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Beating the Random Walk: Intraday Seasonality and Volatility in a Developing Stock Market

Author

Listed:
  • Kim-Leng Goh

    (Faculty of Economics and Administration, University of Malaya, Malaysia)

  • Kim-Lian Kok

    (Taylor's Business School, Malaysia)

Abstract

Historical prices information has not been exhaustively exploited in forecasting the 10-minute-ahead Composite Index of the Malaysian stock market. A simple model incorporating intraday seasonality can have lower forecast errors than a random walk. Improved accuracy is achieved when time-varying volatility is included in the time-of-day seasonal model for both in-sample and out-of-sample forecasts. The updating of parameter estimates of these volatility models at each new forecast origin to incorporate the latest available information leads to further improvement in forecast performance.

Suggested Citation

  • Kim-Leng Goh & Kim-Lian Kok, 2006. "Beating the Random Walk: Intraday Seasonality and Volatility in a Developing Stock Market," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 5(1), pages 41-59, April.
    • Handle: RePEc:ijb:journl:v:5:y:2006:i:1:p:41-59
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    Cited by:

    1. Jeffrey E. Jarrett, 2008. "Predicting Daily Stock Returns: A Lengthy Study of the Hong Kong and Tokyo Stock Exchanges," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 7(1), pages 37-51, April.

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    More about this item

    Keywords

    calendar effects; forecast; ARCH models; random walk;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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