A comparative analysis of the key methodological approaches to the process of financial stability prediction | Статья в журнале «Вопросы экономики и управления»

Библиографическое описание:

Макулбекова Р. М., Сыздыкова Э. Ж., Сыздыкова Д. И. A comparative analysis of the key methodological approaches to the process of financial stability prediction // Вопросы экономики и управления. — 2017. — №1.1. — С. 38-41. — URL https://moluch.ru/th/5/archive/51/1743/ (дата обращения: 26.05.2018).

The ability of the economic entity to finance its activities on an extended basis, to resist changes in an unstable environment and to ensure their solvency in difficult circumstances leads to the conclusion of its financial stability. We can say that the diagnosis of the financial condition stability allows us to estimate the degree of management efficiency of financial resources of the enterprise during the analyzed period, the success its property usage, a rational combination of equity and debt and using of available capital, the settlement of relations with debtors, creditors, budget, credit institutions.

A huge number of factors have an impact on the financial stability of companies, keeping these factors is the basis of the financial stability of the forecasting process, is an important element in the process to ensure its effective development. Financial forecasting allows you to answer the question of what awaits it in the future - a healthy financial position or insolvency. The role of financial forecasting in system of factors of ensuring the financial sustainability of the enterprise is to help to make adequate administrative decisions, defining the key areas of financial development of the subject. In the Kazakhstan practice there are two main approaches for forecasting financial stability - and coefficient of probability of bankruptcy.

A review of the economic literature, there is no more or less clearly regulated set of financial ratios to assess the financial stability of the enterprise. Thus, N.A. Rusak for the analysis of financial stability recommends to use 9 factors, M.N. Kreynin – 7, E.A. Markaryan – 15, V. Kovalev - 8 [1].

Forecasting bankruptcy studies of foreign scientists allow us to conclude that from large amounts of coefficients only a few could fairly accurately predict bankruptcy of the enterprise. However, often their dynamics is quite controversial. This led to the development of models that allow to predict the bankruptcy of enterprises, based on the value of an integral index, calculated according to a combination of several indicators.

Early forecasts of bankruptcy investigations relate to the 60-th years of last century. W. Beaver tested model of 29 coefficients for a period of five years and predicted the bankruptcy of the example of firms that became bankrupt, and compared them with a control group of firms that didn’t go bankrupt. As a result, the author has developed a multi-factor model, aimed at assessing the financial sustainability of the economic entity for the purpose of diagnosis of bankruptcy, which contains the following components parameters [2]: 1. Beaver’s rates, calculated as the ratio of net income and amortization of to the value of borrowed funds of the enterprise; 2. Profitability of assets; 3. The ratio of debt to total assets; 4. Absolute liquidity ratio; 5. The current liquidity ratio.

The obtained values of these parameters correlate with their calculated values of Beaver for the following categories of business entities: Successfully growing businesses; Enterprises, gone bankrupt during the year; Enterprises gone bankrupt within five years.

The most popular method of determining the level of solvency of business entities was developed in 1968 by the American economist E. Altman. It is based on the definition of the functions of the set of parameters that reflect the financial capacity of the economic entity and the success of its operation for a certain period. The proposed index, referred to as the Z-score is calculated using the formula:

where: - Working Capital / Total Assets. Measures liquid assets in relation to the size of the company, - Retained Earnings / Total Assets. Measures profitability that reflects the company's age and earning power, - Earnings Before Interest and Taxes / Total Assets. Measures operating efficiency apart from tax and leveraging factors, - Market Value of Equity / Book Value of Total Liabilities, - Sales / Total Assets.

Fifteen years later, a scientist proposed a variant of determining the value of Z-score for enterprises whose shares are not publicly traded, representing the following ratio:

where: - the carrying value of the shares / debts.

In 1977. O. Taffler was presented multifactor model, which based on the analysis of multivariate discriminant is calculated partial correlation, which allows to select a group of enterprises in accordance with the level of their financial stability. The author proposed the following formula:

where: - profit before tax / current responsibility, - current assets / obligations, - current obligations / assets, - lack of credit range, - weight coefficient.

In 1972 British economist R. Fox offered another Z-score model, calculating the probability of bankruptcy:

where: - working capital / assets, - profits from sales / assets, - undistributed profits / assets, – equity / loan capital.

At the same time, in our opinion, the most common methods of predicting financial stability in the domestic practice have the following complex of shortcomings and deficiencies [3]:

1. There is no single evaluation index, which gives a comprehensive picture of the financial performance of the enterprise.

2. Financial ratios are used as one of the main analysis tools do not include sector-specific analysis of the object, causing their value does not always reflect the real situation in the economic entity.

3. Existing techniques generally used only accounting data and do not include management accounting data, which greatly impoverishes the range of estimates obtained.

4. Assessment of the probability of bankruptcy to the greatest extent takes into account the development of the company in the recession phase, but its application is not quite adequate in the other phases of the life cycle of an economic entity.

As the direction of assessment of financial stability is expedient assignment of an economic entity to a class of risk, depending on the quantity and quality of its financial and economic activity. This assessment may be based on a system of absolute and relative indicators or a combination of both. In this regard, let us note that the specific risks associated with the decisions is the need to make a choice from the available options at the effects of uncertainty, i.e. in conditions of incomplete knowledge. It should be noted that the knowledge cannot be complete, in principle, [4]. Therefore, one of the tools of financial stability prediction may be an element such as stress testing. It is possible as a qualitative review of the stress tests results within a set of management tools and integration of the stress component in the calculation of capital required to cover the risks. Within the concept of exceptional but plausible events are known several groups of scenarios, with some groups in isolated univariate and multivariate scenario. A special place in the multifactor occupy expert, i.e. hypothetical, created on the basis of expert assessments, taking into account both historical crises, and the current state of the market and allow to focus on the most significant risk factors. At the same time, according to experts, the financial stability predicting the greatest risk are the value of working capital, sources of its formation, as well as indicators of the state of the enterprise's assets. In particular, according to L. Filobokova for small businesses seems possible following graduation classes of financial stability (Table 1). In our view, this method should be transformed, depending on the scope of the object of financial stability prediction.

