This article is devoted to the analysis of the existence of target capital structure of insurance companies and empirical testing of wide known capital structure theories for Russian insurance companies. Trade-off and “pecking order” theories were considered and the model that reflects the impact on the capital structure indicators various characteristics of firms was built. Traditional for insurance markets coefficients — net premium/capital ratio and liabilities/active ratio — were considered as capital structure indicators. It was shown that tradeoff theory is more adequate for Russian insurance market. The existence of target capital structure was discovered. Such indicators as firm size, the share of premiums transferred to reinsurance, return on assets, returned on capital have significant impact on the capital structure. The opportunity to grow, which was estimated as growth in premiums, and the breadth of the range didn’t has significant impact.
This publication reflects the results of the authors’ research aimed at finding ways to reduce the complexity of appraising the investment attractiveness of potential recipients of investments. The purpose of the research is to create a methodology that will effectively manage not only the process of determining the recipients of investments but also the development of organizations to increase their investment attractiveness. The authors provide an overview of the most significant publications that consider existing methods for appraising investment attractiveness, based on both financial statements and the market value of a business. In the main part of the article, the authors conclude that data envelopment analysis (DEA) may be used to aggregate several different criteria of the investment attractiveness appraising in one number. The section that presents the empirical results of the study contains a description of a number of indicators of Russian oil refining companies and their aggregation based both on the method of expert assessments and a formal approach using the DEA. The examples only apply criteria calculated based on organizations’ financial statements. It is emphasized that in real practice the first method is a very expensive and time-consuming procedure in comparison with the second, which provides a formalized agreement of the criteria used in the former method, and takes into account the situation in the entire market segment under study. It is shown that the calculations made based on these two methods give approximately the same results. This indicates that the methodology proposed by the authors can be considered as an effective alternative to existing expert approaches to appraising investment attractiveness. In the final part of the article, recommendations are formulated for improving the proposed methodological approach by including a number of market indicators that characterize the activities of potential recipients of investments.
In the introduction, the authors argue the relevance of the researched problem of improving the algorithm for estimating transaction cost of bank’s purchase and sale in the Russian financial services market. It is emphasized that the need to manage the value of a commercial enterprise arises not only when planning the purchase and sale transaction of the entire business or part of it. The valuation is taken into account, first of all, when corporatizing an organization, attracting new shareholders, insuring its property, obtaining a loan secured by property, calculating the fair value of taxes.The first part of the paper substantiates the business valuation algorithm intended for a potential investor and adapted to the conditions of the Russian financial market. This takes into account the specific features of each bank in question. Based on the data from open financial statements (for 2017–2022), the parameters required in the procedure for obtaining estimates are calculated.The second part of the paper presents the result of selecting indicators of the external and internal economic environment of banks that have a significant statistical relationship with the resulting valuation. The selected factors are under the control of managers and can be used to guide the proposed cost estimate. Data were obtained on the direction and strength of influence of selected factors on the value of business. The selection algorithm is based on mathematical modeling using bank data for the period under consideration.The valuation is based on a comparative approach, where the values of the multiples are calculated using a linear regression model. To organize cost management, a panel regression model is built, which allows to select significant financial indicators and determine the nature of their impact on the bank's value.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.