«Дайджест-Финансы»
 

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

Журнал «Дайджест-Финансы»
т. 23, вып. 3, сентябрь 2018

Получена: 20.04.2018

Получена в доработанном виде: 04.05.2018

Одобрена: 18.05.2018

Доступна онлайн: 28.09.2018

Рубрика: RISK, ANALYSIS AND EVALUATION

Коды JEL: F47, F63, G17

Страницы: 261-273

https://doi.org/10.24891/df.23.3.261

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

https://orcid.org/0000-0003-3708-8184
SPIN-код: отсутствует

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

https://orcid.org/0000-0002-0763-6453
SPIN-код: отсутствует

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

https://orcid.org/0000-0003-1262-5588
SPIN-код: отсутствует

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.

Ключевые слова: cryptocurrency market, forecast, modeling, time series, stochastic analysis, bitcoin

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ISSN 2311-9438 (Online)
ISSN 2073-8005 (Print)

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т. 23, вып. 3, сентябрь 2018

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