Application of improved convolution neural network in financial forecasting

Financial status and its role in the national economy have been increasingly recognized. In order to deduce the source of monetary funds and determine their whereabouts, financial information and prediction have become a scientific method that can not be ignored in the development of national economy. This paper improves the existing CNN and applies it to financial credit from different perspectives. Firstly, the noise of the collected data set is deleted, and then the clustering result is more stable by principal component analysis. The observation vectors are segmented to obtain a set of observation vectors corresponding to each hidden state. Based on the output of PCA algorithm, we recalculate the mean and variance of all kinds of observation vectors, and use the new mean and covariance matrix as credit financial credit, and then determine the best model parameters.The empirical results based on specific data from China's stock market show that the improved convolutional neural network proposed in this paper has advantages and the prediction accuracy reaches.

ESG Principles in International Business and Sustainable Contracts

The concept of sustainable development has captured the world. It is altering society, generating new social patterns, reorganizing business and management models, testifying to the ultimate connectedness of the world and, as a result, encourages rethinking the legal superstructure, adapting supernova normative arrays to the current legal taxonomy, which is not always possible with taking into account the positivist approach to law. ESG principles have today become a kind of model for sustainable business development, due to which the goals of companies’ involvement in solving environmental, social and management problems are achieved. They have not only a vector effect, but also a regulatory, reputational; they have also an increasing impact on international business in a variety of industries. In addition, they are updating relatively new rating mechanisms that form the basis of investment, financial, credit, trade, corporate, management and other policies of companies. At the same time, ESG principles are segmented, fragmented and, as a rule, objectified externally in the form of norms of nonstate, often industry regulation. Without legally binding force, ESG principles are quite comparable with law in terms of the degree of impact on public relations and in terms of the resulting legal and economic consequences. Cross-border contracting practices are also changing, leading to the incorporation of “sustainability” clauses into contracts, as well as the emergence of the concept of a sustainable contract. The pre-contractual stage becomes more complicated, it requires human due diligence procedures, the formation and assessment of supply chains, the development of strategies for the disclosure of non-financial information, the study of legal risks taking into account the global law enforcement practice, as well as the establishment of methods and a jurisdictional forum for the resolution of disputes. International Commercial Arbitration claims to be attractive in resolving ESG disputes. These and other issues, taking into account their relevance, are studied in this paper.

RESEARCH OF FORMS AND METHODS OF INVESTMENT SUPPORT OF INNOVATION ACTIVITIES OF INDUSTRIAL ENTERPRISES

To solve the problems of stimulating the development of innovative activity of domestic enterprises, a number of regulatory acts have been developed in Ukraine today that regulate relations in the sphere of investment in innovation. National legislation defines the following forms of investment of innovative activity: state (municipal) investment, commercial investment, social investment, foreign investment, general investment. In order to receive financial support, the subjects of innovation activity whose innovation projects are listed in the State Register of Innovation Projects shall submit to the State Innovation Financial-Credit Institution (its regional branches) innovative projects and all necessary documents, the list of which is determined by it. The subject of innovative activity, the innovative project of which has been competitively selected, may receive one or more types of financial support from the innovative financial-credit institution, depending on the competitive procedure established by the competitive procedure. Financial support for the implementation of innovative projects can be provided in the form of successive tranches as a result of monitoring the progress of project implementation.The analysis of the structure of state financing of innovation activity by types of economic activity of subjects of innovation in 2018 allows to determine the priority branch of chemical and petrochemical industry. Investing of own funds of subjects of innovative activity is realized through capital investments and financial investments. Structural analysis of sources of financing of innovative activity in Ukraine allows to distinguish the overwhelming share of own funds of the enterprises in the total volumes of financing of their innovative activity. But in the conditions of insufficient level of state support of innovative activity of enterprises and instability of their financial results, as the main source of own funds for investing, the role of financial and credit providing of investments by the subjects of the financial market significantly increases.

Repressive Policy of the Soviet State in the Field of Protection and Ensuring the Stability of the Ruble in the 1920s-1950s (Financial, Economic, Criminal and International Legal Aspects)

Based on the analysis of archival and bibliographic sources, the paper examines the financial, economic, criminal and international aspects of the policy of the Soviet state in the field of protection and maintenance of the national currency and economic sovereignty of the USSR in the 1920s-early 1950s. Special attention is paid to the study of the law enforcement practice of Soviet punitive bodies. In conclusion, conclusions are formulated designed to actualize the priority of conducting a unified financial, credit and monetary policy in the Russian Federation

Assessing the Determinants of Electricity Generation Infrastructure in Nigeria

The supply and demand for electricity have outpaced available infrastructure in Nigeria despite the abundant energy resources. The paper investigates the determinants of electricity generating infrastructure in Nigeria for the period 1980 to 2016. Using an Autoregressive Distributed Lag model, electricity generation capacity was used as an indicator for electricity infrastructure development. Its expansion was based on the behaviour of inflation rate, total government expenditure, interest rate, private sector financial credit, exchange rate, real GDP per capita, real gross fixed capital formation, and the rate of urbanisation. Financial credit to private sector, total public expenditure, real per capita income, real gross fixed capital formation, urbanization, and exchange rate adversely affect the development of electricity generation capacity. Investment in generating assets is capital intensive, which should be matched with adequate private sector financing. If the power sector subsidy will remain and achieve its objective, strategies that will lead to sustaining exchange rate stability should be promoted. Based on estimate, every one million population require 1000MW of electricity to function in modern-day society implying that Nigeria needs 180,000MW of electricity capacity. The realisation of this is hinged on large scale electricity infrastructure investment enabled, partly, by the favourable macroeconomic environment.JEL Classification: E16, O1, O2

Research on Credit Risk Identification of Internet Financial Enterprises Based on Big Data

The advent of the era of big data has provided a new way of development for Internet financial credit collection. The traditional methods of credit risk identification of Internet financial enterprises cannot get the characteristics of credit risk zoning, leading to large errors in the results of credit risk identification. Therefore, this paper proposes a new method of credit risk identification based on big data for Internet financial enterprises. According to the big data perspective, the credit risk assessment steps of Internet financial enterprises are analyzed and the weight of assessment indicators is calculated using the improved analytic hierarchy process (AHP), and the linear weighted synthesis method is applied to comprehensively assess the credit of clients. Using the unique characteristics of big data credit risk region division, the big data credit risk is determined by rule-based matching method. The eXtreme Gradient Boosting (XGBoost) machine learning algorithm is used to establish a credit risk identification model of Internet financial enterprises. The kappa coefficient and ROC curve are used to evaluate the performance of the proposed method. Experimental results show that the proposed method can accurately assess the credit risk of Internet financial enterprises.