Forecasting Interaction of Exchange Rates between Fiat Currencies and Cryptocurrencies Based on Deep Relation Networks

Chiao Ting Chen, Lin Kuan Chiang, Yi Cheng Huang, Szu Hao Huang

研究成果: Conference contribution

摘要

Forecasting exchange rates is difficult because financial time-series data is too complicated to analyze. In traditional financial studies, economic models and statistic approaches were widely used for predicting exchange rates. Recently, machine learning and deep learning techniques have played increasingly important roles in financial technology studies. This study adopts a deep learning technique called relation networks (RNs) to predict the exchange rates of fiat currencies and cryptocurrencies. To discover the relationship among different currencies, the concept of visual question answering (VQA) is applied in RNs. We also propose a specially designed architecture for the feature extraction stage to consider both spatial and temporal relationships simultaneously. The experimental results show that the proposed approach can achieve higher prediction performance for cryptocurrencies with approximately 65% accuracy rate. We aim to improve traditional approaches and construct a model using the concept of VQA based on RNs to optimize the prediction performance between fiat currencies and cryptocurrencies.

原文English
主出版物標題Proceedings - 2019 IEEE International Conference on Agents, ICA 2019
發行者Institute of Electrical and Electronics Engineers Inc.
頁面69-72
頁數4
ISBN(電子)9781728140261
DOIs
出版狀態Published - 十月 2019
事件2019 IEEE International Conference on Agents, ICA 2019 - Jinan, China
持續時間: 18 十月 201921 十月 2019

出版系列

名字Proceedings - 2019 IEEE International Conference on Agents, ICA 2019

Conference

Conference2019 IEEE International Conference on Agents, ICA 2019
國家China
城市Jinan
期間18/10/1921/10/19

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  • 引用此

    Chen, C. T., Chiang, L. K., Huang, Y. C., & Huang, S. H. (2019). Forecasting Interaction of Exchange Rates between Fiat Currencies and Cryptocurrencies Based on Deep Relation Networks. 於 Proceedings - 2019 IEEE International Conference on Agents, ICA 2019 (頁 69-72). [8929155] (Proceedings - 2019 IEEE International Conference on Agents, ICA 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/AGENTS.2019.8929155