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 ANALYSIS OF THE EFFECTIVENESS OF USING SYNTHETIC ECONOMIC FACTORS TO PREDICT THE PRICES OF DIGITAL ASSETS OF THE NEXT DAY
Tác giả hoặc Nhóm tác giả: TRAN H.H.1, POLYAKOV P.A.1, STARCHENKOVA O.D.1, KONNIKOV E.A.1
Nơi đăng: ЭКОНОМИЧЕСКИЙ ВЕСТНИК Учредители: ИП Клюев Сергей Васильевич eISSN: 2949-4648; Số: 1;Từ->đến trang: 80-92;Năm: 2024
Lĩnh vực: Kinh tế; Loại: Bài báo khoa học; Thể loại: Quốc tế
TÓM TẮT
ABSTRACT
The relevance of this study is due to the fact that globalization affects not only the development of countries and individual sectors of the economy, but also what unites them all - a means of payment, store of value and exchange. Thus, thanks to modern technologies and the development of decentralized networks, blockchain and its by-product - a digital asset - appeared. Purpose of the study : to build predictive models to track changes in the price of digital coins such as Bitcoin and Binance coin. One of the main tasks was to determine the factors influencing future prices for digital assets, as well as to identify the most effective machine learning method for various data samples. The scientific novelty of the article lies in the concentration on relative synthetic factors, obtained by the simplest transformations from absolute indicators, and their use to build predictive models to predict the next day's price change for Bitcoin and Binance coin. To achieve their goals, the authors used various machine learning methods, which were applied on various data samples, including a stack of already predicted data. Mathematical and statistical processing was carried out using KNIME and Microsoft Excel software. The results of this study showed that machine learning methods can produce the required performance in predicting the direction of the future day's price on a stack of already predicted data. Applied nature of the research: the results obtained can be useful for traders and investors operating in the digital asset market.
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