Risk management in an enterprise cannot be a set of momentary actions. In any case, this is a whole process of directed actions. Moreover, the risk management process must be part of overall business management to achieve results.

As such, the risk management process includes a specific set of steps. It should be noted that in practice these stages are not necessarily implemented in strict sequence, but can be performed in parallel. The general scheme of risk management is presented in Figure 4.1.

As we see in this figure, there is a general sequence of actions that reflects the logic of the risk management process (thick arrows). In addition, there are feedback connections between stages, i.e. at any of them you can return to the previous one. At the last stage, as we will see later, a general assessment and analysis of the process is carried out. The results of this stage will be taken into account during the further implementation of each stage of the risk management process. This is shown by the arrows on the right.

At stage 3, decisions are made about the risk management methods used, which may require clarification of information about risks (stage 1) or determine the design of the monitoring process (stage 5).

So, this is the logic of the sequence of implementation of risk management stages in an enterprise. Now let's look at each of these stages in a little more detail.

Stage 1. Risk identification and analysis. Under risk identification understand the identification of risks, their specificity due to the nature and other characteristic features of risks, highlighting the features of their implementation, including studying the amount of economic damage, as well as changes in risks over time, the degree of relationship between them and the study of factors influencing them. This process involves determining the following points:

sources of uncertainty and risk;

consequences of risk realization;

information sources;

numerical determination of risk;

mutual influence of risks on each other.

At this stage, first of all, an information base is created for the implementation of the further risk management process: information about the risk and its consequences, the amount of economic damage, quantitative assessment of risk parameters, etc. Additionally, it should be noted that risk identification and analysis is not a one-time task a set of actions. Rather, it is a continuous process carried out throughout the entire risk management algorithm.

Stage 2. Analysis of risk management alternatives. There is a whole range of different methods to reduce the degree of risk and the amount of damage. At this stage, these methods are reviewed and analyzed in relation to a specific situation. That is, the manager decides how to reduce the risk and losses in the event of a risk situation, and looks for sources to cover this damage.

The risk management methods themselves are quite diverse. This is due to the ambiguity of the concept of risk and the presence of a large number of criteria for their classification. In the next section of this chapter we will look at the main methods in more detail, but here we will limit ourselves to just a brief overview of them.

Firstly, approaches to risk management can be grouped as methods for minimizing the negative impact of adverse events as follows.

Risk aversion(Risk elimination) is a set of measures leading to complete avoidance of the influence of the adverse consequences of a risk situation.

Risk Reduction(Risk reduction, Risk mitigation) are actions leading to a reduction in damage. In this case, the company takes on risks (Risk retention, Risk assumption).

Transfer of risk(Risk transfer) are measures that allow you to shift responsibility and compensation for damage arising from the occurrence of a risk situation to another entity.

From another point of view, risk management methods can be classified according to the ratio of the time of implementation of control measures and the occurrence of a risk situation.

Pre-event risk management methods– measures taken in advance aimed at changing significant risk parameters (probability of occurrence, extent of damage). These include methods of risk transformation (Risk control, Risk control to stop losses), which are mainly associated with preventing the realization of risk.

Typically, these methods are associated with preventive measures.– carried out after the occurrence of damage and aimed at eliminating the consequences. These methods are aimed at generating financial sources used to cover damage. These are mainly risk financing methods (Risk financing, Risk financing to pay for losses).

In graphical form, both classifications given here are presented in Figure 4.2.

Stage 3. Selection of risk management methods. Here the manager forms an anti-risk policy for the company, as well as a policy aimed at reducing the degree of uncertainty in its work. The main issues that need to be addressed are as follows:

selection of the most effective risk management methods;

determining the impact of the selected program on the overall risk in the organization’s activities.

In essence, the choice of risk management methods comes down to the calculation of an economic and mathematical model, where the criteria and limitations are the economic and probabilistic characteristics of risk (determined at the first stage of the risk management process). However, other parameters can be added here, for example, technical or social.

When developing a risk management system, a manager must take into account, first of all, the principle of its effectiveness. It lies in the fact that control actions should not focus on all risks, but, first of all, on those that have the greatest impact on the company’s activities. Under conditions of, say, budget constraints, the most insignificant risks should be discarded in order to save resources (passive strategy). At the same time, using the freed funds, intensive work is carried out with more serious risks (active strategy).

The result of this stage is a risk management program for the enterprise. It represents a detailed description of the activities that need to be taken, resource and information support, criteria for determining the effectiveness of the program, distribution of responsibilities, etc.

