From: Forex market forecasting using machine learning: Systematic Literature Review and meta-analysis
Author(s) | Year of Pub. | Book/Book Chapter/ Conf./Article/Thesis | Topic | Studies | Citations |
---|---|---|---|---|---|
Salman Ahmed, Saeed-Ul Hassan, Naif Radi Aljohani, Raheel Nawaz | 2020 | Elsevier | FLF-LSTM: A novel prediction system using Forex Loss Function | [P1] | [1] |
Pradyot Ranjan Jena, Ritanjali Majhi, Babita Majhi | 2015 | Elsevier | Development and performance evaluation of a novel knowledge guided artificial neural network (KGANN) model for exchange rate prediction | [P2] | [28] |
Juan Julián Cuéllar Abril | 2019 | IEEE | Currency Exchange Rate Prediction with Long Short-Term Memory Networks Based on Attention and News Sentiment Analysis | [P3] | [37] |
Svitlana Galeshchukand Sumitra Mukherjee | 2017 | SCITEPRESS – Science and Technology Publications, Lda. | Deep Learning for Predictions in Emerging Currency Markets | [P4] | [20] |
Dadabada Pradeepkumar and Vadlamani Ravi | 2014 | Springer | FOREX Rate Prediction Using Chaos, Neural Network and Particle Swarm Optimization | [P5] | [45] |
Michal DOBROVOLNY, Ivan SOUKAL, Kok Cheng LIM, Ali SELAMAT And Ondrej KREJCAR | 2020 | Hradec Economic days | Forecasting of FOREX Price Trend Using Recurrent Neural Network—Long Short-term Memory | [P6] | [14] |
Amit R. Nagpure | 2019 | International Journal of Innovative Technology and Exploring Engineering (IJITEE) | Prediction of Multi-Currency Exchange Rates Using Deep Learning | [P7] | [39] |
Md. Saiful Islam, Emam Hossain | 2020 | Elsevier | Foreign Exchange Currency Rate Prediction using a GRU-LSTM Hybrid Network | [P8] | [56] |
João Carapuço, Rui Neves, Nuno Horta | 2018 | Applied Soft Computing Journal | Reinforcement learning applied to Forex trading | [P9] | [8] |
Dadabada Pradeepkumar and Vadlamani Ravi | 2017 | Springer | FOREX Rate Prediction: A Hybrid Approach Using Chaos Theory and Multivariate Adaptive Regression Splines | [P10] | [58] |
Christian Gonz´alez Rojas, Molly Herman | 2018 | Elsevier | Foreign Exchange Forecasting via Machine Learning | [P11] | [21] |
Leslie C.O. Tiong, David C.L. Ngo, and Yunli Lee | 2013 | Researchgate | Forex Trading Prediction using Linear Regression Line, Artificial Neural Network and Dynamic Time Warping Algorithms | [P12] | [67] |
THEODOROS ZAFEIRIOU, DIMITRIS KALLES, | 2013 | International Journal on Artificial Intelligence Tools | short-term trend prediction of foreign exchange rates with a neural-network based ensemble of financial technical indicators | [P13] | [74] |
Boning Zhang | 2018 | Journal of Physics | Foreign exchange rates forecasting with an EMDLSTM neural networks model | [P14] | [75] |
Yaxin Qu1, Xue Zhao1 | 2019 | Journal of Physics | Application of LSTM Neural Network in Forecasting Foreign Exchange Price | [P15] | [48] |
Lina Ni, Yujie Li,Xiao Wang, Jinquan Zhang, Jiguo Yu, Chengming Qi | 2018 | Elsevier | Recurrent Neural Networks and ARIMA Models for Euro/Dollar Exchange Rate Forecasting | [P16] | [43] |
V.V.Kondratenko1 and Yu. A Kuperin | 2014 | Researchgate | Using Recurrent Neural Networks To Forecasting of Forex | [P17] | [35] |
Darko Vukovic | 2013 | Researchgate | Forex predicton with neural network: usd/eur currency pair | [P18] | [72] |
Ling Qi, Matloob Khushi, Josiah Poon | 2020 | Elsevier | Event-Driven LSTM For Forex Price Prediction | [P19] | [47] |
Alexander Jakob Dautel, Wolfgang Karl Härdle, Stefan Lessmann Hsin‑Vonn Seow | 2020 | Springer | Forex exchange rate forecasting using deep recurrent neural networks | [P20] | [13] |
