Modeling risky situations in the economy Laboratory work. Risk theory and modeling of risky situations. The concept of risk. Criteria of risk classifications. Risk accounting in investment projects
Risk theory and modeling of risky situations
Lecture 1.
- The concept of risk. Criteria of risk classifications.
- Mathematical apparatus for modeling and studying the risk of situations.
- The basic concepts of the theory of games. Classification of games.
1. The concept of risk. Criteria of risk classifications.
Concept of risk
Any sphere of human activity, especially economics or business, is associated with decision-making in the conditions of non-payment of information.
Sources of uncertainty can be the most diverse: the instability of the economic, political situation, the uncertainty of the actions of business partners, random factors, that is, a large number of circumstances, to consider which is not possible (for example, weather conditions, the uncertainty of demand for goods, not the absolute reliability of production processes, Inaccuracy of information, etc.). Economic solutions, taking into account the listed and many other uncertain factors, are accepted within the framework of the so-called decision-making theory - an analytical approach to the choice of the best action (alternatives) or a sequence of actions. Depending on the degree of certainty of possible outcomes or the consequences of the various actions faced by the decision-making person (LPR), three types of models are considered in decision-making theory:
the choice of solutions in conditions of certainty, if relative to each action it is known that it consistently leads to some specific outcome;
the choice of solution at risk, if each action leads to one of the many possible private outcomes, and each outcome has a calculated or expertly estimated probability of appearance. It is assumed that the LPR of these probabilities are known or can be determined by expert assessments;
the choice of solutions for uncertainty, when something or another or several actions, have their consequence many private outcomes, but their probabilities are completely unknown or do not make sense.
The difference between risk and uncertainty refers to a method for specifying information and is determined by the presence (in the case of risk) or the absence (with uncertainty) of probabilistic characteristics of uncontrolled variables. In a noted sense, these terms are used in the mathematical theory of the study of operations, where they distinguish the tasks of decision-making at risk and, accordingly, in conditions of uncertainty. If it is possible to qualitatively and quantify the degree of likelihood of a particular option, then it will be a risk situation.
The situation of risk is a type of uncertainty when the event occurs is likely and can be determined.
That is, in the risk situation, it is objectively the opportunity to assess the likelihood of events that arise as a result of joint activities of partners in the production, countertility of competitors or opponents, the influence of the natural environment on the development of the economy, the introduction of science achievements, the transition to a new level of technology, etc.
For risk about howl situation is characteristic:
-availability of uncertainty (random nature of an event that determines which experienced outcomes is being implemented in practice);
-availability of alternative solutions;
-known or you can determine the probabilities of outcomes and expected results;
-probability of losses;
-probability of additional profit.
In a market economy, the risk is the key moment of entrepreneurship. The problem of risk and profits is one of the key in economic activity, in particular in the management of production and finance.
In this context, it is appropriate to recall that in the explanatory dictionary of V. Dal "Risk" means "to go to the random, on an incorrect matter, I am prompting, to dare, to go for anything, to do something without a sure calculation, to undergo chance, to act boldly, enterprising, hoping for luck". "The risk" means "courage, courage, determination, enterprise, action on Avos, Mind."
In the dictionary of the Russian language. Ozhegova "RISK" Definitely "Danger, the possibility of danger" or as "Action Mind in the hope of happy outcome."
We note an interesting paradox. The expressions of the type have long been known: "Who does not risk, he does not win," "Risk is a noble thing", "there is no business without risk", etc. It became the opinion that "no risk of serious undertakings does not happen" and "big risk - Big Benefit, "etc. At the same time, the expression" risky step ", the" risky event "contain an explicit shade of disapproval. Recommendations and instructions "avoid risk" are widely popular, "to reduce the risk to a minimum."
Thus, the "risk" is determined, on the one hand, as "the danger of something", on the other hand, as "the action of the Mind, requiring courage, determination, enterprise, in the hope of a happy outcome."
An entrepreneur who knows how to risk in time, often turns out to be rewarded. The risk of entrepreneurial activity is naturally associated with management, with all its functions - planning, organization, operational management, the use of personnel, economic control. When these functions are associated with a certain risk measure and requires the creation of an adaptive management system to it. That is, special risk management, which is based on the knowledge of the economic essence of risk, the development and implementation of the strategy of attitudes towards it in business activities. In the conditions of market relationships of accounting and risk assessment, it acquires independent and applied importance as an important part of the theory and management practices. Most managerial solutions are accepted under risk.
