Market Dynamics of Ensuring Financial Security and Sustainable Development of Enterprise

Abstract

The paper substantiates the need to study the level of financial security of an enterprise. To study the dynamics of financial security of an enterprise we consider a system-dynamic model and simulation of distributed financial flows of a representative industrial enterprise under the impact of random factors, which reflect the threats affecting its financial security. Information on the financial statements of firms is often confidential, which leads to the need to develop a simulation model of a firm’s activities and to conduct experimental research based on the enterprise’s size and reserve fund ensuring its financial security. During simulation experiments, three scenarios for metallurgical enterprise (pessimistic scenario, optimistic scenario and most probable scenario) were investigated, and it was established that for at least half of the cases, an enterprise needs to form a reserve fund to maintain autonomous operations and ensure the necessary level of financial security.

JEL Classifications: C1, C9, D33

Keywords

Financial security financial stability current assets cash flow simulation model of enterprise

Introduction

Ensuring the sustainable growth of activity of an enterprise and stability of its performance and attaining goals that meet the interests of its owners and society as a whole are achieved by forming the enterprise’s strategy, which in the global economy is determined by the availability of a reliable system of its financial and legal security (Rudensky, 2002; Starinets, 2018; Slizkaya, 2007).

Financial security is the object of research in the works of Ukrainian economists (Baranovsky, 2004; Bilyiy 2018; Epiphanov, 2009; Solomin, 2018). The need to ensure sustainable long-run development, especially under crisis, requires further study of approaches to assessing and analysing the level of financial security of enterprises.

In the field of financial security of an enterprise, principal challenges are associated with a systematic analysis of the dynamics of its financial condition, causing both administrative and criminal liability rather than, with the inefficiency of its financial activity, the impossibility of payments, the appearance of arrears, reducing the level of financial security of the enterprise (Bagrov, 2008; Thompson, 2006). This kind of problem requires research using a system approach and dynamic analysis of the system.

A sufficient level of enterprises' financial security will ensure that the state can perform its functions, provide economic development and make improvements to social standards. Thus, the financial security of enterprises is one of major components of the national security of any country, because the enterprises are taxpayers. Assessment of financial security will allow a company to minimize the threats of financial instability and increase the safety of its existence.

Major victims of COVID-19 outbreak are the small and medium-sized enterprises (SME), because SMEs, in comparison to large enterprises, usually do not possess sufficient resources, especially financial and managerial, and are not prepared for such disruptions. Due to the lack of sufficient governmental support, most SMEs face financial decline and even go bankrupt. SMEs have limited capability and resources to recover from such crisis. Likewise, the situation of other industries is no different (Shafi et al., 2020).

A comprehensive survey of methods and indicators of assessment, levels of financial security and affecting factors is required to conduct the financial security assessment. Under the conditions of economic, political and pandemic instability, variability of micro and macro environmental factors influencing the financial security of enterprises becomes a particularly relevant question. The main tasks of an enterprise's financial security is to protect its financial interests from the influence of external and internal threats in order to ensure its efficiency.

The purpose of the paper is to assist practitioners in identifying strategies required to respond to the impact of external and internal factors on a representative industrial enterprise to help it in predicting risks in the early stage of business decision-making and planning financial security of the enterprises using simulation models.

Literature Review

The method for assessing the ecological and economic security of state enterprises is a sequence of stages that ensure: the formation of an information base for the research; selection of indicators; their processing using component, index and normative methods; and interpretation of the results of calculations (Cherchyk et al., 2019). The methodology for assessing the level of economic security is premised on two approaches: qualitative (mathematical model) and quantitative (simulation models). These approaches can help develop the strategies enabling us to identify and implement the policy that will maximize the level of economic security of an enterprise (Yaremko et al., 2018).

The author (Kaczmarek, 2019) quantifies corporate value in relation to the level of the financial security of a company's functioning. The assessments concern the degree of the balancing of effects in the context of value creation and sustainable management of financial security. The analysed entities include all the manufacturing enterprises in Poland using public statistical data for 2007–2018. The paper examines both value drivers and financial-security explanatory variables. The following result was extracted: There is a directly proportional relationship between the effects of the value creation process and ensuring of financial security of manufacturing enterprises.

Different companies from the automotive, metal and chemical sectors implement their strategies based on the risk factors affecting relations with suppliers operating in the country. The surveyed firms indicated the following sources of threats in relations with suppliers as the most critical: the possibility of untimely deliveries, quality defects in products, suppliers' financial situation, communication problems, low level of supply flexibility, product assortment errors and limited production capacity. Risk management is still essential to avoid disruptions in supply chains (Urbaniak, 2019).

