Arch / garch-modeling in the study of the dynamics of the cryptocurrency market volatility (the bitcoin case)
The digitalization of business processes significantly changes the wellestablished models for the development of economic systems, forming new factors of socio-economic growth. This article proposes a cryptocurrency market forecasting toolkit based on building a model of autoregressive conditional heteroskedasticity. The paper enables the analysts to determine the most suitable model from the GARCH family for forecasting one of the most common and popular cryptocurrencies in the world - bitcoin. The proposed and tested tools make it possible to plan the development of the cryptocurrency market for the short term. This, in turn, can serve as the basis for monitoring and predicting future market adjustments, which allows coordination of state planning measures in this sector of economic relations.