The risk is activities associated with overcoming uncertainty in the situation of inevitable choice, in the process of which it is possible to quantitatively and qualitatively assess the likelihood of achieving the intended result, failure and rejection from the goal.
Quantitative assessment of the degree of risk, as well as the possibility of building confidence intervals in a well-known probability, makes it possible to influence the economic process in question in order to increase profits and reducing risk.
To understand the nature of entrepreneurial risk, risk and profits have a fundamental importance. The entrepreneur shows the willingness to take risk in uncertainty, because along with the risk of losses there is an opportunity for additional income. Although it is clear that the receipt of the profit of the entrepreneur is not guaranteed, the remuneration for the time spent, effort and ability, and losses, and losses.
You can choose a solution containing less risk, but the profit will be less and less. And at the highest risk, the profit has the highest value.
Risk, the entrepreneur receives a chance to get super-profile and at the same time gets the opportunity to be at a loss. The desire to "earn" contradicts the goals of "security". Revenues are higher than usual, the average norms are achieved, as a rule, as a result of risky actions. In economic theory and practice, it is proved that a well-known risk share is a prerequisite for obtaining income.
Along with this, there is an inverse relationship between the level of risk and liquidity.
The higher the level of liquidity (company assets, etc.), the lower the level of risk.
The high profitability of assets can be achieved thanks to minimizing reserves, which is fraught with a breakdown of operational processes and means risk of liquidity. And excessive stocks inevitably threaten the turnover and profitability of assets.
Risk classification criteria
Qualifying risk system includes groups, categories, types, subspecies and varieties of risks.
According to the nature of the consequences, that is, depending on the possible result (risk aboutof the events) risks can be divided into two big groups: Clean risks and speculative risks.
Ø Clean risksmean the possibility of obtaining a negative or zero result. Feature of pure risks (they are sometimes called statistical or simple) lies in the fact that they almost always carry losses for business activities. Their reasons may be natural disasters, accidents, the disease of the heads of firms, etc.
Ø Speculative risks It is expressed in the possibility of receiving both a positive and negative result. The feature of speculative risks, which are also called dynamic or commercial, is that they carry either losses or additional profits for the entrepreneur. And the reasons may be changes in currency exchange rates, changing market conditions, changing investment conditions, etc.
On the sphere of occurrence, which is based on areas of activity, distinguish the following types of risks: Production risk, commercial risk, financial risk.
Production risk - This is the risk associated with the non-fulfillment of its plans and obligations for the production of products, goods and services, other types of industrial activities, as a result of the impact of both the external environment and internal factors.
Commercial risk - This is a risk of loss in the process of financial and economic activities. The reasons for commercial risk can be a decrease in sales volumes, unforesestrating the volume of procurement, increasing the purchase price of the goods, increasing the costs of circulation, loss of goods in the process of circulation, etc.
Financial risk - This is a risk associated with the impossibility of fulfilling its financial obligations. Financial risk needs can be a change in the purchasing power of money, the failure of payments, a change in exchange rates, and the like.
Depending on the main reason for the occurrence of risks, they are divided into the following categories: Natural and natural risks, environmental risks, political risks, transport risks, commercial risks.
Naturally natural risks These are risks associated with the manifestation of the natural forces of nature: earthquake, flood, hurricane, tsunami, fire, epidemic, etc.
Environmental risks - These are risks associated with environmental pollution.
Environmental pollution is classified as follows: Natural environmental pollution is caused by natural phenomena, usually with disasters (floods, volcanic eruptions, selene streams); Anthropogenic pollution arise as a result of people's activities.
Environmental risk may arise in the process of construction and operation of the facility and be an integral part of industrial risk.
Political risks - These are the risks associated with the political situation in the country and the activities of the state. Political risks arise in violation of the conditions of production and trading process, directly independent of the economic entity.
Political risks include:
u.the impossibility of exercising economic activities due to hostilities, revolution, exacerbation of the internal political situation in the country, nationalization, confiscation of goods and enterprises, the introduction of the embargo, due to the refusal of the new government to fulfill the obligations adopted by the predecessors, etc.;
u.the introduction of a delay (moratorium) for external payments for a certain period due to the occurrence of emergency circumstances (strike, war, etc.);
u.unfavorable change in tax legislation;
u.ban or restriction of the conversion of the national currency in the payment currency.