Financial security of a microeconomic system means the achievement of a level of financial stability that will contribute to simultaneously maintaining financial equilibrium and ensuring targeted growth aligned with the development strategy. Three main determinants of the financial security of rail enterprises were identified for Ukrzaliznytsia: a reduction in traffic volumes, unstable capital structure and the impossibility of timely repayment of current liabilities (Britchenko et al., 2018). The effectiveness of financial security depends on building a high-quality financial architecture, which consists of capital structure, ownership structure and quality of corporate governance (Sosnovska & Zhytar, 2018).

The sensitivity of small and medium-sized enterprises to shocks in the economy and competition with new rivals generate risks of resource shortage and derived demand on credit. In this case, businesses also face a number of challenges, including high interest rates and significant requirements to loan against a pledge. Therefore, solving these problems is an important task to ensure the growth of small businesses (Korkuna et al., 2016).

The study (Mutoko, 2015) aims at exploring the financial challenges faced by small-, micro- and medium-sized enterprises (SMMEs) in manufacturing. The results show that SMMEs use more internal financing than external financing, as they cannot easily access external financing due to a lack of collateral security, high default rate, poor credit rating, poor banking history, lack of honest reporting and lack of up-to-date records. Commercial banks should offer a mentor and guide SMMEs, in addition to financing them. SMMEs need to benchmark with the best companies in other countries. Commercial banks should develop financing packages that suit firms according to their growth rate.

Over 94% of enterprises have been affected in some form by the ongoing coronavirus outbreak or due to the lockdown (Shafi et al., 2020). Specifically, 31% of SMMEs have shut down business completely, whereas 19% have partially closed their businesses, and 18% of enterprises are planning to apply for a loan to ensure their financial security. During any economic crisis, most businesses face a cash flow shortage; therefore, enterprises require new strategies to overcome the cash flow shortage. About two-thirds of enterprises can be maintained under pandemic conditions up to 8 weeks (around 2 months). Over 27% of the participating enterprises indicated the need for the provision of loan on a low-interest basis, and over 23% aim to get subsidies on utility charges (Shafi et al., 2020).

In the process of ensuring the economic security of an enterprise, special attention should be paid to the economic security of production, which includes KPIs (key performance indicators) of operational activity, such as break-even point, financial safety margin and operating leverage. The analysis of these indicators and data analysis can help in determining the reserves for increasing the efficiency of production (Ianioglo, 2016; Kobets et al., 2018). An effective corporate governance structure is designed as an institute to ensure a scientific decision-making approach to financial management operations, which helps a company guard against operational risks, reducing the company's financial risk (Long & Liu, 2016).

Security means an enterprise's state of safety from all threats in the present and in future when the company can survive and expand its growth despite all affecting threats.

Financial security is a financial position of enterprise that is characterized by the balance of financial interests and the ability to ensure their implementation; resistance to the negative impact of internal and external threats of company's environment; and ability to provide financial equilibrium and sustainable financial stability of the enterprise in the short and long run (Nosovaa & Yafinovycha, 2015).

An enterprise's financial security includes the following aspects: 1.

Financial security as a component of the enterprise's economic security and stable finance position;

Identification of problem areas to protect independence of the enterprise and its own financial interests;

Monitoring of the internal and external factors of the company's risk, growth and stability;

Combination of quantitative and qualitative indicators that should have the appropriate threshold (normative values) to determine the level of security; and

Evaluation of measures of financial security effectiveness.

The objects of impact to support these aspects are income, cash flows, equity, commitment, investment in assets and financial and economic risks, the last being the most dangerous.

The list of financial interests of an enterprise includes: 1.

Maximization of the welfare of its owners;

Increase in profitability of equity;

Adequacy of financial resources at all stages of the company's development;

Financial stability of the company under conditions of its growth;

High level of investment activity; and

High level of financial innovation activities.

An enterprise should ensure its development and stability, providing protection for its financial interests at all levels of financial relations.

Financial security demonstrates the accuracy of the chosen financial strategy under dynamic market conditions. Fluctuations in the individual parameters of an enterprise's financial security require decision-making about the reserve fund to ensure the necessary level of financial stability.

In Ukraine, the basic legal act aimed at regulating financial security and bankruptcy is the constitution of the country. Besides, financial security is indirectly regulated by laws of Ukraine, such as ‘On the Fundamentals of National Security of Ukraine’, ‘On Protection Against Unfair Competition’, ‘The Commercial Code of Ukraine’ and the ‘European Convention on Certain International Aspects of Bankruptcy’, which explain the international aspects of bankruptcy procedures.