Stage 4. Execution of the selected risk management method. Here the program developed at the previous stage is directly implemented. The issues that are resolved at this stage relate to the technical specifics of the decisions made. The main ones are the following:

specific activities to be implemented;

the timing of these activities;

sources and composition of resources necessary to carry out this work;

identification of responsible persons.

In this way, contradictions and ambiguity in planning and monitoring the execution of the risk management program are eliminated.

Stage 5. Monitoring results and improving the risk management system. This stage implements feedback in the risk management system. The first task of this relationship is to determine the overall efficiency of the system as a whole. In addition, bottlenecks and weaknesses of risk management in the enterprise are highlighted.

The second task is to analyze the risks realized during the period. Here the reasons for their implementation and associated changes in the risk management program, if any, should be identified.

As the name of the stage suggests, it is aimed not only at monitoring the risk management process, but also at identifying those improvements that can improve the efficiency of the system. Thus, to the indicated tasks we can add the following questions that the manager concerns when implementing this stage:

the contribution of each implemented activity to the overall effectiveness of the system;

possible adjustments to the composition of these activities;

flexibility and efficiency of the decision-making system.

Among other things, at this stage the information base about risks is replenished. The updated information is used in the next cycle of the risk management process.

A feature of efficiency calculations at this stage is the consideration of hypothetical losses. This is due to the fact that during the analyzed period the risks may not have materialized at all, and the costs of operating the risk management system are incurred in any case. If we take into account only real losses, then in some cases the ratio of losses and costs will indicate zero efficiency of the risk management system. However, the absence of losses can serve as evidence of its high efficiency.

The main goal of assessing the effectiveness of implemented measures is to adapt their system to the changing external environment. Its achievement is carried out, first of all, through the following changes.

Replacing ineffective measures with more effective ones (within existing restrictions).

Changing the organization of execution of the risk management program.

Value at Risk- one of the most common forms of measuring financial risks. Commonly referred to as “VaR”.

It is also often called "16:15", it received this name because 16:15 is the time at which it supposedly should lie on the table of the head of the bank’s board JPMorgan. (In this bank, this indicator was introduced for the first time in order to improve the efficiency of working with risks.)

Essentially, VaR reflects the amount of possible loss that will not be exceeded over a certain period of time with some probability ( which is also called the “tolerable risk level”"). Those. the largest expected loss that an investor can receive within n days with a given probability

The key VaR parameters are:

1. Time horizon - the period of time for which the risk is calculated. (According to the Basel documents - 10 days, according to the Risk Metrics method - 1 day. Calculations with a time horizon of 1 day are more common. 10 days are used to calculate the amount of capital covering possible losses.)
2. The level of acceptable risk is the probability that losses will not exceed a certain value (According to the Basel documents, the value is 99%, in the RiskMetrics system - 95%).
3. Base currency - the currency in which VaR is calculated

Those. A VaR equal to X with a time horizon of n days, a risk tolerance of 95% and a base currency of US dollar would mean that there is a 95% chance that the loss will not exceed $X within n days.

• The standard for broker-dealer reporting of OTC derivatives transactions to the US Securities and Exchange Commission is a 2-week period and a 99% confidence level.
• The Bank of International Settlements to assess the adequacy of bank capital, I set the probability at 99% and a period of 10 days.
• JP Morgan publishes its daily VaR values ​​at the 95% confidence level.
• According to a study by New York University Stern School of Business, about 60% of US pension funds use VaR in their work

Example of VaR calculation in Excel:

Let's take the price history of the asset we are interested in, for example, ordinary shares of SberBank. In the example, I took EOD (EndOfDay) prices for 2010.

Let's calculate the standard deviation of the obtained return (the formula for calculating the standard deviation for a sample for Microsoft Excel will look like =STDEV.B(C3:C249)):

Assuming an acceptable risk level of 99%, we calculate the inverse normal distribution (quantile) for a probability of 1% (the formula for Excel in our case will look like =NORM.REV(1%, AVERAGE(C3:C249), C250)):

Well, now let’s directly calculate the value of VaR itself. To do this, subtract the estimated value obtained by multiplying by the quantile from the current value of the asset. Therefore, for Excel the formula will take the form: =B249-(B249*(C251+1))

In total, we received the calculated value of VaR = 5.25 rubles. Taking into account our time horizon and the degree of acceptable risk, this means that SberBank shares will not fall in price by more than 5.25 rubles over the next day, with a 99% probability!

