| Autor: |
Ghorpade, Naveen, Baraki, Parashuram, Biradar, Arun, M. R., Mahesh Kumar |
| Předmět: |
|
| Zdroj: |
Turkish Online Journal of Qualitative Inquiry; 2021, Vol. 12 Issue 10, p2282-2291, 10p |
| Abstrakt: |
Cryptocurrencies are now well-established and widely accepted as a form of alternative trading money. Because they have invaded nearly all accounting operations, cryptocurrency trading is often regarded as popular and propitious sorts of successful investments. A reliable forecasting and prediction model is essential for predicting the high volatility caused by the increase in financial market. This current work summarises various optimisation techniques by shedding light on the volatility factors like internal competition, market pressure, financial problems, social and political conflicts, etc. A comprehensive study is presented on how to predict the volatility of cryptocurrency and formulate their inter-connections with the parent Cryptocurrencies using various deep learning frameworks. Further, this work focuses on utilising sophisticated models to improve the forecasting performance of cryptocurrency. We are hopeful that this work will provide broader insights in the future research of cryptocurrency. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
|
