Abstract

The article is based on a financial condition indicators system, which assesses the financial risk of the enterprise, and their grouping according to the nature of the impact on the enterprise financial position. The following financial risks groups have been identified: the inappropriate capital structure, inefficient financial activity, liquidity decline, ineffective operating activities, the imbalances in cash flows and ineffective investment activities risks. Each group of indicators is selected by the "center of gravity"one representative method to construct a model for assessing the financial risk in the enterprise level. It is determined that representative indicators in identifying the financial risk in an enterprise level are: coefficient of autonomy, coefficient of turnover of capital, absolute liquidity ratio, return on sales, net cash flow ratio, total return on investment.At the next stage of constructing a model for enterprise financial risks minimizing using expert method, representative indicators are measured according to their informativity for assessing financial risk at the enterprise. Taking into account the indicators significance, a machine-building enterprises assessment financial risk model was constructed on the basis of the enterprise financial risk level indicators-representatives additive convolution with their significance weight coefficients correction.The functional dependencies between the indicators are determined given the direct and inverse nature of the link between the indicators that characterize the machine-building enterprises financial risk, using correlation-regression analysis. An optimization model for machine-building enterprises financial risks minimizing was built on the principle of limiting financial risks. Optimizing the model means getting the maximum integral index value of the financial risk neutralization level. To this end, the Kuhn-Tucker theorem is used. As a result of model optimization it was revealed that from the point of view the financial risks at machine-building enterprises level minimizing, the optimum values of financial indicators are: for the coefficient of autonomy — 0.41; for the capital turnover coefficient — 31,0; for the coefficient of absolute liquidity — 0,45; for a profitability ratio of sales — 0,29; for the coefficient of sufficiency of net cash flow — 0,60; for the coefficient of total return on investment — 0,28. The established norms of financial indicators provide financial risk minimization at machine-building enterprises.

Highlights

  • The current state of the machine-building industry in Ukraine is characterized by a loss-making activity, a decrease in export potential, the volatility of the volumes of manufacturing and sales, and the volume of investment

  • The statistical data given testifies to the unstable financial state of the enterprises of machine-building industry and high level of financial risk, which determined the relevance of the study

  • As a result of the study, a model for minimizing the level of financial risks of machine-building enterprises was carried out, which determined the optimum values of financial indicators, the use of which for the establishment of internal norms will improve the financial state and minimize the level of financial risk of enterprises

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Summary

Introduction

The current state of the machine-building industry in Ukraine is characterized by a loss-making activity, a decrease in export potential, the volatility of the volumes of manufacturing and sales, and the volume of investment. According to the results of 3 quarters of 2017, the enterprises of machine-building industry received a surplus of UAH 5039.7 million. Against this background, exports are decreasing every year starting from 2014: the average annual rate of decrease is 18.4% [1]. The purpose of the study is to improve the methodological tools for assessing financial risks of enterprises in the machine-building industry and determinig the optimal values of financial indicators that will ensure the financial sustainability of the enterprise and maximize the efficiency of the activity, thereby minimizing the level of financial risks. Formation of a system of indicators of financial risk assessment of an enterprise by groups of financial risks

Determination of representative indicators by groups of financial risks
Conclusions
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