Risk assessment is a set of analytical measures that make it possible to predict the possibility of obtaining additional business income or a certain amount of damage from a risk situation that has arisen and the untimely adoption of measures to prevent the risk.

The degree of risk is the probability of a loss event occurring, as well as the amount of possible damage from it.

• May be:
• acceptable - there is a threat of complete loss of profit from the implementation of the planned project;
• critical - it is possible that not only profits will not be received, but also revenues and losses will be covered at the expense of the entrepreneur’s funds;

catastrophic - loss of capital, property and bankruptcy of the entrepreneur are possible.

Quantitative analysis is the determination of the specific amount of monetary damage of individual subtypes of financial risk and financial risk in the aggregate.

Sometimes qualitative and quantitative analysis is carried out on the basis of assessing the influence of internal and external factors: an element-by-element assessment of the specific weight of their influence on the work of a given enterprise and its monetary value is carried out. This method of analysis is quite labor-intensive from the point of view of quantitative analysis, but brings its undoubted fruits in qualitative analysis. In this regard, more attention should be paid to the description of methods for quantitative analysis of financial risk, since there are many of them and some skill is required for their competent application.

In absolute terms, risk can be determined by the amount of possible losses in material (physical) or cost (monetary) terms.

Depending on the magnitude of probable losses, it is advisable to divide them into three groups:

• losses, the value of which does not exceed the estimated profit, can be called acceptable;
• losses whose value is greater than the estimated profit are classified as critical - such losses will have to be compensated from the entrepreneur’s pocket;
• Even more dangerous is catastrophic risk, in which the entrepreneur risks incurring losses exceeding all his property.

If it is possible in one way or another to predict and estimate possible losses for a given operation, then a quantitative assessment of the risk that the entrepreneur is taking has been obtained. By dividing the absolute value of possible losses by the estimated cost or profit, we obtain a quantitative assessment of the risk in relative terms, as a percentage.

Saying that risk is measured by the magnitude of possibilities. probable losses, the random nature of such losses should be taken into account. The probability of an event occurring can be determined by an objective method or a subjective one. The objective method is used to determine the probability of an event occurring based on calculating the frequency with which the event occurs.

The subjective method is based on the use of subjective criteria, which are based on various assumptions. Such assumptions may include the judgment of the assessor, his personal experience, the assessment of a rating expert, the opinion of a consulting auditor, etc.

Thus, the basis for assessing financial risks is to find the relationship between certain amounts of losses of an enterprise and the likelihood of their occurrence. This dependence is expressed in the plotted curve of the probabilities of occurrence of a certain level of losses.

Fitting the curve is an extremely complex task that requires financial risk officers to have sufficient experience and knowledge. To construct a curve of the probabilities of a certain level of losses (risk curve), various methods are used: statistical; cost feasibility analysis; method of expert assessments; analytical method; method of analogies. Among them, three should be especially highlighted: the statistical method, the method of expert assessments, and the analytical method.

The essence of the statistical method is that the statistics of losses and profits that occurred in a given or similar production are studied, the magnitude and frequency of obtaining a particular economic return are established, and the most probable forecast for the future is compiled.

Undoubtedly, risk is a probabilistic category, and in this sense, it is most reasonable from a scientific point of view to characterize and measure it as the probability of a certain level of losses occurring. Probability means the possibility of obtaining a certain result.

Financial risk, like any other, has a mathematically expressed probability of loss, which is based on statistical data and can be calculated with fairly high accuracy. To quantify the amount of financial risk, it is necessary to know all the possible consequences of any individual action and the likelihood of the consequences themselves.

In relation to economic problems, the methods of probability theory come down to determining the values ​​of the probability of the occurrence of events and to selecting the most preferable from possible events based on the largest value of the mathematical expectation, which is equal to the absolute value of this event multiplied by the probability of its occurrence.

The main tools of the statistical method for calculating financial risk: variation, dispersion and standard (mean square) deviation.

Variation is a change in quantitative indicators when moving from one result option to another. Dispersion is a measure of the deviation of actual knowledge from its average value.

The degree of risk is measured by two indicators: the average expected value and the variability (variability) of the possible result.

The average expected value is related to the uncertainty of the situation and is expressed as a weighted average of all possible outcomes E(x), where the probability of each outcome (A) is used as the frequency or weight of the corresponding value (x). In general, it can be written like this:

E(x)=A1X1 +A2X2+···+AnXn.

The average expected value is the value of the event magnitude that is associated with an uncertain situation. It is a weighted average of all possible outcomes, where the probability of each outcome is used as the frequency, or weight, of the corresponding value. In this way, the result that is supposedly expected is calculated.