Enterprise’s economic security includes the organization of cash flows analysis and profit formation affecting most components of the financial stability of enterprise. An enterprise's financial security mechanism has to assess and identify internal and external factors influencing financial security, which can be determined not only on the basis of data from previous periods of business operation but also using simulation methods in assessing the current situation and giving predictions for the future considering the influence of micro and macro factors on the enterprise's activity. To simulate the influence of internal and external environmental factors on financial position indicators, we can use scenario methods. The optimal criterion for indicators of financial stability is a bigger amount of equity than liabilities. Indicators being lower than recommended can affect the solvency of the enterprise. If the indicators are higher than their normative value, it can be a sign of ineffective use of available financial resources. Requirements for the values of the indicators are not mandatory, but advisory.

Creation of a financial security assessment system will help develop tactics and a strategy for enterprises' activity.

The financial mechanism that ensures an appropriate level of financial security of an enterprise consists of: financial methods, instruments, leverage and legal and information support. Financial forecasting is used to determine the short- and long-run indicators that characterize the financial state of the enterprise.

Financial indicators can provide several scenarios of actions. Plans based on forecasts with reference to a company's financial capabilities and strategies provide key indicators for the future.

The following reasons can lead to the emergence of financial crisis in an enterprise: 1.

Incorrect development strategy and KPIs; and

Mistakes in the implementation of the enterprise's management (incorrectly defined capital structure, failures in planning of reserve fund, etc.).

The environmental factors that can affect an enterprise are: 1.

Internal (endogenous, including own finance) factors at the control of the enterprise; and

External (exogenous) factors, which are out of the control of the enterprise and which may affect its activity (changing economic conditions, adopted legislation acts). The external environment consists of micro and macro factors, permanent (technical progress, exchange rate) and temporary ones (disasters, pandemic, seasonality).

The classification of financial security threats is presented in Table 1 (Bagrov, 2008; Baranovsky, 2004; Bilyiy, 2018).

Table 1.

Classification of Financial Security Threats.

Characteristics of Financial Security Threats	Interpretation of Characteristics
Source of financial security	Unfair competition; reservation price; supply chain contractors; strike-breakers; criminal deals; actions of the state and local authorities
Object of attacks	Informational; financial; human resources
Size of expected loss	Catastrophic (bankruptcy or deep financial crisis); critical size (long-run instability); difficulties (short-run instability); minor impact (immediate-run instability)
Forms of revealing	Quantitative threats (poor reserve fund); qualitative threats (financial crisis, bankruptcy, corporate conflicts, etc.)

Source: Bagrov, 2008; Baranovsky, 2004; Bilyiy, 2018.

Financial risk management (stand-alone risk, risk of specific projects, stand-alone risk measured by assessing the volatility of cash flow and profitability of the enterprise, market risk) is part of an enterprise's financial security system. It includes: 1.

Qualitative analysis of risks that threaten the financial security of the company (revealing of risk factors, identification of diversified and undiversified risks); and

Quantitative risk assessment (e.g., standard deviation of expected values of reserve fund), which involves determining the probability of occurrence and the size of potential losses to minimize risks of financial instability of the enterprise.

Financial risk depends on the availability of debt sources in the enterprise's capital structure and is characterized by indicators of financial leverage. The sources of financial risk are instability of demand and variability of financial conditions of credit. The higher the interest on borrowing, the higher are the financial risks, which can lead to reducing financial security.

In order to assess the financial sustainability of an enterprise, it is necessary to determine normative values of the indicators based on empirical or simulation data for certain industries of the economy. They can be considered as indicators characterizing the activity of the most effective enterprise or average data for enterprises under study plus/minus standard deviation, where the number of indicators may vary depending on the task of analysis (Nosovaa & Yafinovycha, 2015). The effectiveness of cash flow management is defined by synchronization of cash receipts and cash payments of the enterprise.

The use of key indicators to assess an enterprise's financial security reveals the weaknesses of its activity. In order to improve the financial security of enterprise, we have to develop an estimation algorithm of financial security, comprising: 1.

Simulation of probability function, which includes the expected value and standard deviation of reserve fund and identification of threats to the enterprise's financial security;

Calculation of the indicators to explain the financial security of the enterprise;

Summary of all quantitative (means, standard deviations) and qualitative (optimistic, pessimistic and most probable scenario) performance indicators;

Diagnosis of financial security and decision-making regarding its maintenance and improvement; and

Monitoring of the level of financial security and enforcement of its optimal performance level.

After obtaining meaningful and important information, advanced statistical analysis can bring new insights to many areas, such as markets, industries and microeconomic systems. We propose methods of statistical analysis combined with practical applications.

