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Forecasting stock price directional movements using technical indicators : Investigating window size effects on one-step-ahead forecasting

Shynkevich, Y, McGinnity, TM, Coleman, SA, Li, Y and Belatreche, A 2014, Forecasting stock price directional movements using technical indicators : Investigating window size effects on one-step-ahead forecasting , in: The Institute of Electrical and Electronics Engineers (IEEE) : Computational Intelligence for Financial Engineering and Economics Conference, 27-28 March 2014, London.

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Abstract

Accurate forecasting of directional changes in stock prices is important for algorithmic trading and investment management. Technical analysis has been successfully used in financial forecasting and recently researchers have explored the optimization of parameters for technical indicators. This study investigates the relationship between the window size used for calculating technical indicators and the accuracy of one-step-ahead (variable steps) forecasting. The directions of the future price movements are predicted using technical analysis and machine learning algorithms. Results show a correlation between window size and forecasting step size for the Support Vector Machines approach but not for the other approaches.

Item Type: Conference or Workshop Item (Paper)
Schools: Schools > School of Computing, Science and Engineering
Journal or Publication Title: Computational Intelligence for Financial Engineering & Economics (CIFEr), 2104 IEEE Conference
Publisher: The Institute of Electrical and Electronics Engineers (IEEE)
Refereed: Yes
Related URLs:
Funders: Non funded research
Depositing User: Yuhua Li
Date Deposited: 19 Jun 2015 18:26
Last Modified: 05 Apr 2016 18:18
URI: http://usir.salford.ac.uk/id/eprint/33103

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