This paper investigates the role of the frequency of price overreactions in the cryptocurrency market in the case of BitCoin over the period 2013-2018. Specifically, it uses a static approach to detect overreactions and then carries out hypothesis testing by means of a variety of statistical methods (both parametric and non-parametric) including ADF tests, Granger causality tests, correlation analysis, regression analysis with dummy variables, ARIMA and ARMAX models, neural net models, and VAR models. Specifically, the hypotheses tested are whether or not the frequency of overreactions (i) is informative about Bitcoin price movements (H1) and (ii) exhibits no seasonality (H2). On the whole, the results suggest that it can provide useful information to predict price dynamics in the cryptocurrency market and for designing trading strategies (H1 cannot be rejected), whilst there is no evidence of seasonality (H2 cannot be rejected).

When creating an investment portfolio, certain financial resources are needed. To form an effective portfolio, a financial institution (enterprise) lacks equity funds, and it attracts external investors to use borrowed funds. In a joint investment project, every participant has his own financial interests and determines his strategy of participation in this project. Therefore, external investors invest money in such a project to obtain additional profit as well as the financial institution expects to get the maximum net profit.The purpose of this study is to develop a strategy for creating an investment portfolio and its further management, taking into

The article deals with the process of distribution of an innovative product using the Bass model. Numerical characteristics of the generalized Bass model are described. The function of external influence is suggested to be approximated by means of a regression equation with respect to the price function of the product under investigation, which is also a control function. The control process is based on a mathematical apparatus under the Pontryagin maximum principle. An algorithm for determining the optimal price of products in order to obtain the maximum balance profit of the corporation is given. Selected numerical results of the corporate strategy implementation for conquering the market in 2017-2020 are offered.

Given that in order to predict the economic growth of a country, the dynamics of its GDP should be considered, and the forecast itself should be made taking into account the difference between actual and estimated figures, the article discusses the problems of GDP management and its optimal distribution. The use of averages to determine economic parameters is also analyzed. The correspondence of the regression formula and the Cauchy boundary value problem is considered. The problem of managing the GDP components to obtain the necessary characteristics of GDP growth is solved using Pontryagin Maximum Principle. As an example, several options of the optimal GDP distribution (constant prices, national currency) for China in 2016-2020 are considered. Numerical results are reported and adjusted for the discount factor. Based on the calculations, it is shown that in 2017-2018, GDP increases and in 2019-2020 it decreases.

This paper considers an algorithm for constructing an integrated assessment of the environmental risk of enterprises based on risk indicators. An overview of risk assessment methods is given. To find and process the research results, the method of expert assessments and elements of the fuzzy logic method were used. The membership function is constructed for the classification of the current value of the environmental risk factor. Based on the obtained numerical results, the ranking of the studied variables is given. A generalized indicator of the level of environmental risk of an oil and gas enterprise is found.