Beating the Random Walk: Intraday Seasonality and Volatility in a Developing Stock Market
AbstractHistorical 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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Bibliographic InfoArticle 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)
calendar effects; forecast; ARCH models; random walk;
Find related papers by 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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