Despite the fact that the scientific literature pays considerable attention to ensuring the investment attractiveness of national corporate bond markets based on macro-environmental factors, as well as individual companies – based on micro-environmental factors, the issue of optimizing the characteristics of corporate bonds in the prospectus remains insufficiently disclosed. However, coupon rate, price and maturity are the basic indicators that investors take into account when deciding to purchase corporate bonds, so they need more detailed research. approach to ensuring the issuance of investment-attractive corporate bonds, based on the use of indicators of companies with the highest level of demand on the stock market to build a matrix of coupon rate, price and maturity of corporate bond, the use of which allows to establish the optimal ratio between these characteristics. Enterprises issue corporate bonds to attract additional financial resources in their activities, so they are interested in ensuring the investment attractiveness of these securities. The investment attractiveness of corporate bonds depends on their own characteristics, as well as on micro- and macro-environmental factors. The most affordable way to ensure the investment attractiveness of corporate bonds is to establish the optimal characteristics of bonds in the prospectus. The companies whose corporate bonds are in the highest demand on the stock market have the optimal ratio between coupon rate, price and maturity. Determining the trend of ensuring a balance between these indicators of leading companies allows us to establish a model of decision-making by investors in a particular market of corporate bonds.
The article considers economic and mathematical models and studies the socio-economic processes that develop over time, as well as mathematical models that describe them. These are dynamic models. All variables in dynamic models generally depend on the time that acts as an independent variable. In economic research, there are often problems in which variables acquire discrete numerical values. For example, at the end of the month, quarter, year, etc., production results are optimized; accrual of interest on the bank deposit at the end of the month, six months, at the end of the year. In addition, because computers operate only with numbers, so when using computer technology, all continuous processes are reduced to discrete. In this case, from differential equations that describe certain economic processes, we move to difference equations. There are dynamic models with continuous and discrete time, ie continuous and discrete models. Therefore, depending on the type of dynamics of the system under study, dynamic models can be divided into discrete and continuous. In discrete dynamic models, difference equations or systems of difference equations are used; differential equations or systems of differential equations are used in continuous dynamic models. In addition, in some cases there may be systems with mixed dynamics, then differential-equation equations are used to describe them. Difference equations and systems of equations are used successfully in modeling dynamic processes (in economics, banking, etc.). It is when the change of process occurs abruptly, or discretely, that it is convenient and expedient to apply difference equations and systems of equations. The theory of dynamical systems with discrete time, which arose as a result of building mathematical models of real economic and physical processes at the junction of the theory of difference equations and discrete random processes, is currently experiencing a period of rapid development and widespread use in various spheres of human life. In this paper, we investigate the following equations, as well as show their application to solve economic problems. In particular, discrete models described by first-order difference equations are considered. Considerable attention is paid to the analysis of specific models that are meaningful and widely used in economic theory, banking, etc.
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.