This study aims to analyze the predictions of the default probability in the non-financial sector of the Indonesia Stock Exchange and the mutual influence between financial ratios. The KMV–Merton method was used for the calculations. The study was conducted on the example of data from 18 companies listed on the Indonesia Stock Exchange. The scientific materials and documentation were analyzed with the help of the EViews. The authors made the following

conclusions: Return on Equity (ROE) has no effect on the probability of default; Current Ratio (CR) has no effect on the probability of default; Debt to Equity Ratio (DER) has a positive effect on the probability of default; Total Assets Turnover (TAT) has a negative effect on the probability of default. 

The article aims to find the best time series predictive model, considering the minimization of errors and high accuracy of the prediction. The authors performed the comparative analysis of the most popular “traditional” econometric model ARIMA and the deep learning model LSTM (Long short-term memory) based on a recurrent neural network. The study provides a mathematical description of these predictive models. The authors developed algorithms for predicting time series based on the “Rolling forecasting origin” approach. These are Python-based algorithms using the Keras, Theano and Statsmodels libraries. Stock quotes of Russian companies Alrosa, Gazprom, KamAZ, NLMK, Kiwi, Rosneft, VTB and Yandex for the period from June 2, 2014 to November 11, 2019, broken down by week, served as input data. The research results confirm the superiority of the LSTM model, where the RMSE error is 65% less than with the ARIMA model. Therefore, an LSTM model-based algorithm is more preferable for the better quality of time series prediction.

Over the years, project finance has proved to be one of the innovative techniques in bridging the resource constraints faced by most governments in financing large developmental investments. In this regard, the current state and dynamics of indicators of the world project finance market, as well as the role and place of the Arab economy in this global phenomenon, are interesting. The aim of the article is to review the features of project financing in the world and in Arab countries, mainly in the GCC region. The article employed the methods of statistical analysis, regression modelling. The author analysed historical data on the volume, dynamics, and structure of project financing in the GCC countries. The study revealed the use of project finance in 18 Arab countries, primarily concentrated in three areas: energy and water supply, petrochemicals, and the oil and gas industry. The author concluded that there is a growing tendency to use Islamic project finance structure.

The relevance of the article is conditioned by the need to study institutionalization of financial literacy of the adult population, as well as to increase its level due to financial services and products emerging on the market (banking, investment, insurance, pension) and tools for their use. The novelty of this topic is associated with a systematic analysis of the institutionalization processes of financial literacy of the adult population, which makes a significant contribution to implementing national goals and strategic objectives of the development of the Russian Federation, and is also an important consumer of financial services. The aim of the article is a comprehensive scientific study of the institutionalization processes of financial literacy of the adult population. Techniques such as content analysis of references, verification, analysis, statistical and sociological methods (survey), crosstabulation, etc. were employed to analyze the data. Theoretical and methodological principles of institutionalization of financial literacy of the adult population were analyzed. The authors developed a conceptual model of its institutionalization. The study analyzed the state and dynamics of institutionalization of financial literacy of the adult population. The authors formulated the conclusions and recommendations on the sustainable development of institutional entities that contribute to improving the financial literacy of the adult population. The study calls for including the list of target population groups of citizens of retirement and pre-retirement age, as well as persons with disabilities, in the Strategy for Improving Financial Literacy in the Russian Federation in 2017–2023; making arrangements for financial education of the population within the national projects “Digital Economy”, “Education”, “Culture”, “Demography”; supporting the creation of electronic platforms and online panels in educational organizations for systematic financial education of various target groups of the population of the Russian Federation, etc.

The aim of the article is to analyze the features of regulatory arbitrage between credit and microfinance organizations in the retail lending market in Russia and to develop proposals to improve existing regulations on the activities of professional lenders. The work employed the methods of analysis, synthesis, generalization, as well as comparative legal research. The author found that regulatory arbitration might aim to get benefit from imperfect legislation. Signs of regulatory arbitration may indicate the inefficiency and redundancy of current legislation concerning the regulation of consumer lending. The author developed the following recommendations: to reduce redundant regulation regarding the limits of the full loan value for point-of-sale loans and installment loans; to switch to licensing system of financial organizations, considering the scale of their activities and the produced risks.

