The relevance of the research subject is explained by the presence of a wide range of risks of the methodology for predicting bitcoin parameters, which is explained by the limitations of the research methods used and the increasing internal complexity of the processes of its functioning. The purpose of the research is to study the series of dynamics of the frequency of requests and the price of bitcoin under the conditions of taking into account the risks of using various forecasting methods. During the research, general scientific and special methods (neural networks, ARIMA models) were used. The scientific novelty of the research results consists in the proven importance of the role, statistical dependence and interdependence of the series of dynamics of the price of bitcoin and the frequency of its online requests. Also, the research grounded the approach and the forecasting procedure for the studied series of dynamics, which in essence correspond to the basic principles of the implementation of the forecasting methodology, take into account the specifics of the formation of the frequency of online requests for bitcoin prices and the socio-economic meaning of its functioning. The practical value consists in determining that the minimum risks for the study of a time series dynamics of bitcoin price and frequency of requests for bitcoin price were demonstrated by the neural network methodology in comparison with the use of the ARIMA model.