期刊名称：International Journal of Computer Science Issues
印刷版ISSN：1694-0784
电子版ISSN：1694-0814
出版年度：2012
卷号：9
期号：6
出版社：IJCSI Press
摘要：Chart patterns and indicators are popular technical tools for making investment decisions. This article presents a trading strategy combining price movement patterns, candlestick chart patterns, and trading indicators, including Moving Average, Exponential Moving Average, Bollinger Bands, On Balance Volume, Relative Strength Index, Moving Average Convergence Divergence, and Stochastic Oscillator, with the aim to increase the return on investment. A neural network ensemble is employed to determine buy and sell signals on the next trading day. Experimental results, using stocks from five different industries in Stock Exchange of Thailand, show that the proposed strategy yields higher returns than do traditional technical trading methods