The author considers fiscal incentives of regional authorities in the system of federal intergovernmental relations. The aim of the study is to determine how the debt burden of Russian regions affects regional fiscal policy in the context of federal co-financing of expenditure obligations. The work employed the methods of grouping, one-dimensional cluster analysis, correlation analysis, and regression by generalized method of moments (system-GMM). The study found that the increase in the regional debt burden relates to a decrease in the level of local fiscal decentralization. Intensive debt financing of regional expenditures in 2013–2015 also reduces the willingness to regionally co-finance federal priorities. The author concludes that high debt burden reduces the fiscal incentives of regional authorities to co-finance federal initiatives and creates the risk of underfunding of national projects.

The aim of the article is to study the effect of M&A transactions in Russia for shareholders and investors of an acquiring company. The objectives of the study were to develop methods for efficiency evaluation, to conduct a general analysis of the M&A market in Russia, to develop recommendations based on the results. The framework of the study was the market-based approach to the analysis of transaction efficiency. The authors investigated the key indicators: the value of the company EV (Enterprise Value) and the market value of the company MV (Market Value). They analyzed three time points for each transaction and the change of the indicators in-between: six months before the transaction, at the time of the transaction and six months after the transaction. The data obtained allowed for calculating the growth rates of stock prices, the values of the companies and the average values for the market. Based on the study results, the authors concluded that the M&A market has a weak effect on the Russian economy as a whole, but at the same time there is a decreasing effect for shareholders. The majority of M&A transactions aim to expand corporate finance, to increase the company’s capitalization, and to maximize business value. The results are of use to predict the further dynamics of the company’s value, a key indicator for portfolio and institutional investors, as well as to analyze the efficiency of acquisitions followed by evaluation of investment attractiveness of the company.

Assumptions about the impending new global crisis, which are increasingly found in expert discussions, have intensified the search for reliable crisis predictors, despite the existing theoretical consensus on the fundamental impossibility of forecasting crises. The purpose of the article is to describe the most popular “new” crisis predictors and evaluate their predictive properties. The primary research method was monitoring the confirmation of signals supplied by predictors, indicators of macroeconomic dynamics based on retrospective data. As a result of the study, we clarified the classification of types of financial crises to determine the predictors that best predict certain types of financial crises, which in current conditions are very likely to be the starting stage of a new kind of financial and economic crisis. We analysed financial condition indices (FCI); VIX (“fear index”); yield spreads between US treasury bonds of different maturities; investor sentiment indices and risk premium indicators; CAPE (Schiller coefficient). We analysed the signals from the “new” crisis predictors about the possible onset of the crisis. The authors concluded that various predictors show good results concerning crises of a particular type (the starting point of which were different segments of the financial sector). The analysis of the predictor time of various predictors made it possible to build them in a certain sequence depending on the time interval between the predictor signal and the onset of the crisis. Based on combining the linking of predictors with the types of crises that they predict better, with a sequence of predictors arranged according to the time of the predictions, we proposed a flow chart for monitoring external crisis predictors.

The aim of the study is to reveal if there is a coordination of fiscal and monetary policies in Armenia, as well as to assess its impact on economic growth in the country. Methods used: statistical analysis, logistic regressions, mathematical modeling. The authors analyzed the economic growth rates and annual GDP growth per capita in Armenia from 1990 to 2018. They described the model of coordination of fiscal and monetary regulation. The relationship and interdependence between the monetary and fiscal regulation mechanisms are represented by mathematical equations. Provided are the calculations for the optimal values of fiscal and monetary indicators, as well as economic indicators for Nash equilibrium. The study results showed that fiscal and monetary regulation in Armenia is ineffective; there is no coordination of regulatory mechanisms, which is detrimental to the economic growth rate. The authors conclude that it is necessary to revise approaches to monetary and fiscal policies for a greater emphasis on coordination and harmonization of macroeconomic regulation instruments to ensure sustainable economic growth in the long term.