Table 1 - Grading types of financial stability of economic agents [5]

Type of financial stability

Quantitative values of the main stress factors

Conclusions about the possible forecast of the economic system


Depreciation of fixed assets - up to 10%. The probability of default on receivables - up to 7%. The ratio of turnover rates of receivables and payables - more than 1.75.

The ideal is theoretically possible degree of stability for domestic enterprises.


Depreciation of fixed assets - 11-25%. The probability of default on receivables - 8-15%. The ratio of turnover rates of receivables and payables – 1.51-1.74.

Possibility of continuous sustained activity during the year.


Depreciation of fixed assets - 26-35%. The probability of default on receivables - 16- 20%. The ratio of turnover rates of receivables and payables – 1.00-1.50.

Possibility of continuous sustained activity during the year. Recommended the formation of Redevelopment Fund and the provision for doubtful debts.

Unstable financial condition

Depreciation of fixed assets - 36-50%. The probability of default on receivables - 21-31%. The ratio of turnover rates of receivables and payables – 0,75-0,99.

Possibility of continuous sustained activity in the case of restrictions on the payment of dividends. Recommended the formation of Redevelopment Fund, the stabilization fund and provision for doubtful debts.

Pre-crisis financial condition

Depreciation of fixed assets - 51-74%. The probability of default on receivables - 31-41%. The ratio of turnover rates of receivables and payables – 0,25-0,74.

The impossibility of continuing operations without additional attraction of financial resources and the development of crisis management measures.

The critical financial situation

Depreciation of fixed assets - more than 75%. The probability of default on receivables - more than 41%. The ratio of turnover rates of receivables and payables – below 0.25.

The impossibility of continuing operations without additional attraction of financial resources and the development of crisis management measures.

In particular, according to S.E. Lobykina existing values of the main factors, reflecting the state's financial and economic activities of economic entities is necessary to correlate with a certain normative average indicator reflecting a normal financial situation for a specific business area [6]. In addition, the same can be said about the accounting phase of the enterprise life cycle, which makes some adjustments in the process of establishing the normal range of indicators considered in this example. The implementation of these conditions using of the described method allows a higher degree of reliability to assess the prospects for financial stability of the economic actors.

To summarize the comparative analysis, it can be noted that the discussed approaches to forecasting the financial sustainability of business entities based on the analysis of absolute and relative indicators of its activity, and such approaches do not allow enough to correctly assess these indicators for the following reasons [7]:

1. Incomplete information provided in the financial statements, leading to a distorted assessment of the state's assets and liabilities.

2. The approach to the assessment of financial stability, defined as the ratio of own capital and borrowed credit funds that provide assets does not provide a real picture of sustainable development of the economic entity.

3. Forecasting of financial stability on the basis of extrapolation of current trends into the future, it requires the use of large data sample size, missing in many enterprises.

The impact of environmental factors at the same time studied rarely. In addition, when not monitored system dynamics calculations static stability and change its behavior under the influence of various exogenous and endogenous factors at certain times [8]. Thus, there is often incomplete correct input data and low information available at the moment of methodological approaches necessitate the development of more appropriate approaches to the assessment and forecasting of financial stability, based on the use of a wider information base and integrated approach to accounting factors affecting the financial stability of enterprises.


  1. Mukhametshin A.T., Antipov A.V. The difficulties and limitations of the practical application of coefficient of the method of financial analysis companies in assessing their value // URL; http:www.appraiser.ru/UserFiles/File.
  2. Lyubushin N.P. Analysis of financial and economic activity of the enterprise. - M., 2000. - P. 224.
  3. Sahakyan TG Comparative analysis of the main approaches to forecasting of financial stability // Issues of financial and credit relations, accounting, audit and economic analysis: a collection of articles and graduate candidates for a degree of Candidate of Sciences. – Rostov n/D., 2012. – P. 120.
  4. Yefremenko D.V. The concept of the knowledge society as a theory of social transformation: achievements and problems // Problems of Philosophy. - 2010. - № 1. - P. 54.
  5. Filobokova L.Y. Stress testing tools predict financial stability of small enterprises // Management of economic systems. - 2010. - № 3. - P. 38.
  6. Lobykina S.E. Perfection of a technique of the financial analysis of commercial organizations in a variety of activities. – Orenburg, 2007. – P. 24.
  7. Ogorodnikov P.O., Perunov V.B. Biotechnical approach to the analysis and forecasting of financial stability // The economy of the region. – 2011. - № 2. – P. 236.
  8. Sahakyan T.G. Predictive modeling of financial stability on the basis of rating methods // Accounting and Statistics. – 2013. - № 3. – P. 98.
Основные термины (генерируются автоматически): financial stability, economic entity, financial stability prediction, forecasting financial stability, total assets, financial condition stability, financial sustainability, calculations static stability, healthy financial position, financial forecasting, financial ratios, business entities, Measures liquid assets, Forecasting bankruptcy studies, normal financial situation, financial development, current liquidity ratio, financial resources, factors, Absolute liquidity ratio.


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