Estimating Return Rate of Blockchain Financial Product by ANFIS-PSO Method
Yazarlar (3)
Doç. Dr. Şule Öztürk Birim Manisa Celâl Bayar Üniversitesi, Türkiye
Filiz Erataş Sönmez Manisa Celâl Bayar Üniversitesi, Türkiye
Doç. Dr. Yağmur SAĞLAM Sinop Üniversitesi, Türkiye
| Bildiri Türü | Tebliğ/Bildiri | Bildiri Dili | İngilizce |
| Bildiri Alt Türü | |||
| Bildiri Niteliği | Web of Science Kapsamındaki Kongre/Sempozyum | ||
| DOI Numarası | 10.1007/978-3-031-09173-5_92 | ||
| Kongre Adı | INFUS 2022 | ||
| Kongre Tarihi | 19-07-2022 / 21-07-2022 | ||
| Basıldığı Ülke | Türkiye | Basıldığı Şehir | İzmir |
| Bildiri Linki | https://link.springer.com/book/10.1007/978-3-031-09176-6 | ||
| UAK Araştırma Alanları |
Uluslararası Ticaret
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| Özet |
| Today, blockchain technology is developing rapidly and the volume of blockchain financial product trading is increasing rapidly as well. The aim of this study is to predict the return rates of cryptocurrencies with the help of artificial learning applications, considering the complex and unstable structure of the financial system. The rate of return is one of the important criteria used for investment decisions. Therefore, an efficient method for return rate prediction will help investors in preparing their portfolios. Ethereum, one of the top three most traded cryptocurrencies in the world, was chosen for empirical analysis. The adaptive neuro-fuzzy inference system approach (ANFIS) has emerged as a method that has been frequently used in recent years. ANFIS uses optimization algorithms to obtain the best prediction performance based on neural network modeling. The ANFIS approach has a multilayered structure consisting … |
| Anahtar Kelimeler |
| ANFIS | PSO | ANFIS-PSO | Cryptocurrencies | Bitcoin | Ethereum | Tether |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Web of Science | 6 |
| Google Scholar | 14 |