Gunho Jung and Sun-Yong Choi | 2021 | Hindawi | Forecasting Foreign Exchange Volatility Using Deep Learning Autoencoder-LSTM Techniques | [P21] | [30] |
Dinesh K. Sharma, H.S. Hota, Richa Handa | 2017 | Review of Business and Technology Research, Vol. 14, No. 1, 2017, ISSN 1941-9414 | PREDICTION OF FOREIGN EXCHANGE RATE USING REGRESSION TECHNIQUES | [P22] | [61] |
Deniz Can Yıldırım, Ismail Hakkı Toroslu and Ugo Fiore | 2021 | Springer | Forecasting directional movement of Forex data using LSTM with technical and macroeconomic indicators | [P23] | [73] |
Thuy Nguyen Thi Thu, Vuong Dang Xuan | 2018 | IEEE | Using Support Vector Machine in FoRex Predicting | [P24] | [41] |
Francesco Rundo | 2019 | MDPI Applied Sciences | Deep LSTM with Reinforcement Learning Layer for Financial Trend Prediction in FX High Frequency Trading Systems | [P25] | [52] |
AREEJ ABDULLAH BAASHER, MOHAMED WALEED FAKHR | 2017 | Researchgate | Forex trend classification using machine learning techniques | [P26] | [3] |
Alexander Amo Baffour a, Jingchun Feng, Evans Kwesi Taylor, | 2019 | Elsevier | A hybrid artificial neural network-GJR modeling approach to forecasting currency exchange rate volatility | [P27] | [2] |
Krin Chinprasatsak, Nattee Niparnan, Attawith Sudsang | 2018 | Elsevier | ENMX: An elastic network model to predict the FOREX market evolution | [P28] | [9] |
Smruti Rekha Das, Debahuti Mishra, Minakhi Rout | 2017 | ScienceDirect | A hybridized ELM-Jaya forecasting model for currency exchange prediction | [P29] | [12] |
Mehreen Rehman,Gul Muhammad Khan, Sahibzada Ali Mahmud | 2014 | Elsevier | Foreign currency exchange rates prediction using CGP and Recurrent Neural Network | [P30] | [51] |
Paponpat Taveeapiradeecharoen, Kosin Chamnongthai, (senior member, ieee), and Nattapol Aunsri | 2019 | IEEE | Bayesian Compressed Vector Autoregression for Financial Time-Series Analysis and Forecasting | [P31] | [64] |
Mercedeh AmirAskari, Mohammad Bagher Menhaj | 2016 | IEEE | A modified fuzzy relational model approach to prediction of foreign exchange rates | [P32] | [25] |
Nathan D’Lima, Shamsuddin S. Khan | 2014 | International Journal of Engineering Research & Technology (IJERT) | FOREX Rate Prediction using A Hybrid System | [P33] | [11] |
Ahmad Bagheri, Hamed Mohammadi Peyhani, Mohsen Akbari | 2014 | Elsevier | Financial forecasting using ANFIS networks with Quantum-behaved 4 Particle Swarm Optimization | [P34] | [4] |
LudmilaDymova,PavelSevastjanov ∗ ,KrzysztofKaczmarek | 2016 | Elsevier | A Forex trading expert system based on a new approach to the rule-base evidential reasoning | [P35] | [15] |
Bernardo Jubert de Almeida, Rui Ferreira Neves,, Nuno Hortaa | 2017 | Applied Soft Computing | Combining Support Vector Machine with Genetic Algorithms to Optimize Investments in Forex Markets with High Leverage | [P36] | [29] |
Milton Saulo Raimundo, Jun Okamoto Jr. | 2018 | IEEE | SVR-Wavelet Adaptive Model for Forecasting Financial Time Series | [P37] | [49] |
Pradeepta Kumar Sarangi, Muskaan Chawla, Pinaki Ghosh, Sunny Singh, P.K. Singh | 2020 | Elsevier | FOREX trend analysis using machine learning techniques: INR vs USD currency exchange rate using ANN-GA hybrid approach | [P38] | [36] |
Yaroslav Vyklyuk1, Darko Vukovic2, Ana Jovanovic3 | 2013 | ACTUAL PROBLEMS OF ECONOMIICS #10((148)),,2013 | FOREX PREDICTION WITH NEURAL NETWORK: USD/EUR CURRENCY PAIR | [P39] | [69] |
Kristina Sanjaya Putria*, Siana Halima | 2020 | International Journal of Industrial Optimization | Currency movement forecasting using time series analysis and long short-term memory | [P40] | [46] |