Cost feasibility analysis is focused on identifying potential risk areas taking into account the financial stability of the company. In this case, you can simply make do with standard methods of financial analysis of the results of the activities of the main enterprise and the activities of its counterparties (bank, investment fund, client enterprise, issuing enterprise, investor, buyer, seller, etc.).

The method of expert assessments is usually implemented by processing the opinions of experienced entrepreneurs and specialists. It differs from statistical only in the method of collecting information to construct a risk curve.

This method involves collecting and studying estimates made by various specialists (of the enterprise or external experts) of the probabilities of occurrence of various levels of losses. These assessments are based on taking into account all financial risk factors, as well as statistical data. The implementation of the method of expert assessments becomes significantly more complicated if the number of assessment indicators is small.

The analytical method of constructing a risk curve is the most complex, since the underlying elements of game theory are accessible only to very narrow specialists. The most commonly used subtype of analytical method is model sensitivity analysis.

The sensitivity analysis of the model consists of the following steps: selection of a key indicator in relation to which the sensitivity is assessed (internal rate of return, net present value, etc.); choice of factors (inflation level, state of the economy, etc.); calculation of key indicator values ​​at various stages of the project (purchase of raw materials, production, sales, transportation, capital construction, etc.).

The sequences of costs and receipts of financial resources formed in this way make it possible to determine the flows of funds for each moment (or period of time), i.e. determine performance indicators. Diagrams are constructed that reflect the dependence of the selected resulting indicators on the value of the initial parameters. By comparing the resulting diagrams with each other, it is possible to determine the so-called key indicators that have the greatest impact on the assessment of the project’s profitability.

Sensitivity analysis also has serious shortcomings: it is not comprehensive and does not clarify the likelihood of alternative projects being implemented.

The method of analogies when analyzing the risk of a new project is very useful, since in this case data on the consequences of the impact of unfavorable financial risk factors on other similar projects of other competing enterprises is examined.

Indexation is a way to preserve the real value of monetary resources (capital) and profitability in the face of inflation. It is based on the use of various indices.

For example, when analyzing and forecasting financial resources, it is necessary to take into account price changes, for which price indices are used. Price index is an indicator characterizing price changes over a certain period of time.

Thus, existing methods for constructing a curve of the probabilities of a certain level of losses are not entirely equivalent, but one way or another they make it possible to make an approximate assessment of the total volume of financial risk.

Source - O.A. Firsova - METHODS OF ASSESSING THE DEGREE OF RISK, FSBEI HPE "State University - UNPC", 2000.

Excerpt from the book “Credit Risk Analysis”.

There are various methodologies for assessing possible losses on financial instruments and portfolios. Let us note the main ones:

- VaR (Value-at-Risk - “value at risk”);
- Shortfall;
- Analytical approaches (for example, delta-gamma approach);
- Stress Testing (new technique).

Let's consider the most common method of quantitative assessment of the market risk of trading positions - VaR:

VaR is an estimate, expressed in monetary units of the base currency, of the amount that losses expected during a given period of time (time horizon) with a given probability (confidence level) will not exceed. The basis for assessing VaR is the dynamics of exchange rates and prices of instruments over a specified period of time in the past.

The time horizon is often selected based on the length of time the financial instrument is in the portfolio or its liquidity, based on the minimum realistic period during which this instrument can be sold on the market without a significant loss. The time horizon is measured in the number of working or trading days.

The level of confidence, or probability, is selected depending on the risk preferences expressed in the bank's regulatory documents. In practice, levels of 95% and 99% are often used. The Basel Committee on Banking Supervision recommends a level of 99%, which supervisory authorities are guided by.

The VaR value is calculated by three main methods:

• parametric;
• historical modeling method;
• using the Monte Carlo method.

Parametric method for calculating VaR

This method can be used to assess the market risk of financial instruments for which the bank has an open position. It is worth noting that the parametric method is poorly suited for assessing the risk of assets with non-linear price characteristics. The main disadvantage of this method is the assumption of a normal distribution of returns on financial instruments, which, as a rule, does not correspond to the parameters of the real financial market. To parametrically calculate VaR, it is necessary to regularly calculate the volatility of securities quotes, exchange rates, interest rates or other risk factors (the variable on which the change in the value of positions opened by the bank most depends).

