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Erg"un, Z. C., & KARABIYIK, B. K. Forecasting monero prices with a machine learning algorithm. Eskic{s}ehir Osmangazi "Universitesi .Iktisadi ve .Idari Bilimler Dergisi, 16(3), 651–663. 
Added by: Jack (2023-01-08 14:48)   Last edited by: Jack (2023-01-20 17:38)
Resource type: Journal Article
BibTeX citation key: Ergun
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Categories: Monero-focused
Creators: Erg"un, KARABIYIK
Collection: Eski\c{s}ehir Osmangazi \"Universitesi \.Iktisadi ve \.Idari Bilimler Dergisi
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Attachments   forecasting monero.pdf [8/18] URLs   https://dergipark. ... ticle-file/1751494
Abstract
Many researchers have attempted to forecast the values of different cryptocurrencies, but few studies analyzed the Monero price trends. Monero ranks first in terms of privacy features, and its demand is expected to grow in the future. This paper can be classified as the first to use the PATSOS model to forecast Monero prices and trends. According to the findings, the PATSOS model accurately forecasted future Monero prices with a very low error rate. Moreover, investors can withstand market volatility and avoid large losses by using the consistent "buy" and "sell" signals produced by the PATSOS mechanism.
Added by: Jack  Last edited by: Jack
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