Transport risks - These are the risks associated with transportation of goods by transport: automotive, sea, river, rail, air transport, etc.
Commercial risks mean the uncertainty of the results from this commercial transaction.
By structural feature Commercial risks are divided into property, industrial, trade, financial.
è Property risks - These are the risks associated with the probability of loss of property of the entrepreneur due to theft, negligence, overvoltage of technical and technological systems, etc.
Property risk is the likelihood of losing a part of its property, its damage and income income in the process of carrying out production and financial activities.
A group of property risks can be divided into the following subspecies:
Risk of loss of property as a result of natural disasters (fires, floods, earthquakes, hurricanes, etc.);
The risk of loss of property due to the actions of the attackers (theft, sabotage);
Risk of loss of property as a result of emergency situations in production;
Risk of loss or damage to property during transportation;
The risk of alienation of property due to the action of local authorities or other owners.
In addition, the risk of loss of any particular type of property, such as computing equipment or individual types of raw materials, materials and components, is likely for a particular manufacturing company.
It is possible to reduce the level of listed risks through the insurance of certain types of property, as well as through the establishment of strict property responsibility in the enterprise, ensuring the organization of the protection of the company, the development and implementation of organizational and technical, economic and other measures to prevent risks or their minimization.
è Production risks - These are the risks associated with a loss of the production stop due to the impact of various factors, and above all with the death or damage to the main and current funds (equipment, raw materials, transport, etc.), as well as risks associated with the introduction of new techniques in the production and technology.
è Trade risks-Risks associated with a loss due to delay of payments, refreading due to the period of transportation of goods, non-delivery of goods, etc.
è Financial risks associated with the probability of loss of financial resources (i.e. cash).
Financial risks are divided into two kinds: risks associated with the purchasing power of the Dellega Risks associated with the investment of capital (investment risks).
The risks associated with the purchasing power of money include the following risk varieties: Inflation and deflation risks, currency risks, liquidity risks.
Inflationary risk - This is the risk that when increasing inflation-based money incomes are depreciated from the point of view of real purchasing power faster than growing. In such conditions, the entrepreneur carries real losses.
Deflation risk - This is the risk that with the growth of deflations there is a fall in price levels, deterioration of economic conditions of entrepreneurship and revenue reduction.
Currency risks There are a danger of currency losses associated with a change in the course of one foreign currency in relation to the other, when conducting foreign economic, credit and other currency transactions.
Risks of liquidity - These are risks associated with the possibility of losses in the implementation of securities or other goods due to changes in the assessment of their quality and consumer value.
Currency risk includes three types of risks: Economic risk, risk of translation, risk of transactions.
è Economic risk For an entrepreneurial company, it is that the cost of its assets and liabilities may vary in a large or smaller side (in national avatar) due to future changes in the exchange rate. It also applies to investors, the foreign investments of which are shares or debt obligations - bring revenue in foreign currency.
è Risk of translation has accounting nature and is associated with differences in the accounting of assets and liabilities of the company in foreign currency. If there is a drop in the course
è foreign currency in which the assets of the company are expressed, the cost of these assets is reduced. It should be borne in mind that the risk of translation is an accounting effect, but little or does not reflect the economic risk of the transaction.
è More important savoibility of view is risk of transactionwhich considers the impact of changes in the exchange rate for the future flow of payments, and consequently, on the future profitability of the entrepreneurial company as a whole.
è Risk of transactions- This is the likelihood of cash currency losses on specific operations in foreign currency. This risk arises due to the uncertainty of the cost in the national currency of the foreign currency in the future. This type of risk exists in the conclusion of trading contracts and when receiving or providing loans. It consists in the possibility of changing the magnitude of income or payments when recalculating in national currency.
In addition, the currency risk for the importer and the risk for exporter should be distinguished.
Risk of transaction for exporter - This is the fall of the foreign currency course from the moment of receipt or confirmation of the order before receiving the payment and during the negotiations.
Risk of Transactions for Importer - This is an increase in the course of the currency in the period of time between the date of the order confirmation and the day of payment.
Thus, when concluding contracts it is necessary to take into account possible changes in exchange rates.
Investment risks include the following subspecies risks: Risk of missed benefits, risk of reducing returns, risk of direct financial losses.
