Trying to predict cryptocurrency prices using artificial neural network models Case study: (Bitcoin, Ethereum, Cardano)
Keywords:
cryptocurrency, artificial neural networks, Forecasting
Abstract
This study aims to predict the prices of encrypted digital currencies (Bitcoin, Ethereum, Cardano), which is one of the most attractive financial assets for investors as it has become of great importance in the economic field.
Artificial neural networks models were used to find out their effectiveness in predicting the prices of cryptocurrencies. The result confirmed that the PNN-type networks models are strong models in predicting the prices of these currencies in the short term, as the predicted values are very close to the actual values.
References
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• غياث عدنان. (2021). عملة كاردانو الرقمية Cardano شرح العملة المشفرة. . تاريخ الاسترداد 15 7, 2021، من مصاري: https://masary.net/
• يوسف محمد. (2021). عملة التيثر الرقمية : مميزاتها وكيفية شرائها ومستقبلها. تاريخ الاسترداد 15 6, 2021، من مدرسة التداول: https://tadawulschool.com
• CPMI. (2015). Report on Digital Currencies. usa: Bank for International.
• Grosan, C. A. (2011). Intelligent Systems A Modern Approach. springer.
• Media, F. (2021). Cryptocurrency. Consulté le 6 12, 2021, sur investing: https://sa.investing.com/crypto/currencies
• Nakamoto, S. (2008). Bitcoin: A Peer-to-Peer Electronic Cash System. Consulté le 6 13, 2021, sur / https://bitcoin.org/bitcoin.pdf
• Robby Houben, A. S. (2018). Cryptocurrencies and blockchain Legal context and implications for financial crime, money laundering and tax evasion, Policy Department for Economic, Scientific and Quality of Life Policies,. European Parliament.
Published
2022-01-03
Section
Articles