The basic formula for determining VaR taking into account the value of an asset position is as follows:

VaR = V* λ *σ,

Where:
λ - quantile of the normal distribution for the selected confidence level. The quantile shows the position of the desired value of the random variable relative to the average, expressed in the number of standard deviations of the portfolio return. With a probability of deviation from the mean equal to 99%, the quantile of the normal distribution is 2.326, with 95% - 1.645;
σ - volatility of changes in the risk factor. Volatility is the standard (mean square) deviation of the change in the risk factor relative to its previous value;
V- current value of the open position. An open position is understood as the market value of financial instruments purchased or sold by a bank for profit or other purposes in such a way that the number of financial instruments currently on balance sheet or off-balance sheet accounts is not zero.

Example
The investor owns shares of the company worth 10 million rubles. The specified confidence level is 99% with a time horizon of one day. One-day stock price volatility (σ) = 2.15.
VaR = 10 * 2.33 * 2.15 = 50.09 million rubles.

In other words, the probability that the investor's losses will exceed 50 million rubles. over the next 24 hours is equal to 1%. Losses exceeding 50 million rubles. expected on average once every 100 trading days.

Historical Simulation Method for VaR Calculation

This method is based on the assumption of stationary behavior of market prices in the near future.

First, a period of time is selected (the number of working or trading days) for which historical changes in the prices of all assets included in the portfolio are tracked. For each time period, price change scenarios are simulated. The hypothetical price of an asset is calculated as its current price multiplied by the price increase corresponding to a given scenario. The entire current portfolio is then completely revalued at prices modeled based on historical scenarios, and for each scenario it is calculated how much the value of the current portfolio might change. After this, the results obtained are ranked by number in descending order (from the largest gain to the largest loss). And finally, in accordance with the desired level of confidence, the VaR value is defined as the maximum loss that is equal to the absolute value of the change with a number equal to the integer part of the number (1-quantile at a given level of confidence) * number of scenarios.

Unlike the parametric method, the historical modeling method allows for a clear and complete assessment of risk; it is well suited for assessing the risk of assets with non-linear price characteristics. The advantage of historical modeling is that it eliminates the high impact of model risk and is based on a model actually observed in the past, without taking into account the assumptions of a normal distribution or any other stochastic model of market price dynamics. It is worth noting that when calculating VaR using this method, there is a high probability of measurement errors due to a short period of historical sampling. In addition, the oldest observations are not excluded from the sample, which sharply worsens the accuracy of the model.

Example:
In 400 scenarios, there were 300 cases of loss and 100 cases of gain. VaR (95%) is the absolute value of the 21st largest loss (400+1-1(1-0.05)*400=21, where 0.05 is the quantile at the 95% confidence level), i.e. changes numbered 380.

Monte Carlo method for calculating VaR

The Monte Carlo method, or stochastic simulation method, is the most complex method for calculating VaR, but its accuracy can be significantly higher than other methods. The Monte Carlo method is very similar to the historical modeling method; it is also based on changes in asset prices, only with specified distribution parameters (mathematical expectation, volatility). The Monte Carlo method involves the implementation of a large number of tests - one-time simulations of the development of the situation in the markets with the calculation of the financial result for the portfolio. As a result of these tests, a distribution of possible financial results will be obtained, on the basis of which a VaR assessment can be obtained by cutting off the worst ones according to the selected confidence probability. The Monte Carlo method does not imply condensation and generalization of formulas to obtain an analytical assessment of the portfolio as a whole, therefore, much more complex models can be used for both the portfolio result and for volatilities and correlations. The method is as follows. Based on retrospective data (time period), estimates of mathematical expectation and volatility are calculated. Using a random number generator, data is generated using a normal distribution and entered into a table. Next, the trajectory of the modeled prices is calculated using the natural logarithm formula and the portfolio value is revalued.

Since VaR estimation by the Monte Carlo method is almost always performed using software, these models may not be formulas, but rather complex subroutines. Thus, the Monte Carlo method allows the use of models of almost any complexity when calculating risks. Another advantage of the Monte Carlo method is that it provides the opportunity to use any distribution. In addition, the method allows you to simulate market behavior - trends, clusters of high or low volatility, changing correlations between risk factors, what-if scenarios, etc. It is worth noting that this method requires powerful computing resources and, with the simplest implementations, may turn out to be close to historical or parametric VaR, which will lead to the inheritance of all their shortcomings.

The disadvantage of the VaR risk assessment method is that it ignores many of the significant and interesting details needed to truly represent market risks. VaR does not take into account how the market contributes to risk, what portfolio structural changes increase risk, or what hedging instruments control specific risk. The model does not provide information about the worst possible loss beyond the VaR value (at a given 95% confidence level, it remains unknown what the losses might be in the remaining 5% of cases).