Risk of missed benefit - This is the risk of an indirect (side) financial damage (incomplete profit) as a result of the non-emergency of any event (for example, insurance, hedging, investment, etc.).
Risk of reducing returns It may arise as a result of a decrease in the amount of interest and dividends on portfolio investments, deposits and loans. The risk of reducing returns includes the following varieties: interest risks and credit risks.
Risks of direct financial losses include the following varieties: stock risk, selective risk, risk of bankruptcy, as well as credit risk.
u.Stock risk- This is the danger of losses from stock transactions.
u.Selective risk - This is the risk of incorrect selection of types of capital investment, type of securities to invest compared with other types of securities in the formation of an investment portfolio.
u.Risk of bankruptcy It is an idea as a result of improper selection of capital investment, full loss by an entrepreneur of equity capital and the inability to pay for its obligations.
From the point of view of duration in time, entrepreneurial risks can be divided into short-term and permanent.
For short-term belonging risks, threatening an entrepreneur for a known period of time (for example, a transport risk, when losses may occur during shipping, or the risk of non-payment on a specific transaction).
To constant risks Those who are continuously threatened with entrepreneurial activities in this geographic area or in a certain sector of the economy (for example, the risk of non-payment in the country with an imperfect legal system or risk of destruction of buildings by Vuraison with an increased seismic hazard).
Since the main task of the entrepreneur is to risk procuringly, without moving the face for which the bankruptcy of the firm should be allocated permissible, critical and catastrophic risks.
Permissible risk - This is a threat of full loss of profits from the implementation of a project or from business activities in general. In this case, losses are possible, but their size is less than the expected entrepreneurial
arrived. Thus, this type of entrepreneurial activity or a specific deal, despite the likelihood of risk, retain their economic feasibility.
The following degree of risk is more dangerous in comparison with permissible - critical risk. Critical risk It is associated with the danger of losses in the amount of the costs of the implementation of this type of entrepreneurial activity or a separate transaction.
Wherein critical risk of first degree associated with the threat of obtaining zero income, but when reimbursed by the entrepreneur of material costs.
Critical risk of a second degree associated with the possibility of losses in the amount of complete
costs as a result of the implementation of this entrepreneurial activity, that is, the loss of the intended revenue and the entrepreneur has to reimburse the costs at its own expense.
Under catastrophic means risk which is characterized by a danger threatening losses in size equal to or exceeding all property status
entrepreneur. As a rule, such a risk leads to the bankruptcy of the company, since in this case it is possible that the loss of all of all invested by the entrepreneur is possible into a certain type of activity or to a specific deal of funds, but also its property. This is characteristic of a situation where the entrepreneurial firm received external loans under the expected profit. If this risk occurs, the entrepreneur has to return loans from personal funds.
2. Mathematical apparatus for modeling and researching Risco situations.
The role of a quantitative assessment of economic risk increases significantly when it is possible to choose from a set of alternative solutions to the optimal solution. The optimal solution provides the greatest probability of the best result at the lowest costs and losses in accordance with the tasks of minimizing and programming risk.
The use of economic and mathematical methods allows you to conduct a qualitative and quantitative analysis of economic phenomena, give a quantitative assessment of the value of risk and market uncertainty and choose the most efficient (optimal) solution.
Mathematical methods and models make it possible to imitate various economic situations and evaluate the consequences when choosing solutions, going around without expensive experiments.
As mathematical means of decision-making in conditions and risk, we will use the methods of mathematical theory of games, the theory of probabilities, mathematical statistics, theory of statistical solutions, mathematical programming.
Many financial transactions (venture investment, purchase of shares, Seling operations, credit operations, etc.) are associated with a rather significant risk. They require to assess the degree of risk and determine its magnitude.
Risk of entrepreneur quantity It is characterized by a subjective assessment of the likely (that is, the expected) value of the maximum and minimum income (loss) from this capital investment. At the same time, the larger the range between the minimum and maximum income (loss) with an equal choice of their preparation, the higher the risk.
The degree of risk is the probability of the occurrence of the case of losses, as well as the size of possible damage from it.
The choice of an acceptable degree of risk depends on the preferences of the head of the enterprise. The leaders of the conservative type are not inclined to innovations, they usually try
get away from any risk. Flexible leaders are striving for more risk decisions, if the risk is voluntary. In a difficult situation, such managers are oriented more risky decisions, if confident in the professionalism of the performers.
