Ayitey Junior, M., Appiahene, P., Appiah, O., & Bombie, C. N. (2023). Forex market forecasting using machine learning: Systematic Literature Review and meta-analysis. Journal of Big Data, 10(9). https://doi.org/10.1186/s40537-022-00676-2
2023
Forex
LSTM, ANN
No
No
2
Gan, L., Wang, H., & Yang, Z. (2020). Machine learning solutions to challenges in finance: An application to the pricing of financial products. Technological Forecasting & Social Change, 153, 119928.
2020
Financial Market
Deep Learning, BP
Yes
Yes
3
Henrique, B. M., Sobreiro, V. A., & Kimura, H. (2019). Literature review: Machine learning techniques applied to financial market prediction. Expert Systems With Applications, 124, 226–251.
2019
Stock
ANN
Yes
Yes
4
Chen, W., Xu, H., Jia, L., & Gao, Y. (2021). Machine learning model for Bitcoin exchange rate prediction using economic and technology determinants.
2021
Crypto
LSTM
Yes
Yes
5
Oktaba, P., Grzywi?ska-R?pca, M. (2023). Modification of technical analysis indicators and increasing the rate of return on investment. Central European Economic Journal.
2023
Forex
No Machine Learning
No
No
6
Maté, C. G. (2022). Forecasting in FOREX the spot price interval of tomorrow with the same information of today. An analysis of the seven majors using a linear regression model based on interval arithmetic. Knowledge-Based Systems, 258, 109923.
2022
Forex
alpha-[B]
No
Yes
7
Alonso-Monsalve, S., Suárez-Cetrulo, A. L., Cervantes, A., & Quintana, D. (2020). Convolution on neural networks for high-frequency trend prediction of cryptocurrency exchange rates using technical indicators.
2020
Crypto
LSTM
Yes
No
8
Adegboye, A., & Kampouridis, M. (2021). Machine learning classification and regression models for predicting directional changes trend reversal in FX markets.
2021
Forex
C + GP + TS
Yes
Yes
9
Wang, G., Ma, J., Wang, Y., Tao, T., Ren, G., & Zhu, H. (2023). SUDF-RS: A new foreign exchange rate prediction method considering the complementarity of supervised and unsupervised deep representation features.
2023
Forex
SUDF-RS
No
Yes
10
Dash, S., Sahu, P.K., Mishra, D., Mallick, P.K., Sharma, B., Zymbler, M., & Kumar, S. (2022). A Novel Algorithmic Forex Trade and Trend Analysis Framework Based on Deep Predictive Coding Network Optimized with Reptile Search Algorithm. Axioms, 11, 396. https://doi.org/10.3390/axioms11080396
2022
Forex
RSA-DPCN
No
Yes
11
Gülmez, B. (2023). Stock price prediction with optimized deep LSTM network with artificial rabbits optimization algorithm.
2023
Stock
LSTM-ARO
No
No
12
Henrique, B. M., Sobreiro, V. A., & Kimura, H. (2023). Practical machine learning: Forecasting daily financial markets directions.
2023
Financial Market
SVM
No
No
13
Rambi, W. Y. V., Wibowo, S. A., & Rizal, S. (2024). Analisis Kinerja Expert Advisor Trading-dong dengan Pendekatan Support dan Resistance.
2024
Forex
No Machine Learning
No
No
14
Kalluri Ram Rohith Reddy, Kankanala Kowsick Raja, P. Subham, & Puspanjali Mohapatra. (2024). Forex Market Analysis Using Deep Learning Approaches.
2024
Forex
GRU
No
No
15
Kusumodestoni, R. H., & Suyatno. (2015). Prediction of Forex Using Neural Network Model.
2015
Forex
Neural Network (Backpropagation)
No
No
16
Baradja, A., Sukoco, & Tjendrowasono, T. I. (2022). Penerapan Machine Learning untuk Meningkatkan Prediksi Mata Uang Forex dengan Indikator Teknikal.