Simulation model can determine key characteristics based on an original system, transaction, or process for experimentation or training. The model is designed to simulate key features. Simulation is not a single technique, but a method to solve problems. It can use various models to represent practical difficulties and verify which measures are effective at solving them. Using a platform provided by computational economics, establish a simulation model of agents in artificial markets (Song & Fisher, 2018).

The problem for the manufacturer is to determine the initial level of the reserve fund. The authors derive the mean and variance of the reserve level as a function of time and provide a robust heuristic approach to aid the manufacturers in their decisions (Buczkowski & Kulkarni, 2006). A significant number of cooperatives in the world have a reserve fund. At the same time, successful cooperatives can operate without any reserve funds. The existence of reserve funds decreases the quality of service to consumers in rural areas in Israel (Galor & Sofer, 2019). Hughes and Nagurney (1992) presents a network model and algorithm of financial flow of funds accounting, which can be used to calculate reconciled values of all outstanding financial instruments, tangible assets and net worth. A computer simulator is developed to run empirical experiments to assess different coupling structures and parameters of the economic and financial models (Onural et al., 2020).

Due to numerous uncertainties, such as bad weather conditions, frequent changes in the schedules of vessels and breakdowns of equipment, port managers are aiming at providing adaptive and flexible strategic planning using the AnyLogic simulation platform. An agent-based system dynamics simulation model as developed in paper (Muravev et al., 2020) can help reach a stable state in the main parameters of intermodal terminals.

Simulation Model

To develop a simulation model of an enterprise, we consider an indicator of the company's net cash flow (NCF), an increase of which is due to the following factors: 1.

Total revenue, TR;

Borrowing, CR⁺; and

Repayment of receivables, DZ⁻.

The distribution of the cash flow leading to its decrease is determined by the following reasons: 1.

Ensuring of the current production process, including the acquisition of various resources for production (M), wages (L) and capital cost (K); and

Compensation and payments, including repayment and servicing of loans (CR⁻), repayment and maintenance of payables to suppliers (KM⁻), repayment of debts related to the wage fund (KL⁻) and repayment and servicing of debts related to the maintenance of the functional state of fixed assets (KK⁻).

Thus, in the model, the value of net cash flow at each moment is determined as follows:

NCF = TR + {DZ}^{-} + {Cr}^{+} - K - {KK}^{-} - L - {KL}^{-} - M - {KM}^{-}

Exploring the financial security of the company, we will distinguish the state of autonomous and non-autonomous functioning and development.

The state of fully autonomous functioning and development of an enterprise is the best possible state of financial security for the enterprise, because its own financial resources generated from functioning are sufficient to cover the current needs (M + L) and development (K):

M + L + K \leq Vr

In practice, production and business activities and the financial flows serving them are impacted by the significant influence of random factors, which require some reserve to be compensated.

To assess the value of the guaranteed reserve, ensuring the state of fully autonomous functioning and development of the enterprise (u₁), it is necessary that the following condition is met at each period:

\max (M) + \max (L) + \max (K) = \min (V r) + R

where R is the reserve, that is, the minimum value of the company's net cash flow which guarantees the autonomous fulfilment by the enterprise of its current obligations in an unfavourable market environment.

To estimate the value of this reserve, we introduce the following simplifying assumptions: 1.

For each financial flow there are stable average standard deviations, which we denote as σ _M , σ _L . σ _K , σ _Vr ;

The boundary probabilistic values of financial flows should be determined taking into account the three-sigma rule, which gives the following values:

\begin{array}{l} (M) = M + 3 σ_{M} \\ (L) = L + 3 σ_{L} \\ (K) = K + 3 σ_{K} \\ (T R) = T R - 3 σ_{T R} \end{array}

(1)

Standard deviations of financial flows are directly proportional to their average values:

\begin{array}{l} σ_{M} = α_{M} M \\ σ_{L} = α_{L} L \\ σ_{K} = α_{K} K \\ σ_{T R} = α_{T R} T R \end{array}

(2)

As follows from Equation (2), α are proportionality coefficients between standard errors and expected values to simulate the probability distribution for a representative industrial enterprise. For a qualitative interpretation of its possible values, we use the scale in Table 2.

Table 2.

Interpretation Scale of Variation Coefficients' Values

Meaning of Variation Coefficient	Interpretation of Meaning
α ≤ 0.1	Financial flow is stable.
0.1 ≤ α ≤ 0.2	Financial flow is subject to insignificant fluctuations.
0.2 ≤ α ≤ 0.33	Financial flow is subject to significant fluctuations.
α ≥ 0.33	Cash flow is irregular.

Source: Lapach et al., 2001.