The readiness of the manager to take risks is usually formed under the influence of the results of the implementation of past similar solutions adopted in uncertainty.
The losses incurred dictate the choice of cautious politics, and success encourages risk.
Most people prefer malicious options. At the same time, the risk is largely dependent on the value of the capital, which the entrepreneur has. During the assessment of alternative solutions, the manager has to predict possible results. In this decision is made in a certainty, when the manager can accurately appreciate the results of each alternative solution.
The risky relate to those solutions that suggest a result with some kind of probability. This happens in the conditions of uncertainty, when the factors requiring analysis and accounting are very complex, and there is no reliable or sufficient information about them. Then it is impossible to be confident in achieving certain results. Uncertainty is characteristic of many decisions taken in rapidly changing circumstances. This situation is very familiar with Russian entrepreneurs. Determining the choice, the manager considers a new project
in relationship with other options and with already established firms' activities. In order to reduce the risk, it is desirable to choose the production of such goods (services), the demand for which changes in opposite directions, that is, with an increase in demand for one product, demand for another decreases, and vice versa.
Unfortunately, not every risk is reduced by diversification. The fact is that various macroeconomic effects are affected by entrepreneurship, such as waiting for the rise or crisis, the movement of a bank interest rate, etc. The risk due to these processes, the manager cannot reduce through the diversification of production. Adoption of management decisions in the enterprise
it assumes the close linking of all types of risk. However, the most common projections of the manager may not come true due to unexpected and unforeseen circumstances that do not depend on the company itself (economic collisions, sharp changes in the tastes of clients, actions of competitors, strikes, unexpected government solutions).
Therefore, in case of occurrence of adverse events, various possibilities for reducing negative consequences through reserve money, production facilities, raw materials, finished products; Material reorientation plans are being developed.
It is possible to significantly reduce the risk possible at the expense of qualified work on forecasting and intra-profit planning, self-insurance and insurance, transmission of part of the risk to other persons or organizations by hedging, futures transactions, ransom of options.
To quantify the amount of risk, you need to know all possible consequences of some separate action and the probability of the consequences themselves.
The probability means the possibility of obtaining a certain result. Prior to economic tasks, the methods of probability theory are reduced to the determination of the values \u200b\u200bof the probability of events and to choose from possible events of the most preferred event based on the greatest value of the mathematical expectation.
The risk is an action in the hope of a happy outcome according to the principle "lucky - not lucky." The entrepreneur is forced to take risk due to the uncertainty. The greater the uncertainty of the economic situation, the greater the risk.
The uncertainty of the economic situation is due to the following factors: lack of complete information, accident, counteraction.
Lack of complete information About the economic situation and the prospects for its change causes the entrepreneur to seek the opportunity to acquire the missing additional information, and in the absence of such an opportunity, start to operate at random, relying on his experience and intuition.
The uncertainty of the economic situation is largely determined by the accident rate. Accident- this is that in similar conditions there is no way, and therefore it is impossible to foresee and stop it. Mathematics apparatus for the study of random variables gives probability theory. The probability allows you to predict random events. It gives them a quantitative and high-quality characteristic. At the same time, the level of uncertainty and the degree of risk decrease.
The uncertainty of the economic situation is largely determined by the countermeasibility factor. To counteracts relate catastrophes, fires and other natural phenomena, war, revolution, strikes, various conflicts in labor collectives, competition, change in demand, accidents, theft, etc. P.Pertoter in the course of its actions should choose such a strategy that will reduce the degree of counteraction, And therefore, reduce the degree of risk. Mathematical apparatus for choosing a strategy in conflict situations gives the theory of games.
The degree of risk is measured by two criteria:
The average expected value
Validity (variability) of the expected result.
Measure risk
The most common point of view according to which risk measure Some commercial (financial) solution or operation should be considered an average quadratic deviation (positive square root from the dispersion) values \u200b\u200bof the effectiveness of this solution or operation.
Indeed, since the risk is due to the non-determination of the outcome of the decision (operation), then the less the scatter (dispersion) of the solution, the more it is predictable, i.e. Less risk.
If the variation (dispersion) of the result is zero, the risk is completely absent. For example, in the conditions of a stable economy, the operations with state securities are considered to be frantic.
Most often, the indicator of the effectiveness of the financial decision (operation) is profit.