2022
Forex
GBM
No
Yes
17
Kaushik, M., & Giri, A. (2020). Forecasting Foreign Exchange Rate: A Multivariate Comparative Analysis between Traditional Econometric, Contemporary Machine Learning & Deep Learning Techniques.
2020
Forex
LSTM
No
No
18
Qi, L., Khushi, M., & Poon, J. (2024). Event-Driven LSTM For Forex Price Prediction.
2024
Forex
LSTM
No
Yes
19
Hu, Z., Zhao, Y., & Khushi, M. (2021). A Survey of Forex and Stock Price Prediction Using Deep Learning.
2021
Forex
LSTM
Yes
Yes
20
Zafeiriou, T., & Kalles, D. (2024). Comparative analysis of neural network architectures for short-term FOREX forecasting.
2024
Forex
ANN
No
Yes
21
Saadati, S., & Manthouri, M. (2024). Forecasting Foreign Exchange Market Prices Using Technical Indicators with Deep Learning and Attention Mechanism.
2024
Forex
LSTM-CNN1D
No
No
22
Edi, M., & Utami, E. (2023). Price Prediction on USDCHF Pair Forex Trading Using Linear Regression.
2023
Forex
REGRESI LINIER
No
No
23
Rundo, F. (2019). Deep LSTM with Reinforcement Learning Layer for Financial Trend Prediction in FX High Frequency Trading Systems.
2019
Forex
LSTM
No
Yes
24
Rosita, Y. D., & Moonlight, L. S. (2024). Comparative Analysis of LSTM Neural Network and SVM for USD Exchange Rate Prediction: A Study on Different Training Data Scenarios.
2024
Forex
LSTM
No
No
25
Ahmed, S., Hassan, S.-U., Aljohani, N. R., & Nawaz, R. (2020). FLF-LSTM: A novel prediction system using Forex Loss Function. Applied Soft Computing, 97, 106780.
2020
Forex
LSTM
No
Yes
26
Zhang, Y., & Hamori, S. (2020). The predictability of the exchange rate when combining machine learning and fundamental models. Journal of Risk and Financial Management, 13(3), 48. https://doi.org/10.3390/jrfm13030048
2020
Forex
Neural Network
No
No
27
Perla, S., Bisoi, R., & Dash, P.K. (2023). A hybrid neural network and optimization algorithm for forecasting and trend detection of Forex market indices. Decision Analytics Journal, 6, 100193.
2023
Forex
DKRVFLN-AE
No
No
28
Roondiwala, M., Patel, H., & Varma, S. (2017). Predicting Stock Prices Using LSTM.
2017
Stock
LSTM
No
No
29
Khattak, B. H. A., Shafi, I., Khan, A. S., Flores, E. S., García Lara, R., Samad, M. A., & Ashraf, I. (2023). A Systematic Survey of AI Models in Financial Market Forecasting for Profitability Analysis.
2023
Financial Market
LSTM
No
No
30
Meirinaldi, Y., Yolanda, & Seputra, Y. E. A. (2022). Analysis of Foreign Exchange Using Perceptron and Genetic Algorithm Machine Learning (GALM).
2022
Forex
GALM
No
No
31
Qu, Y., & Zhao, X. (2019). Application of LSTM Neural Network in Forecasting Foreign Exchange Price.
2019
Forex
LSTM
No
No
32
Zhang, C., Sjarif, N. N. A., & Ibrahim, R. (2024). Deep learning models for price forecasting of financial time series: A review of recent advancements: 2020–2022. WIREs Data Mining and Knowledge Discovery, 14(1), e1519. https://doi.org/10.1002/widm.1519
2024
Financial Market
Transformers
No
No
33
Gyamerah, S. A., & Moyo, E. (2020). Long-Term Exchange Rate Probability Density Forecasting Using Gaussian Kernel and Quantile Random Forest.
2020
Forex
GQRF
No
No
34
Jia, H. (2021). Deep Learning Algorithm-Based Financial Prediction Models.