The total revenue is determined by the total cost of production, taking into account the profitability index of sales as follows:

TR = (1 + r) \cdot TC

(3)

where r is the profitability index of sales and TC the total cost of the final product; and 5.

The total cost of production has a stable structure. In (Nikiforova, 2008), the following structure of the cost for ferrous metallurgy of Ukraine is given: material costs—86%; labour costs—8%; expenses for social events—3%; and depreciation—3%. Thus, taking into account the structure of financial flows identified in the simulation model, we can define the following relations:

\begin{matrix} M = 0.86 \cdot T C \\ L = (0.08 + 0.03) \cdot T C = M = 0.11 \cdot T C \\ K = 0.03 \cdot T C \end{matrix}

(4)

Then, taking into account Equations (1) and (2), the state of fully autonomous functioning and development of an enterprise is achieved under the following condition:

M \cdot (1 + 3 α_{M}) + L \cdot (1 + 3 α_{L}) + K \cdot (1 + 3 α_{K}) = T R \cdot (1 - 3 α_{T R}) + R

(5)

where R is a reserve fund that guarantees the fully autonomous functioning and development of the enterprise.

Using Equations (3) and (4) and also taking into account that the average profitability of Ukrainian metallurgical enterprises was r = 6.61%, Equation (5) can be rewritten as follows:

T C \cdot (0.86 (1 + 3 α_{M}) + 0.11 (1 + 3 α_{L}) + 0.03 (1 + 3 α_{K})) = T C \cdot 1.066 (1 - 3 α_{T R}) + R

from where

R = T C \cdot (0.86 (1 + 3 α_{M}) + 0.11 (1 + 3 α_{L}) + 0.03 (1 + 3 α_{K}) - 1.066 (1 - 3 α_{T R}))

(6)

As one can see from Equation (6), the value of the reserve fund is proportional to the value of current assets of the enterprise, TC. For further analysis, we will consider the share of the reserve fund in the structure of current assets (R/TC):

\frac{R}{T C} = 0.86 (1 + 3 α_{M}) + 0.11 (1 + 3 α_{L}) + 0.03 (1 + 3 α_{K}) - 1.066 (1 - 3 α_{T R})

(7)

Let us consider the main factors determining the dynamics of (R/TC). Thus, for the analysis, the system of partial derivatives should be determined as follows:

{\begin{matrix} \frac{\partial (R / T C)}{\partial α_{M}} = 3 \cdot 0.86 α_{M} = 2.58 α_{M}, \\ \frac{\partial (R / T C)}{\partial α_{L}} = 3 \cdot 0.11 α_{L} = 0.33 α_{L}, \\ \frac{\partial (R / T C)}{\partial α_{K}} = 3 \cdot 0.03 α_{K} = 0.09 α_{K}, \\ \frac{\partial (R / T C)}{\partial α_{T R}} = 3 \cdot 1.066 α_{TR} = 3.198 α_{TR} \end{matrix}

(8)

From Equation (8), it follows that the key factors determining the dynamics of the reserve, guaranteeing the autonomy of the operation and development of the enterprise, are the variation of the financial flow, serving the formation of various resources for production (α_M), and the variation of the financial flow, forming revenue from sales of products (α_Vr). If the values of the variation coefficients are comparable, the variation of revenue determines about 52% $(\frac{3.198}{2.58 + 0.33 + 0.09 + 3.198} \times 100 %)$ and the variation of resources about 42% $(\frac{2.58}{2.58 + 0.33 + 0.09 + 3.198} \times 100 %)$ of the variation of the reserve fund.

Thus, exploring the mechanisms to reduce the variation in financial flows is associated with revenue generation and financing of inputs. It is possible to achieve a significant reduction in the reserve fund. To illustrate the scale of this fund, we will determine its expected values for various combinations of the corresponding coefficients of variation. In this case, to calculate the value of the fund, we use Equation (7) and take the values presented in Table 1 as possible values of the coefficients of variation. The results of the relevant calculations are presented in Table 3.

Table 3.

Dynamics of the Reserve Fund under Financial Flows Variation.

S. No.	Values of Variation Coefficients	α_TR
S. No.	Values of Variation Coefficients	0.1	0.2	0.33
	α_M	α_K = α_L = 0,1
1	0.1	0.5538	0.8736	1.28934
2	0.2	0.8118	1.1316	1.54734
3	0.33	1.1472	1.467	1.88274
	α_M	α_K = α_L = 0,2
4	0.1	0.5958	0.9156	1.33134
5	0.2	0.8538	1.1736	1.58934
6	0.33	1.1892	1.509	1.92474
	α_M	α_K = α_L = 0.33
7	0.1	0.6504	0.9702	1.38594
8	0.2	0.9084	1.2282	1.64394
9	0.33	1.2438	1.5636	1.97934

Source: Results of our simulation experiment.

