange rate volatility," Research in International Business and Finance, Elsevier, vol. 24(1), pages 82-101, January.
    2. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    3. Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June.
    4. Cheung, Yan-Leung & Ho, Richard Yan-Ki & Pope, Peter & Draper, Paul, 1994. "Intraday stock return volatility: The Hong Kong evidence," Pacific-Basin Finance Journal, Elsevier, vol. 2(2-3), pages 261-276, May.
    5. Bollerslev, Tim & Ghysels, Eric, 1996. "Periodic Autoregressive Conditional Heteroscedasticity," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(2), pages 139-151, April.
    6. Sébastien Laurent & Luc Bauwens & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109.
    7. Andersen, Torben G. & Bollerslev, Tim, 1997. "Intraday periodicity and volatility persistence in financial markets," Journal of Empirical Finance, Elsevier, vol. 4(2-3), pages 115-158, June.
    8. Gau, Yin-Feng, 2005. "Intraday volatility in the Taipei FX market," Pacific-Basin Finance Journal, Elsevier, vol. 13(4), pages 471-487, September.
    9. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    10. David McMillan & Alan Speight, 2004. "Intra-day periodicity, temporal aggregation and time-to-maturity in FTSE-100 index futures volatility," Applied Financial Economics, Taylor & Francis Journals, vol. 14(4), pages 253-263.
    11. Hua, Mingshu & Gau, Yin-Feng, 2006. "Determinants of periodic volatility of intraday exchange rates in the Taipei FX Market," Pacific-Basin Finance Journal, Elsevier, vol. 14(2), pages 193-208, April.
    12. Kitamura, Yoshihiro, 2010. "Testing for intraday interdependence and volatility spillover among the euro, the pound and the Swiss franc markets," Research in International Business and Finance, Elsevier, vol. 24(2), pages 158-171, June.
    13. Cao, C Q & Tsay, R S, 1992. "Nonlinear Time-Series Analysis of Stock Volatilities," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(S), pages 165-185, Suppl. De.
    14. Gau, Yin-Feng & Hua, Mingshu, 2007. "Intraday exchange rate volatility: ARCH, news and seasonality effects," The Quarterly Review of Economics and Finance, Elsevier, vol. 47(1), pages 135-158, March.
    15. Rabemananjara, R & Zakoian, J M, 1993. "Threshold Arch Models and Asymmetries in Volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(1), pages 31-49, Jan.-Marc.
    16. Akgiray, Vedat, 1989. "Conditional Heteroscedasticity in Time Series of Stock Returns: Evidence and Forecasts," The Journal of Business, University of Chicago Press, vol. 62(1), pages 55-80, January.
    17. Andersen, Torben G. & Bollerslev, Tim & Cai, Jun, 2000. "Intraday and interday volatility in the Japanese stock market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 10(2), pages 107-130, June.
    18. Tse, Y K & Tsui, Albert K C, 2002. "A Multivariate Generalized Autoregressive Conditional Heteroscedasticity Model with Time-Varying Correlations," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 351-362, July.
    Full references (including those not matched with items on IDEAS)


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. Miralles-Quirós, José Luis & Daza-Izquierdo, Julio, 2015. "Do DOW returns really influence the intraday Spanish stock market behavior?," Research in International Business and Finance, Elsevier, vol. 33(C), pages 99-126.
    2. Vortelinos, Dimitrios I., 2013. "Portfolio analysis of intraday covariance matrix in the Greek equity market," Research in International Business and Finance, Elsevier, vol. 27(1), pages 66-79.
    3. Balaban, Ercan & Ozgen, Tolga, 2016. "Trading session effects on stock returns and their conditional volatility: Firm-level evidence from a European Union accession country," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 446(C), pages 264-271.


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:riibaf:v:24:y:2010:i:3:p:329-343. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.