As an alternative measure of market risk, the Shortfall methodology can be used, which represents the average value of losses exceeding VaR. Shortfall is a more conservative measure of risk than VaR. For the same probability level, Shortfall requires you to reserve more capital. Thus, it allows for large losses that are unlikely to occur. It also more adequately allows for risk assessment in such a common case in practice, when the loss distribution has “fat tails” of the distribution function (deviations at the edges of the probability density distribution from the normal distribution).

Risk calculation in accordance with Regulations of the Central Bank of the Russian Federation No. 313-P

The amount of market risk is included in the calculation of the bank’s own funds (capital) adequacy ratio in accordance with Bank of Russia Instruction No. 110-I dated January 16, 2004 “On mandatory standards for banks.” The procedure for calculating the amount of market risks by credit institutions is provided for by the Regulations of the Central Bank of the Russian Federation “On the procedure for calculating the amount of market risk by credit institutions” dated November 14, 2007 N 313-P. The total amount of market risk is calculated using the formula:

RR = 12.5 * (PR + FR) + VR,

Where:
RR- the total amount of market risk;
ETC- the amount of market risk for financial instruments sensitive to changes in interest rates (hereinafter referred to as interest risk);
FR- the amount of market risk for financial instruments that are sensitive to changes in the current (fair) value of equity securities;
VR- the amount of market risk for positions opened by a credit institution in foreign currencies and precious metals.

Types of financial risks

1. Credit risk refers to the likelihood that a debtor will default and renege on its obligations to repay the debt. This type of risk applies to the lender and includes loss of principal, interest due, disruption of cash flows and increased cost of receipt. Losses can be either partial or complete.

2. Concentration risk is a banking term meaning the spread of a bank account divided by the number of bank debtors.

3. Market risk is the probability of partial or complete loss of position value due to changes in market prices.

4. Interest rate risk — risk of changes in yield for bondholders. Bond yields depend on the price's sensitivity to changes in market interest rates. The sensitivity, in turn, depends on the coupon rate on the bond and the expiration time.

5. Currency risk or the so-called FX risk is a financial risk that appears when a financial transaction is carried out in a currency different from the main currency of the company. Currency risk is also present if a company's subsidiary abroad produces financial statements in a currency different from the currency used for the preparation of the consolidated group's statements. This risk consists of an unfavorable change in exchange rates for the company before the transaction is completed.

6. Stock risk is the financial risk associated with owning shares in a particular investment. Stock risk usually refers to a company's equity through the purchase of shares.

7. Commodity risk refers to the uncertainty of future market values ​​and the amount of future income that results from changes in commodity prices.

8. Liquidity risk is the risk of not being able to sell a security or asset quickly on the open market to avoid financial loss (or to maintain a required return).

9. Refinancing risk. In banking and finance, refinancing risk is the likelihood that a borrower will not be able to refinance (take on new debt) to pay off the current debt.

10. Operational risk - this is the risk of changes in value, the reason for which is the fact of recording losses resulting from incorrect internal policies of the organization, as well as as a result of the influence of external factors that could not be predicted.

11. Country risk is the risk associated with investing in a particular country. This type of risk depends on changes in the business environment that may affect operating profits or asset values ​​in a particular country.

12. Legal risk is the cost of uncertainty in the legal position of the company, multiplied by the probability of a lawsuit occurring.

13. Political risk refers to the likely difficulties of businesses and governments that may result from political decisions or other policy changes changing the likelihood of business plans being realized.

14. Assessment risk is the financial risk that an asset is overvalued or undervalued at the date of the transaction compared to its expected value.

15. Reputational risk . This risk represents damage to the company’s reputation, revenue, increased legal, operational and capital costs that are associated with a criminal event in which the company will be found innocent.

16. Volatility risk is the probability of a change in the price of an investment portfolio as a result of the volatility factor. This is typically associated with derivatives portfolios, which involve the risk that the underlying asset will experience a significant change in market price.

17. Calculated risk. This risk includes the possibility that the seller will not provide an asset, or its equivalent, after completing a transaction in which the other party has already fulfilled its obligation to transfer liquidity (money) or other assets.

18. Systemic risk — the risk of a fall in the entire financial system or the entire market. This risk differs from non-systemic risk in that it is not associated with the risk of a separate part of the market, a consolidated group or any other entity if this entity cannot influence the entire market at once.