The results show that even with relatively stable financial flows with a variation of 10%, to ensure the autonomous, sustainable operations and development of ferrous metallurgy enterprises, the reserve fund should be more than half of their total cost ( $\frac{R}{TC} = 55.38 %$ ). This in turn leads to the fact that in order to independently achieve a high level of financial security guarantees, enterprises have to sacrifice production efficiency, since the reserve fund is an immobilized enterprise's return capital. The arising losses for enterprises of ferrous metallurgy from this will be as follows (supposing that $R = 0.5538 \cdot T C$ ):

R \cdot (1 + 0.066) = 0.5538 \cdot T C \cdot 1.066 = 0.5538 \cdot T R

It is obvious that the independent formation of such a reserve is an unbearable burden for the enterprise. To distribute it, it is necessary to transfer a part of this burden to external counterparties. The state of non-autonomous (dependent) functioning and development of an enterprise is characterized by non-negative values of receivables and payables indicators, as well as a possible non-zero credit flow, which can be represented by the following system of equations:

\begin{array}{l} C r \in (0, \max (C r); C r^{+} \geq 0; C r^{-} \geq 0 \\ K K \in (0, \max (K K); K K^{+} \geq 0; K K^{-} \geq 0 \\ K L \in (0, \max (K L); K L^{+} \geq 0; K L^{-} \geq 0 \\ K M \in (0, \max (K M); K M^{+} \geq 0; K M^{-} \geq 0 \\ D Z \in (0, \max (D Z); D Z^{+} \geq 0; D Z^{-} \geq 0 \end{array}

Thus, the level of financial security of an enterprise can be estimated through the degree of its financial autonomy. To study the dynamics of financial security of an enterprise, we consider a system-dynamic model and simulation of allocated financial flows of an industrial enterprise in the context of random factors, which reflect threats affecting its financial security. Let us proceed to the definition of the integral indicator, which will give a full image of the state of financial security of the enterprise as a whole. To determine the integral indicator of financial security, we use the following procedure:

Forming a system of indicators and defining normative value and the direction of optimization for each indicator. In this case, to calculate corresponding coefficients in the simulation model, we will use the indicators as shown in Table 4.

Table 4.

The System of Integral Indicators of Financial Security Assessment.

S. No.	Name of the Indicator	Normative Value	Direction of Optimization
1	Current solvency ratio	2	Max.
2	Autonomy ratio	0,6	Max.
3	Return on assets	Inflation index* (i inf.)	Max.

Source: NBU (National Bank of Ukraine) requirement to Financial Security Indicators of Financial Institutions.

Note: *The NBU (National Bank of Ukraine) discount rate was adopted as an estimation of the standard value.

Additionally, the system of indicators includes receivables and payables, but unlike Equations (1)–(3) we will compare these indicators with each other, not with normative values. To do this, we will compare the turnover ratio of receivables (K_ODZ) with the turnover ratio of accounts payable (K_OKZ); 2.

Calculating the level of deviation of a specific indicator of the enterprise from the normative value as follows:

x = \frac{k_{f a c t}}{k_{n o r m}}

where k_fact is factual value of the indicator and k_norm is a normative value of the indicator.

For the system of indicators introduced into the simulation model, deviations from the normative values and conditions corresponding to the minimum required level of financial security are defined as follows:

\begin{array}{l} x_{1} = \frac{K_{T P}}{2} > 1; \\ x_{2} = \frac{K_{A}}{0.6} > 1; \\ x_{3} = \frac{R_{A}}{7 %} > 1. \end{array}

When comparing receivables and payables, a favourable situation is determined as when the turnover ratio of receivables is greater than the turnover ratio of accounts payable. Thus, a situation is favourable when the following inequality holds:

x_{4} = \frac{K_{O D Z}}{K_{O K Z}} > 1.

Determining integral assessment of the financial security during each period of enterprise operations. To do this we can use any convolution procedure based on calculations of cumulative or average values, for example, arithmetic or geometric average. At this stage the influence of the integral assessment (H) is more important than individual factors:

H = x_{1} + x_{2} + x_{3} + x_{4}

Taking into account the conditions introduced, the minimum required level will equal 4. The value of the integral index fluctuates within 2.9–4.15, which can be interpreted as an insufficient level of enterprise financial security. Thus, in three cases out of five with the values less than 4.0, the dynamics of the integral index tend to decrease (Figure 1).

Figure 1.

Source: Results of our simulation experiment.

