近年來外匯市場因為各國經濟的問題變得越來難以掌握,投資人的信心隨著經濟新聞消息的宣布,而變的容易失控,彭雅玲( 2002 ),本研究的目的為:希望由藉由建置在倒傳遞類神經網路結合保力加指標(Bollinger Bands)與RSI(Relative Strength Index)指上標,來設計出於成功的自動交易策略,以解決投資人在外匯變得難以預測時,可以藉著自動交易系統的技術得到外匯投資上的保護以不至於發生重大的虧損,本研究所使用的工具為:MT4交易平台,使用的語言為:MQL4,實現於歐元/美元的交易。 在此研究當中引用了兩個傳統的外匯指標:保力加通道與RSI指標作為研究之指標,並且採用Fann(Fast Artificial Neural Network Library)的函式庫在MT4平台上來創造導傳遞類神經網路,其目的為借由訓練類神經來達成其自動交易之能力。
Foreign exchange market in recent years become increasingly difficult to grasp, and investor mind with the the economic news announce becomes easy to lose control, the purpose of this study: By building in on propagation neural network combined with Bollinger Bands indicator and the RSI (Relative Strength Index) to design for the success of automated trading strategies, when the foreign exchange becomes difficult to predict, the automated trading system can help investor to avoid a significant loss of foreign exchange market, the tools used in this study as follows: MT4 trading platform;MQL4 language; implemented on euro /us dollar ;two traditional Forex indicators: Bollinger Bands and RSI indicators; and Fann (Fast based Artificial Neural network library) library to create the propagation neural network in the MT4 platform, which aims to borrow neural reached the automated trading capabilities.