Использование глубоких моделей нейросетей для определения направления будущего движения рисковых компонент портфеля активов
| Parent link: | Курзина, И. А. (химик ; 1972-). Перспективы развития фундаментальных наук=Prospects of Fundamental Sciences Development: сборник научных трудов XX Международной конференции студентов, аспирантов и молодых ученых, г. Томск, 25-28 апреля 2023 г..— .— Томск: Изд-во ТПУ, 2023 Т. 3 : Математика.— 2023.— С. 31-33 |
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| Summary: | Заглавие с экрана In this article, technical analysis indicators are selected to predict the direction of the cryptocurrency price. We examined a set of technical analysis indicators used as explanatory variables in the current literature and specialized trading websites. Decision trees and deep neural networks were used as a model. Текстовый файл |
| Language: | Russian |
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2023
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| Online Access: | http://earchive.tpu.ru/handle/11683/80911 |
| Format: | Electronic Book Chapter |
| KOHA link: | https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=674336 |
| Summary: | Заглавие с экрана In this article, technical analysis indicators are selected to predict the direction of the cryptocurrency price. We examined a set of technical analysis indicators used as explanatory variables in the current literature and specialized trading websites. Decision trees and deep neural networks were used as a model. Текстовый файл |
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