Experiment

Information on the financial statements of firms is often confidential, which leads to the need to develop a simulation model of a firm’s activities and to conduct experimental research based on the size of the enterprise’s reserve fund, which guarantees its financial autonomy.

For the experiment, we consider three scenarios: 1.

Pessimistic scenario—The standard deviation of resource costs is determined by the ratios (resource costs are above their average value) $\bar{M} < M < \bar{M} + 3 σ_{M}$ , $\bar{L} < L < \bar{L} + 3 σ_{L}$ and $\bar{K} < K < \bar{K} + 3 σ_{K}$ , and on total revenue (which is below average) $\bar{TR} - 3 σ_{TR} < TR < \bar{TR}$ ;

Optimistic scenario—The standard deviation of resource costs is determined by the ratios (resource costs are below their average value) $\bar{M} - 3 σ_{M} < M < \bar{M}$ , $\bar{L} - 3 σ_{L} < M < \bar{L}$ and $\bar{K} - 3 σ_{K} < K < \bar{K}$ , and on total revenue (which is above average) $\bar{TR} < TR < \bar{TR} + 3 σ_{TR}$ ; and

Most probable scenario—The standard deviation of resource costs is determined by the bilateral inequalities (resource costs can be both higher and lower than their average values) $\bar{M} - 3 σ_{M} < M < \bar{M} + 3 σ_{M}$ , $\bar{L} - 3 σ_{L} < M < \bar{L} + 3 σ_{L}$ and $\bar{K} - 3 σ_{K} < K < \bar{K} + 3 σ_{K}$ , and on total revenue $\bar{TR} - 3 σ_{TR} < TR < \bar{TR} + 3 σ_{TR}$ .

The following formula is used to determine the required number of experiments to reveal the structure of the links between R / TC and the explanatory variables (Lapach et al., 2001):

N = (1, 5 \div 2) \cdot (1 + \sum_{i = 1}^{m} L_{i})

(9)

where m is the number of explanatory variables and L_i the degree of approximation by the factor i, L_i = F_i – 1, where F_i is the number of variation levels of each independent variable. Application of Equation (9) allows using experiments in 95% to obtain conclusions that are adequate for real life.

Using Equation (9) and the four explanatory variables of Equation (7), we obtain for a step of variation coefficient value with an accuracy of hundredths from 0 to 0.33 (absolute value): F_i = 34, where i = 1, 2, 3, 4. After substitution of the values of F_i in Equation (9), we have:

min N = 1, 5 \cdot (1 + \sum_{i = 1}^{m} L_{i}) = 1, 5 \cdot (1 + 4 \cdot (34 - 1)) \approx 200

max N = 2 \cdot (1 + \sum_{i = 1}^{m} L_{i}) = 2 \cdot (1 + 4 \cdot (34 - 1)) = 266 .

From this, we get that the average number of experiments required to obtain results adequate for real life should be $N = \frac{min N + max M}{2} \approx 233$ . Therefore, the number of observations should be at least 233. Let us consider 250 experimental observations each for the pessimistic and optimistic scenarios.

Scenario 1

We are going to look at the pessimistic scenario of forming an enterprise's reserves for all coefficients, which vary from 0.1 to 0.33 (Table 2). Using the procedure for random-numbers generation using existing restrictions for variables of a representative metallurgical firm (Table 5), we will generate 100 indicators for the four coefficients defined by the corresponding intervals and calculate the share of the reserve fund in the structure of current assets for each of them based on Equation (7).

Table 5.

Distribution of the Share of the Reserve Fund R / TC in the Structure of Current Assets (pessimistic scenario).

Interval	Frequency	Cumulative Frequency (%)
0.6665	1	0.40
0.7210	5	2.40
0.7755	4	4.00
0.8300	7	6.80
0.8845	7	9.60
0.9390	7	12.40
0.9935	10	16.40
1.0480	10	20.40
1.1025	16	26.80
1.1570	16	33.20
1.2115	19	40.80
1.2660	13	46.00
1.3205	17	52.80
1.3750	23	62.00
1.4295	13	67.20
1.4840	15	73.20
1.5384	16	79.60
1.5929	10	83.60
1.6474	17	90.40
1.7019	9	94.00
1.7564	7	96.80
1.8109	5	98.80
More	3	100.00

Source: Results of our simulation experiment.

The histogram of the distribution obtained for the experimental data described in Table 3 is shown in Figure 2.

Figure 2.

Source: Results of our simulation experiment.

The average value of the R / TC ratio as a result of simulation experiments for the initial actual data was 128%, with a standard deviation of 28%. With a 95% probability, the reserve for a representative enterprise should be between 123% and 134% of its current assets.

