Forecasting stock price directional movements using technical indicators: Investigating window size effects on one-step-ahead forecasting
Forecasting stock price directional movements using technical indicators: Investigating window size effects on one-step-ahead forecasting
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使用技术指标预测股价方向变动：研究窗口大小对一步预测的影响
DOI：
10.1109/cifer.2014.6924093
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发表时间：
2014
期刊：
影响因子：
--
通讯作者：
A. Belatreche
中科院分区：
文献类型：
--
作者：
Yauheniya Shynkevich;T. McGinnity;S. Coleman;Yuhua Li;A. Belatreche
准确预测股票价格的方向性变化对于算法交易和投资管理非常重要。技术分析已成功地应用于财务预测，近年来研究人员对技术指标参数的优化进行了探索。本研究探讨了计算技术指标的窗口大小与一步前（可变步长）预测准确性之间的关系。使用技术分析和机器学习算法预测未来价格走势的方向。结果表明，支持向量机方法的窗口大小和预测步长之间的相关性，但不为其他方法。
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.