METHODOLOGICAL APPROACHES TO FORECASTING DYNAMICS OF CRYPTOCURRENCIES EXCHANGE RATE USING STOCHASTIC ANALYSIS TOOLS (ON THE EXAMPLE OF BITCOIN)

Abstract

The accelerated pace of development of the cryptocurrency market and its integration into the system of economic, operational, financial and other processes determines the need for a comprehensive study of this phenomenon. This is particularly relevant because in recent months, at the state level have intensified discussions on the prospects of the legalization of the cryptocurrency market and the possibility of using its tools in the economic activities of economic agents. Despite the sometimes polar views and approaches at the moment among Russian experts regarding the solution to this issue, the development of the crypto-currencies market is extremely high, regardless of its regulation. This determines and actualizes the scientific research in the field of evaluation of the prospects of development of this market, forming the subject of this study in order to predict the possible effects and risks for the national economic system. The purpose of the article is the development of tools of modelling and forecasting the volatility of the cryptocurrency market on the basis of “foreseeing” fluctuations in the value of “digital money” using special models of autoregression (ARMA, ARIMA). The study was based on the application of a class of parametric models. It allowed describing both stationary and non-stationary time series and on this basis to develop a system of prognostic estimates for the prospects of further development of the series under study. With the help of our ARIMA model, which evaluates the parameters of the analyzed time series of the cryptocurrency exchange rate, we developed a system of prognostic assessments for the short term. The authors proved that the application of such models with a high level of reliability predicts future adjustments in the market under study. It leads to a high level of prospects for their use in modelling future parameters of the cryptocurrency market development. This creates a basis for a business to develop adaptive mechanisms for to emerging price index adjustments of “digital money”.

Keywords

• cryptocurrency market
• bitcoin
• stochastic analysis
• forecasting
• autoregression models