Volume 5, No. 1, April 2006

 

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
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.
Key words: calendar effects; forecast; ARCH models; random walk
JEL classification: C53; G14

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