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AuthorMesleh, Mahmoud
AuthorKiranyaz, Mustafa
Available date2024-07-24T10:13:52Z
Publication Date2021
Publication NameProceedings - 2021 2nd International Conference on Electronics, Communications and Information Technology, CECIT 2021
ResourceScopus
URIhttp://dx.doi.org/10.1109/CECIT53797.2021.00067
URIhttp://hdl.handle.net/10576/57074
AbstractThis study compiles 10 years of past daily closing prices for numerous trading assets, and economic reports. The data will be used to train, test, and validate a variety of ANN and LSTM models. This paper introduces a learning window that trains the network using a predefined number of days in the past to predict several days' closing prices in the future. A search grid algorithm is used to select the optimal hyperparameters for the networks. The MLP network managed to achieve an accuracy of above 80% when 30 days of the previous closing price were used as input to the network.
Languageen
PublisherInstitute of Electrical and Electronics Engineers Inc.
SubjectANN
artificial neural networks
financial market
Forex
LSTM
MLP
prediction
RNN
TitleCase Study: Predicting Future Forex Prices Using MLP and LSTM Models
TypeConference Paper
Pagination343-346
dc.accessType Abstract Only


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