Scenario 2

Similarly, we consider the optimistic scenario of an enterprise's reserve formation for all coefficients, which vary from 0.1 to 0.33 (Table 2).

With a confidence level of 95%, the excess of revenues over the enterprise's costs during the simulation experiment (Figure 3) will be established within the range of 136%–147% of the current assets of the metallurgical firm (Table 4).

Table 6.

Distribution of the Share of the Reserve Fund R / TC in the Structure of Current Assets (optimistic scenario).

Interval	Frequency	Cumulative Frequency (%)
–2047	1	0.40
–1.991	0	0.40
–1.936	4	2.00
–1.880	4	3.60
–1.825	4	5.20
–1.769	10	9.20
–1.714	16	15.60
–1.658	11	20.00
–1.603	20	28.00
–1.547	16	34.40
–1.492	16	40.80
–1.436	24	50.40
–1.381	18	57.60
–1.325	13	62.80
–1.270	18	70.00
–1.214	11	74.40
–1.159	13	79.60
–1.103	11	84.00
–1.048	8	87.20
–0.992	12	92.00
–0.937	5	94.00
–0.881	9	97.60
More	6	100.00

Source: Results of our simulation experiment.

Figure 3.

Source: Results of our simulation experiment.

Scenario 3

Next, we consider the most likely scenario for forming an enterprise's reserves for all coefficients, which vary from −0.33 to 0.33 (Table 2), according to the procedure described above, when each of the four simulated indicators may deviate both above and below the average value (Table 6).

Using Equation (9) and the four explanatory variables of Equation (7), we obtain for a step the coefficient of variation with an accuracy of hundredths from −0.33 to 0.33: F_i = 67, where i = 1,2,3,4. After substitution of the values of F_i in Equation (9) we have:

min N = 1, 5 \cdot (1 + \sum_{i = 1}^{m} L_{i}) = 1, 5 \cdot (1 + 4 \cdot (67 - 1)) \approx 398

max N = 2 \cdot (1 + \sum_{i = 1}^{m} L_{i}) = 2 \cdot (1 + 4 \cdot (67 - 1)) = 530 .

From this, we get that the average number of experiments required to obtain results adequate for real life should be

N = \frac{min N + max M}{2} \approx 464

. Therefore, the number of observations should be at least 464. Let us consider 500 experimental observations.

Table 7.

Distribution of the Share of the Reserve Fund R / TC in the Structure of Current Assets (most probable scenario).

Interval	Frequency	Cumulative Frequency (%)
–1.85471	1	0.20
–1.69321	5	1.20
–1.5317	4	2.00
–1.3702	7	3.40
–1.20869	14	6.20
–1.04719	18	9.80
–0.88568	26	15.00
–0.72417	29	20.80
–0.56267	28	26.40
–0.40116	33	33.00
–0.23966	44	41.80
–0.07815	39	49.60
0.083354	46	58.80
0.244859	33	65.40
0.406365	30	71.40
0.567871	30	77.40
0.729376	18	81.00
0.890882	20	85.00
1.052388	24	89.80
1.213893	18	93.40
1.375399	18	97.00
1.536905	9	98.80
More	6	100.00

Source: Results of our simulation experiment.

The results of the simulation experiment in Table 7 demonstrate that in 49.6% of cases, there is no need for metallurgical enterprises to form a reserve fund, while in 50.4% of cases it becomes necessary to form a reserve fund to maintain the autonomous operations of the enterprise (Figure 4).

Figure 4.

Source: Results of our simulation experiment.

The average value of the R / TC ratio as a result of simulation experiments for the initial actual data was 3.96%, with a standard deviation of 77.4%. With a 95% probability, the reserve for a metallurgical company should be at least 11% of its return capital.

Conclusions

The use of the proposed simulation model made it possible to evaluate the complex effect of various factors on the financial security of an enterprise and its structure, and to investigate the dynamics of the integrated assessment of the financial security of an enterprise.

For statistically valid parameters for the operation of a metallurgical representative enterprise, three scenarios were considered. During simulation modelling, it was determined with a 95% probability that the reserve of a representative industrial enterprise should be up to 11% of its return capital. Moreover, in 50.4% of cases of production activities, a representative enterprise will explore these reserves using either equity or debt capital to ensure its own financial security. This simulation model can be implemented by practitioners in any other industry in the decision-making about the size of reserve fund of a representative industrial enterprise for initial parameters using different scenarios.

Footnotes

Declaration of Conflicting Interests

Funding

The authors received no financial support for the research, authorship and/or publication of this article.

ORCID iD

Vitaliy Kobets

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