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

Abstract

Historical prices information has not been exhaustively exploited in forecasting the 10-_x000D_ 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.