Forecasting directional movement of Forex data using LSTM with technical and macroeconomic indicators

作     者：Deniz Can Yıldırım Ismail HakkıToroslu Ugo Fiore 

作者机构：Department of Computer EngineeringMiddle East Technical University06800 AnkaraTurkey Department of Management Studies and Quantitative MethodsParthenope University80132 NapoliNAItaly 

出 版 物：《Financial Innovation》 (金融创新（英文）)

年 卷 期：2021年第7卷第1期

页      面：1-36页

核心收录：

学科分类：07[理学] 0701[理学-数学] 070101[理学-基础数学] 

主　　题：Time series Forex Directional movement forecasting Technical and macroeconomic indicators LSTM 

摘      要：Forex(foreign exchange)is a special financial market that entails both high risks and high profit opportunities for *** is also a very simple market since traders can profit by just predicting the direction of the exchange rate between two ***,incorrect predictions in Forex may cause much higher losses than in other typical financial *** direction prediction requirement makes the problem quite different from other typical time-series forecasting *** this work,we used a popular deep learning tool called“long short-term memory(LSTM),which has been shown to be very effective in many time-series forecasting problems,to make direction predictions in *** utilized two different data sets—namely,macroeconomic data and technical indicator data—since in the financial world,fundamental and technical analysis are two main techniques,and they use those two data sets,*** proposed hybrid model,which combines two separate LSTMs corresponding to these two data sets,was found to be quite successful in experiments using real data.