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

  • Kim-Leng Goh

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

  • Kim-Lian Kok

    (Taylor's Business School, Malaysia)

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.

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Article provided by College of Business, and College of Finance, Feng Chia University, Taichung, Taiwan in its journal International Journal of Business and Economics.

Volume (Year): 5 (2006)
Issue (Month): 1 (April)
Pages: 41-59

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Handle: RePEc:ijb:journl:v:5:y:2006:i:1:p:41-59
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