![Scientific journal NRU ITMO
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Forecasted debt coverage as a tool for investment monitoring of companies
![Scientific journal NRU ITMO
Series](/images/mag-ihbt.png)
Annotation
The article is devoted to the development of methodical approaches to investment monitoring using tools for assessing the debt security of companies. The purpose of the study was to develop an author's model of the forecasted debt security and justification of its analytical significance in investment monitoring of companies. The proposed model appeals to the principles of evaluation of corporate obligations, which are used in the theoretical models of financial insolvency of the firm. This approach to the building of the model has certain advantages, without conflict with the specifics of the company, industry and the market. At the same time, the model is oriented to Russian companies, which is reflected in the characteristics of the assessment of free cash flow. In particular, the indicator of adjusted free flow on invested capital is introduced, which takes into account a consistently high share of other revenues in the total amount of income of Russian companies. The author's model is tested on the example of a transport company operating in one of the major ports of the Baltic Sea. It is shown that the result of the forecasted debt security largely depends on the way of calculation of free cash flow. Approbation of the model allowed to reveal its features in more detail, revealing the advantages and limitations of the evaluation. The main recommendations for interpreting the possible values of the forecasted debt securitycoefficient are systematized and presented in tabular form. According to the authors, the model of predicted debt security will be usefulfor investors and managers in investment monitoring of companies, making a contribution to the development of such areas of financial science and practice as capital structure management, financial restructuring, financial risk assessment, corporate financial diagnostics and financial stability monitoring.
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