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Mechanisms for the identification of business cycles of regional economic systems based on cross-correlation analysis

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

Journal: Regional Economics: Theory and Practice, #8, 2017

Subject The article deals with the issues of regional business activity and search for mechanisms that promote objective perception and evaluation of this kind of activity.
Objectives The article aims to test the business model mechanisms of regional economic system and develop predictive assessments of the industrial development of the region and the national economy as a whole.
Methods The article uses the methods of cross-correlation analysis, statistical analysis, and some other special methods.
Results The article introduces methodological approaches to diagnosing the business activity of regional economic systems (the Republic of Tatarstan as a case study) and the development of projections of key macroeconomic parameters of the Republic of Tatarstan and the Russian Federation up to 2017.
Conclusions and Relevance For the time being, the factors that characterize the adjustments in the stock and financial markets have the greatest impact on the region's business activity. The results of the study reveal a positive trend in business development in the Republic of Tatarstan in 2016, which suggests that the economic growth should be revived in 2017. The results obtained can be useful for the public administration when developing short-term projections of the socio-economic development of the territories.


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.


Methodological approaches to forecasting the industrial development based on the simulation of economic agents' expectations

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

Journal: Economic Analysis: Theory and Practice, #11, 2017

Importance Researching the mechanisms and methods of scenario-specific forecasting of socio-economic systems is an important scientific and methodological issue that is of particular relevance in the environment of dynamically developing and evolving external and internal factors. The article deals with their definition and identification, assesses specific impacts on future changes in the industrial development of the national economy.
Objectives The aim is to test the mechanisms for scenario modeling of industrial sectors of the Russian economy based on the assessment of expectations of economic agents generating transformation processes in the national economic system.
Methods I apply tools of cross-correlation analysis of major systemically important factors impacting the expectations of economic agents, and tools for designing probit and logit models and multiple choice models. The study also employs taxonomic analysis, indicative methods, etc.
Results I formulated methodological approaches to simulate the growth of industrial sectors of economy on the basis of assessment of expectations. Their testing enabled elaboration of estimates of Russian industrial development for the period up to 2020. The findings may be useful for public administration authorities to make short- and medium-term forecasts for the industrial development.
Conclusions and Relevance The findings revealed trends in the industrial growth of the national economy over the medium term, depending on designed scenarios for institutional environment development.


Mechanisms and methods for statistical analysis and tracing of shifts in phases of cyclical development of the economy under increased uncertainty of the institutional and market environment

Safiullin M.R. Kazan Federal University, Kazan, Republic of Tatarstan, Russian Federation ( c.p@tatar.ru )

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

Prygunova M.I. Center of Advanced Economic Research in the Academy of Sciences of the Republic of Tatarstan, Kazan, Republic of Tatarstan, Russian Federation ( Mariya.Prigunova@tatar.ru )

Journal: National Interests: Priorities and Security, #10, 2016

Importance Contemporary socio-economic systems develop in cycles. Those cyclical changes concern various aspects and levels of the economic system, its structure, thus outlining certain patterns. Considering economic globalization, regionalization, formation of complicated and mobile dynamic structures generating crisis phenomena, it is very reasonable to focus on the issue of contemporary regulation of cyclical development of economy, which becomes very difficult to resolve with classical methods of the cyclical theory.
Objectives The research scientifically confirms, verifies and tests the model of cyclical fluctuations that is based on such factors that would be very vulnerable to changes in the external and internal environment of the economic system.
Methods The research involves a technique that relies upon a factor-based approach and methods of statistical analysis and forecast and taxonomic method in particular.
Results We devised an algorithm to assess and evaluate cyclical fluctuations, which would allow identifying the upward and downward phases of economic cycles no matter whether they enter the positive or negative zone of priority development indices. This algorithm helps to make short-term forecasts, one to two years ahead of the current path of economic development of the national economy.
Conclusions and Relevance As the analysis shows, short-term cycles of the Russian economy somewhat different from conventional short-term Kitchin cycles, which reoccur every two to four years. The time of economic cycles in the Russian Federation has a very broad range, depending on adjusting activities of governmental authorities, and increased volatility of market conditions.


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