2021
Forex
FEPA
No
Yes
35
Kurujitkosol, T., Takhom, A., & Usanavasin, S. (2022). Automated Forex Trading System Using Stacked Machine Learning and Technical Analysis.
2022
Forex
LSTM
No
Yes
36
Nguyen, P. D., Thao, N. N., Chi, D. T. K., Nguyen, H. C., Mach, B. N., & Nguyen, T. Q. (2024). Deep learning-based predictive models for forex market trends: Practical implementation and performance evaluation.
2024
Forex
LSTM
No
Yes
37
Khoa, B. T., & Huynh, T. T. (2022). Long Short-Term Memory Recurrent Neural Network for Predicting the Return of Rate Underframe the Fama-French 5 Factor.
2022
Stock
LSTM-RNN
No
Yes
38
Echrigi, R., & Hamiche, M. (2023). Optimizing LSTM Models for EUR/USD Prediction in the context of reducing energy consumption: An Analysis of Mean Squared Error, Mean Absolute Error and R-Squared.
2023
Forex
LSTM
No
No
39
García, F.; Guijarro, F.; Oliver, J.; Tamoši$3;nien?, R. (2024). Foreign Exchange Forecasting Models: LSTM and BiLSTM Comparison. Eng. Proc. 68, 19. https://doi.org/10.3390/engproc2024068019
2024
Forex
BiLSTM
No
No
40
El Mahjouby, M., El Fahssi, K., Bennani, M. T., Lamrini, M., & El Far, M. (2024). Machine Learning Techniques for Predicting and Classifying Exchange Rates between US Dollars and Japanese Yen.
2024
Forex
LR+XGB+GNB
No
No
41
Tsuji, C. (2022). Exchange Rate Forecasting via a Machine Learning Approach.
2022
Forex
RF
No
No
42
Milke, V., Luca, C., & Wilson, G. B. (2024). Reduction of financial tick big data for intraday trading. Expert Systems, 41(7), e13537. https://doi.org/10.1111/exsy.13537
Dobrovolny, M., Soukal, I., Lim, K. C., Selamat, A., & Krejcar, O. (2020). Forecasting of FOREX Price Trend Using Recurrent Neural Network - Long Short-term Memory.
2020
Forex
LSTM
No
No
45
Falat, L., Marcek, D., & Durisova, M. (2016). Intelligent Soft Computing on Forex: Exchange Rates Forecasting with Hybrid Radial Basis Neural Network.
2016
Forex
RBF-SMA
No
Yes
46
Nguyen, T. N. T., & Vuong, D. X. (2018). FoRex Trading Using Supervised Machine Learning.
2018
Forex
SVM
No
Yes
47
Tian, T. (2024). Integrating deep learning and innovative feature selection for improved short-term price prediction in futures markets.
2024
Financial Market
CNN_LSTM, GRU_LSTM
No
Yes
48
Ni, L., Li, Y., Wang, X., Zhang, J., Yu, J., & Qi, C. (2019). Forecasting of Forex Time Series Data Based on Deep Learning.
2019
Forex
C-RNN
No
Yes
49
Trading strategy model based on LSTM neural network and Extreme Value-Dynamic programming
2022
Financial Market
LSTM
No
Yes
50
Gandhmal, D. P., & Kumar, K. (2019). Systematic analysis and review of stock market prediction techniques. Computer Science Review, 34, 100190.
2019
Stock
ANN
No
No
51
Kabir, M. R. (2024). LSTM-Transformer based Robust Hybrid Deep Learning Model for Financial Time Series Forecasting.
2024
Financial Market
LSTM-mTrans-MLP
No
Yes
52
Panagopoulos, P. (2024). NEAT vs LSTM vs XGBoost. Three novel methods introduced and compared on forex trading.
2024
Forex
NEAT
No
Yes
53
Global stock market investment strategies based on financial network indicators using machine learning techniques
2019
Stock
SVM
No
Yes
54
Alaminos, D., Salas, M. B., & Partal-Ureña, A. (2024). Hybrid ARMA-GARCH-Neural Networks for intraday strategy exploration in high-frequency trading. Pattern Recognition, 148, 110139.
