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Setting the Stochastic Model for Mid-Term Prediction of Cryptocurrency Exchange Rate: The Bitcoin Case

Safiullin M.R. Kazan (Volga Region) Federal University (KFU), Kazan, Republic of Tatarstan, Russian Federation ( Marat.Safiullin@tatar.ru )

El'shin L.A. University of Management TISBI, Kazan, Republic of Tatarstan, Russian Federation ( Leonid.Elshin@tatar.ru )

Abdukaeva A.A. Center of Advanced Economic Research in Academy of Sciences of Republic of Tatarstan, Kazan, Republic of Tatarstan, Russian Federation ( Aliya.Abdukaeva@tatar.ru )

Journal: Digest Finance, #3, 2018

Importance The article discusses the process of economic and mathematical modeling of time series describing the volatility of the bitcoin exchange rate through the Autoregressive Moving Average (ARMA) models.
Objectives We search for, and substantiate tools and mechanisms used to predict the cryptocurrency market developments.
Methods The research applies tools of stochastic analysis of stationary and non-stationary time series.
Results The ARIMA models provide for rather precise estimates of current and future changes in the digital money rates for a three to four month’s time.
Conclusions and Relevance The bitcoin price will have approximated USD 11,000 by the end of Q3 2018. The methodological approaches to modeling help determine not only future trends, but also changes in exchange rates throughout the entire analyzable period. The findings provide empirical information for cryptocurrency market regulators and business community.


Developing a stochastic model for medium-term forecasting of cryptocurrency exchange rate: The bitcoin case

Safiullin M.R. Kazan (Volga Region) Federal University, Kazan, Republic of Tatarstan, Russian Federation ( Marat.Safiullin@tatar.ru )

El'shin L.A. University of Management TISBI, Kazan, Zelenodolsk, Republic of Tatarstan, Russian Federation ( Leonid.Elshin@tatar.ru )

Abdukaeva A.A. Center of Advanced Economic Research in the Academy of Sciences of the Republic of Tatarstan, Kazan, Republic of Tatarstan, Russian Federation ( Aliya.Abdukaeva@tatar.ru )

Journal: Finance and Credit, #5, 2018

Importance The article considers the process of economic and mathematical modeling of time series characterizing the volatility of bitcoin exchange rate on the basis of autoregressive moving average models.
Objectives The purpose of the work is to provide a scientific rationale for tools and mechanisms to forecast the cryptocurrency market development.
Methods The study rests on tools of stochastic analysis of stationary and non-stationary time series characterizing the volatility in the global cryptocurrency market.
Results We prove that ARIMA models enable to predict current and future adjustments of cryptocurrency exchange rates with a high level of accuracy.
Conclusions and Relevance We found that by the end of the third quarter of 2018, the bitcoin market value will be about 11,000 USD. The methodological approaches of modeling help define future trends and fluctuations of exchange rates over the entire forecast period. The findings are of practical interest for both the public authorities and representatives of business community.


A descriptive and formalized analysis of the digital economy's development in Russia: A case study of the assessment of demand for blockchain technology

Safiullin M.R. Kazan (Volga Region) Federal University (KFU), Kazan, Republic of Tatarstan, Russian Federation ( Marat.Safiullin@tatar.ru )

El'shin L.A. Center for Advanced Economic Studies of Tatarstan Academy of Sciences, Kazan, Republic of Tatarstan, Russian Federation ( Leonid.Elshin@tatar.ru )

Abdukaeva A.A. Center for Advanced Economic Studies of Tatarstan Academy of Sciences, Kazan, Republic of Tatarstan, Russian Federation ( Aliya.Abdukaeva@tatar.ru )

Journal: Finance and Credit, #7, 2019

Subject This article deals with the methodological approaches to formalized assessment of the development of certain components of the digital economy, in particular considering the case of blockchain technologies.
Objectives The article aims to develop and test the diagnostic tools for the development of the demand for financial and economic relations mechanisms based on the principles of integration into the socioeconomic environment of blockchain technologies.
Methods For the study, we used the methods of descriptive and formalized estimative analysis.
Results The article proposes certain approaches to assessing the level of blockchain technologies coverage of the socioeconomic environment, and on their basis, it determines and quantifies the main parameters and characteristics that reveal key features of the emerging demand dynamics for distributed data storage technologies in the Russian Federation between 2015 and 2018.
Conclusions and Relevance The systemization of the studied data helps form a blueprint for scientific research aimed at finding and constructing formalized models of the impact of blockchain technologies on the parameters of economic development of the national economy. The approach should be used in research to assess the current and prospective parameters of the effectiveness of individual components of the digital economy.


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