Eugenia Bondarenko

The purpose of the article is to determine the degree of financial interaction between the stock and insurance market, or, in other words, to determine the potential capacity of the stock market’s risk insurance sector for the Ukrainian insurance market. The authors examine the insurance not of all possible risks on the stock market, but only the most potentially important for the development of the stock market at this stage of economic development: insurance of professional risks of depositories and insurance of individual investments of individuals – participants of the stock market. In order to calculate the capacity of the stock market’s risk insurance sector in the context of the two above mentioned types, the authors apply the models that are widely used in the economic-mathematical analysis. For mathematical calculations we used 31 absolute indicators of the characteristics of the state of the stock and insurance markets, as well as some macroeconomic indicators. When forming an array of input data for mathematical calculations we used annual values of absolute indicators for the period 2005–2015 were used. For the adequacy of the received calculations the normalization of the selected indicators was carried out. All indicators were divided into two groups: stimulators and de-stimulators. The normalization of stimulator indicators was carried out by the method of natural normalization, and of de-stimulator indicators – according to the Savage formula. The capacity of the segment of the new type of insurance was determined by the authors as the maximum possible amount of insurance premiums that insurers can get in the process of implementing a new insurance product based on the current state of development of the insurance market. The capacity of the sector of the new type of insurance was presented as a function of the main component (an indicator that directly characterizes the created segment) and the corrective component (a set of indicators characterizing the segments created indirectly). The weight coefficients of the corrective component were determined by using the Fischer’s formula. As a result of the calculations, the authors obtained the data on the prospects of simultaneous introduction for the stock and insurance markets of such types of insurance as a professional liability insurance of depositories and an insurance of individual investors on the stock market.

A compensation fund is an effective mechanism for ensuring the protection of individual investors’ investments on the stock market, which confirms the experience of different countries both with the developed stock market and with the emerging markets (USA, UK, France, Czech Republic, Bulgaria, Ireland, Malta).
The formation of a steady interest of individual investors in stock market instruments is stimulated by the implementation of a mechanism for guaranteeing such investments. The stock market of Ukraine faces the problem of attracting additional financing, while individual investors have fairly large amounts of monetary resources that are not involved in the transactions with financial instruments due to the high level of distrust caused by the crisis phenomena on both the global and the national financial markets. The creation of the Ukrainian compensation fund for investment protection involves the development and implementation of a nationwide system for protecting the property interests of investors on the stock market, which requires compensatory payments to the clients of all professional market participants as a result of certain risks.
The main condition for effective functioning of the compensation fund of the stock market is determined by its size, which must meet the following conditions of optimality: to ensure the minimum level of the fund’s risks, to take into account the amounts of contributions for the current period, the amount of maintenance costs and to fulfil the requirements for the financial stability of the fund. A modified Markowitz portfolio model was used to build the model.
The building of the target function and constraints was carried out by using the Statistica software toolkit. The target function and constraints were presented as polynomials of the third degree and calculated with the help of the multiple nonlinear regression. As a result of calculations, an optimization model was developed for determining the size of the compensation fund taking into account these conditions.
The model’s testing was carried out by using the examples of the Deposit Guarantee Fund (DGF) and compensation funds of the United States, Great Britain, France, Czech Republic, Bulgaria, Ireland and Malta. As a result of calculations we determined the size of the compensation fund, which guarantees a minimum level of the fund’s risk taking into account the amount of contributions for the current period, the amount of maintenance costs and requirements to the financial stability of the fund.

The Ukrainian stock market is rated as an emerging market, which is characterized by high profitability and higher risk level as compared to developed economies. Securities transactions on the Ukrainian stock market are accompanied by stable uncertainties. Moreover, insurance is the most effective way to reduce financial risks and their negative effects. Given the current economic and political instability, financial risk insurance can ensure the economic performance of business entities and stimulate their further economic development. Financial risk insurance is the liability insurance in its nature, but its terms are often included in property insurance. This insurance sector has considerable facilities, which require activation of new insurance products that will be able to protect individual and institutional investors. Insurance and stock markets are direct competitors for limited investor resources, including strategic sources such as temporarily free institutional investor funds and household savings. In general, although there is a significant interaction between the insurance and other financial markets in Ukraine, it is hardly realized at all, unlike foreign economies, where it is used to its maximum. With the development of the insurance culture of the population and insurance in general, the relevance of insurance services in a high-risk segment like the stock market increases. The article harmonizes types of financial risks arising on the stock market with the methods of their leveling (insurance, hedging, diversification, etc.), determines the risk factors of the investor in the stock market, and specifies the professional risks of financial institutions. For the Ukrainian stock market participants, the use of two types of insurance coverage, namely, Bankers Blanket Bond and Financial Institution Professional Indemnity, is proposed.

In the conditions of insufficient budgetary financing of the health care system and low quality of medical care in the state medical establishments of Ukraine, the importance of extra-budgetary sources of financing becomes increasingly relevant. One such source is voluntary health insurance. The aim of the paper is to compare the state and structure of medical financing in developed countries and in Ukraine, to study the global experience in the functioning of the voluntary health insurance market, and to calculate the potential capacity of the voluntary health insurance sector in Ukraine. For mathematical calculations, 20 absolute indicators of the state of the voluntary health insurance sector, as well as macroeconomic indicators, were used. The annual values of absolute indicators for the period 2010–2019 were used in forming the array of input data. Based on the experience of foreign countries, the paper substantiates the development of the voluntary health insurance in Ukraine as an extra-budgetary source of health care funding. The capacity of the voluntary health insurance sector was defined by the authors as the maximum possible amount of insurance premiums that insurers can receive in the process of selling voluntary health insurance products. The calculations made it possible to conclude that the voluntary health insurance market in Ukraine has the potential for development, as evidenced by the predominance of the potential capacity of the voluntary health insurance segment over its real indicator.

The paper aims to develop scientific and methodological approach to assessing the interaction of nonperforming loans of Ukrainian banking institutions, the profitability of the banking sector and its financial stability, which will allow a more detailed assessment of the directions and degree of mutual influence of these elements. To substantiate this interaction economically and mathematically, structural equation modeling was chosen. Particularly, Statistica was chosen as a software tool to assess the adequacy of the resulting model and determine the level of statistical significance of its parameters. Six key indicators were selected as a research information base, two for each subject of research: indicators of nonperforming loans in the banking sector (the volume of nonperforming loans and the ratio of problem loans excluding capital reserves), profitability indicators of the Ukrainian banking sector (assets profit and rate of return on capital), and indicators of financial stability of the Ukrainian banking sector (regulatory capital-to-risk-weighted assets ratio and liquid assets-to-total assets ratio). For calculations, statistic data of selected indicators for 2005–2019 were used.
As a result of calculations, mathematical data were obtained that accurately described the interaction of nonperforming loans of Ukrainian banking institutions, the profitability of the banking sector and its financial stability. The adequacy of the model was verified based on the following criteria: main summary statistics (ICSF criterion, ICS criterion, discrepancy function, maximum residual cosine), noncentrality fit indices (noncentrality parameter, population noncentrality parameter, Steiger-Lind RMSEA index, McDonald noncentrality index, adjusted population Gamma index), other single sample indices (Akaike information criterion, Schwarz criterion), and a normal probability plot.