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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.
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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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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