ArashNegahdari Kia, Dr. SamanHaratizadeh and Dr. HadiZare | 2013 | Bonfring | Prediction of USD/JPY Exchange Rate Time Series Directional Status by KNN with Dynamic Time Warping AS Distance Function | [P41] | [34] |
Shian-Chang Huang Pei-Ju Chuang a, Cheng-Feng Wub, Hiuen-Jiun Lai a | 2010 | Elsevier | Chaos-based support vector regressions for exchange rate forecasting | [P42] | [24] |
Pedro Escudero, Willian Alcocer and Jenny Paredes | 2021 | MDPI | Recurrent Neural Networks and ARIMA Models for Euro/Dollar Exchange Rate Forecasting | [P43] | [16] |
Juszczuk Przemyslaw, Kozak Jan and Trynda Katarzyna | 2016 | Springer | Decision Trees on the Foreign Exchange Market | [P44] | [10] |
Sitti Wetenriajeng Sidehabi, Indrabayu1, Sofyan Tandungan2 | 2016 | IEEE | Statistical and Machine Learning Approach in Forex Prediction Based on Empirical Data | [P45] | [63] |
Dadabada Pradeepkumar and Vadlamani Ravi | 2017 | Springer | FOREX Rate Prediction: A Hybrid Approach Using Chaos Theory and Multivariate Adaptive Regression Splines | [P46] | [58] |
Gon_calo Abreu, Rui Neves, Nuno Horta | 2018 | Elsevier | Currency exchange prediction using machine learning, genetic algorithms and technical analysis | [P47] | [40] |
Thuy Nguyen Thi Thu1, Vuong Dang Xuan | 2018 | International Journal of Engineering & Technology | Forex trading using supervised machine learning | [P48] | [42] |
Theodoros Zafeiriou, Dimitris Kalles | 2020 | ACM | Intraday Ultra-Short-Term Forecasting of Foreign Exchange Rates using an Ensemble of Neural Networks based on Conventional Technical Indicators | [P49] | [58] |
Mihiran Rupasinghe, Malka N. Halgamuge, Nguyen Tran Quoc Vinh | 2019 | IEEE | Forecasting Trading-Time-based Profit-Making Strategies in Forex Industry: Using Australian Forex Data | [P50] | [53] |
Nima Shahbazi, Masoud M emarzadeh a nd Jarek G ryz1 | 2016 | MATEC Web of Conferences 6, ICIEA 2016 | Forex Market Prediction Using NARX Neural Network with Bagging | [P51] | [60] |
Gene I. Sher | 2012 | ACM | Forex Trading Using Geometry Sensitive Neural Networks | [P52] | [62] |
Leslie C.O. Tiong*, David C.L. Ngo, Yunli Lee | 2016 | Int. J. Computational Science and Engineering, Vol. 13, No. 4, 2016 | Forex prediction engine: framework, modelling techniques and implementations | [P53] | [66] |
Mustika Ulina, Ronsen Purba, Arwin Halim | 2021 | IEEE | Foreign Exchange Prediction using CEEMDAN and Improved FA-LSTM | [P54] | [68] |
Wenyu Wei, Pengfei Li | 2019 | Proceedings of 2019 International Conference on Advanced Information Science and System | Multi-Channel LSTM with Different Time Scales for Foreign Exchange Rate Prediction | [P55] | [70] |
AMAURY HERNANDEZ-AGUILA1, MARIO GARCÍA-VALDEZ 1, JUAN-JULIÁN MERELO-GUERVÓS2, MANUEL CASTAÑÓN-PUGA 3, AND OSCAR CASTILLO LÓPEZ 1, (Senior Member, IEEE) | 2021 | IEEE | Using Fuzzy Inference Systems for the Creation of Forex Market Predictive Models | [P56] | [22] |
Svitlana Galeshchuk, Sumitra Mukherjee | 2017 | Researchgate | Deep Networks for Predicting Direction of Change in Foreign Exchange Rates | [P57] | [19] |
Yiqi Zhao, Matloob Khushi | 2021 | IEEE | Wavelet Denoised-ResNet CNN and LightGBM Method to Predict Forex Rate of Change | [P58] | [76] |
Babu AS and Reddy SK | 2015 | Journal of Stock & Forex Trading | Exchange Rate Forecasting using ARIMA, Neural Network and Fuzzy Neuron | [P59] | [50] |
Alireza Sadeghi, Amir Daneshvar, Mahdi Madanchi Zaj | 2021 | Elsevier | Combined ensemble multi-class SVM and fuzzy NSGA-II for trend forecasting and trading in Forex markets | [P60] | [55] |