Prediction of Multi-Currency Exchange Rates Using Deep Learning
Amit R. Nagpure
Amit R Nagpure, Department of Computer Science and Engineering, Ramdeobaba College of Engineering and Management, Nagpur (Maharashtra), India
Manuscript received on 07 April 2019 | Revised Manuscript received on 20 April 2019 | Manuscript published on 30 April 2019 | PP: 316-322 | Volume-8 Issue-6, April 2019 | Retrieval Number: F3578048619/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Predicting multi-currency exchange rates and processing time series information is often a significant issue in the economic market. This paper offers the prediction of top traded currencies in the world using different deep learning models which include top foreign exchange (Forex) currencies. This paper applies the Deep Learning model using Support Vector Regressor (SVR), Artificial Neural Network (ANN), Long Short-Term Memory (LSTM), Neural Network with Hidden Layers. They predict the exchange rate between world’s top traded currencies such as USD/EUR, USD/JPY, USD/GBP, USD/AUD, USD/CAD, USD/CHF, USD/CNY, USD/SEK, USD/NZD, USD/MXN and USD/INR from data by day, 30-39 years till December 2018.
Keyword: Artificial Neural Network (ANN), Deep Learning, Foreign Exchange (Forex), Long Short-Term Memory (LSTM) Network, Multi-currency, Machine Learning, Support Vector Regression (SVR).
Scope of the Article: Deep Learning