Time Series Analysis of Cryptocurrency Prices Using Long Short-Term Memory
Algorithms
; 15(7):230, 2022.
Article
in English
| ProQuest Central | ID: covidwho-1963659
ABSTRACT
Digitization is changing our world, creating innovative finance channels and emerging technology such as cryptocurrencies, which are applications of blockchain technology. However, cryptocurrency price volatility is one of this technology’s main trade-offs. In this paper, we explore a time series analysis using deep learning to study the volatility and to understand this behavior. We apply a long short-term memory model to learn the patterns within cryptocurrency close prices and to predict future prices. The proposed model learns from the close values. The performance of this model is evaluated using the root-mean-squared error and by comparing it to an ARIMA model.
Mathematics; prediction; cryptocurrency; LSTM; Currency; Accuracy; Investments; Artificial intelligence; Neural networks; Volatility; Venture capital; Digital currencies; Blockchain; Prices; Autoregressive models; Cryptography; Algorithms; Automation; Time series; Coronaviruses; New technology; COVID-19; Time series analysis
Full text:
Available
Collection:
Databases of international organizations
Database:
ProQuest Central
Type of study:
Experimental Studies
Language:
English
Journal:
Algorithms
Year:
2022
Document Type:
Article
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