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The current problem of forecasting trends in the cryptocurrency market and modern approaches to solving them are considered. Two main factors have been identified that influence the value of cryptocurrency: the size of the cryptocurrency market and the growth rate of market volumes. The results of research on the prospects of the crypto market are presented, including the fact that Bitcoin in the future may be a protection against the fall of the US dollar for financial market participants. Researchers also view bitcoins not as cash, but as an investment asset. It is concluded that regulation and economic policies related to the use of cryptocurrencies are gradually being strengthened by many countries as its investment attractiveness increases. An analysis of the problem of forecasting the cryptocurrency market trend is presented. An analysis of research and publications on methods for predicting the value of cryptocurrency is presented. Traditional time series forecasting models, such as the ARIMA model, are effective for financial forecasting, but their use is less effective for markets with high volatility, which is typical for cryptocurrencies. Cryptocurrency price forecasting is a time series problem that can be solved using regression and other machine learning techniques. The results of modern research into the potential of machine learning in identifying complex trends and patterns are presented. It has been proven that deep learning methods can be effective in predicting time series with significant fluctuations and almost chaotic and unpredictable behavior. It is concluded that the main aspect is to create flexible models that can adapt to new data and changes in market dynamics. Combining traditional technical factor analysis techniques with innovative machine learning techniques can result in powerful hybrid models. These models use both quantitative and qualitative data to develop better forecasts. The feasibility of developing software systems that implement modern methods of artificial intelligence, including machine learning, deep learning, natural language processing and other technologies to provide market analysis, identify patterns and forecast crypto market trends is substantiated. The use of such software will assist investors in identifying potentially profitable investment opportunities, managing risks and making informed decisions in conditions of high uncertainty.
Москаленко et al. (Sun,) studied this question.