2024
Stock
ARMA-GARCH-QRNN
No
Yes
55
Wijesinghe, S. (2023). Time Series Forecasting: Analysis of LSTM Neural Networks to Predict Exchange Rates of Currencies.
2023
Forex
LSTM
No
No
56
Casolaro, A., Capone, V., Iannuzzo, G., & Camastra, F. (2023). Deep Learning for Time Series Forecasting: Advances and Open Problems. Information, 14(11), 598. https://doi.org/10.3390/info14110598
2023
Stock
Transformers
No
No
57
Tsang, E. P. K., Ma, S., & Chinthalapati, V. L. R. (2024). Nowcasting directional change in high frequency FX markets.
2024
Forex
No Machine Learning
No
Yes
58
Firouzjaee, J. T., & Khalilian, P. (2024). The Interpretability of LSTM Models for Predicting Oil Company Stocks: Impact of Correlated Features.
2024
Financial Market
LSTM
No
No
59
Erem, E. (2023). Forecasting Exchange Rates Using Artificial Neural Networks.
2023
Forex
ANN
No
No
60
Borovkova, S., & Tsiamas, I. (2019). An ensemble of LSTM neural networks for high-frequency stock market classification.
2019
Stock
LSTM
No
Yes
61
Dautel, A. J., Härdle, W. K., Lessmann, S., & Seow, H. V. (2019). Forex Exchange Rate Forecasting Using Deep Recurrent Neural Networks. IRTG 1792 Discussion Paper, No. 2019-008.
2019
Forex
GRU
No
No
62
Ghahremani, S., & Nguyen, U. T. (2025). Prediction of foreign currency exchange rates using an attention-based long short-term memory network. Machine Learning with Applications, 20, 100648.
2025
Forex
LSTM
No
Yes
63
Kehinde, T. O., Khan, W. A., & Chung, S. H. (2023). Financial Market Forecasting using RNN, LSTM, BILSTM, GRU and Transformer-Based Deep Learning Algorithms. Proceedings of the IEOM International Conference on Smart Mobility and Vehicle Electrification.
2023
Financial Market
MAE
No
No
64
Ouf, S., El Hawary, M., Aboutabl, A., & Adel, S. (2024). A Deep Learning-Based LSTM for Stock Price Prediction Using Twitter Sentiment Analysis. International Journal of Advanced Computer Science and Applications, 15(12).
2024
Stock
XGBoost
Yes
Yes
65
Dave, Y. (2024). Predicting Forex Pair Movements: Integrating Sentiment Analysis, Technical, and Fundamental Indicators using Machine Learning and Deep Learning Models. Unitec Institute of Technology.
2024
Forex
XGBoost
No
No
66
Windsor, E., & Cao, W. (2022). Improving exchange rate forecasting via a new deep multimodal fusion model. Applied Intelligence, 52, 16701–16717.
2022
Forex
LSTM
Yes
Yes
67
Zhou, T. (2019). Forex trend forecasting based on long short term memory and its variations with hybrid activation functions (Doctoral dissertation). Brunel University London.
2019
Forex
LSTM
No
Yes
68
Burgess, M., Javed, F., Okpara, N., & Robinson, C. (2022). Stock Forecasts with LSTM and Web Sentiment. SMU Data Science Review, 6(2), Article 10.
2022
Stock
ARIMA
Yes
Yes
69
Yildirim, D. C., Toroslu, I. H., & Fiore, U. (2021). Forecasting directional movement of Forex data using LSTM with technical and macroeconomic indicators. Financial Innovation, 7(1), 1-36
2021
Forex
LSTM
No
Yes
70
Abdullah, W., & Salah, A. (2023). A novel hybrid deep learning model for price prediction. International Journal of Electrical and Computer Engineering (IJECE), 13(3), 3420-3431.