Consider as an illustration selection by a person of one handproof options
investments in risk conditions.
Let there be two projects BUT and IN , In which the specified person can invest.
Project BUT At a certain point, in the future provides a random amount of profit.
Suppose its average expected importance, mathematical expectation, equal t A.from
dispersion . For the project IN These numeric characteristics of profit as a random
values \u200b\u200bare assumed equal, respectivelym B. and . Middle quadratic
deviations are equal, respectivelyS A. and S B..
The following cases are possible:
1) t. A. = m B., S A. < S B., You should choose the project BUT ;
2) t. A. > m B., S A. < S B., Follow the project BUT ;
3) t. A. > m B., S A. = S B., You should choose the project BUT;
4) t. A. > m b, s a\u003e s b ;
5) t. A. < m b, s a< S B .
In the last two cases, the decision to choose a project BUT or IN It depends on the attitude towards the risk of LPR.
In particular, in the case of 4) project BUT Provides a higher average profit,
however, he is more risky. The choice is determined by what optional
the magnitude of the average profit is compensated for the LPR the specified increase in risk.
In case 5) for the project BUT The risk is smaller, but the expected profit is smaller.
The subjective risk attitude is taken into account in the theory of Nimanan-Morgettern.
Consider an example of choosing an investment option.
Example. Let there be two investment projects. The first with a probability of 0.6 makes profit of 15 million rubles, but 5.5 million rubles can be lost with the probability of 0.4. For the second project with a probability of 0.8, it is possible to profit 10 million rubles. and with a probability of 0.2 lose 6 million rubles. What project to choose?
Decision.
Both projects have the same middle profitability, equal to 6.8 million rubles:
0,6*15 + +0,4(-5,5) = 0,8*10 + 0,2(-6) = 6,8.
However, the average quadratic profit deviation for the first project is 10.04 million rubles:
1/2 = 10,04;
and for the second - 6.4 million rubles:
1/2 = 6,4.
Therefore, the second project is more preferable.
Although the average quadratic deviation of the effectiveness of the solution and is used often
as a risk measure, it does not accurately reflect reality. There are situations in which options provide approximately the same average profit and have the same average quadratic deviations of profits, but are not equally risky. Indeed, if at risk to understand the risk of ruin, then the risk should depend on the size of the baseline capital of the LPR or the company it represents. Neumanan-Morgettern theory This circumstance takes into account.
3. Basic concepts of game theory. Classification of games.
The theory of games is the theory of mathematical models of adopting optimal solutions in the face of uncertainty, the opposite interests of various parties, conflict.
Mathematical game theory is an integral part of the study of operations.
Operations research tasks can be classified by the level of information about the situation that the decision makes the decision.
The most simple levels of information about the situation are deterministic (when conditions in which decisions are made are fully known) and stochastic (when
there are many possible options for conditions and their probabilistic distribution).
In these cases, the task is reduced to finding the extremum of the function (or its mathematical expectation) with the specified limitations. Methods for solving such tasks are studied in courses of mathematical programming or optimization methods.
Finally, the third level is uncertain when many possible
options, but without any information about their probabilities. Such a level of information about the situation is the most difficult. This complexity turns out to be fundamental, as the principles of optimal behavior may not be clear.
The theory of games is the theory of mathematical models of decision-making in the face of uncertainty when the decision of the decision ("player") has information only about the many possible situations, in one of which it is in fact, about many decisions (strategies), which he It can accept, and about the quantitative measure of the "win", which he could get by choosing this strategy in this situation.
The establishment of the principles of optimal behavior in the face of uncertainty, proof of the existence of solutions that meet these principles, indicating the algorithms for finding decisions and constitute the content of the game theory.
The uncertainty with which we meet in the theory of games may have different origins. However, as a rule, it is a consequence of conscious activities of another person (persons) defending their interests. In this regard, under the theory of games often understand the theory of mathematical models of adopting optimal solutions in conflict.
Mathematical "theory of games" is the theory of mathematical models of adopting optimal solutions in the context of conflict.
Thus, the models of the game theory can be in principle to describe very diverse phenomena: economic, legal and class conflicts, human interaction with nature, biological struggle for existence, etc.
All such models in the theory of games are customary to call games.
Conflict situation - The situation in which two (or more) sides pursue different purposes, and the results of any action of each parties depend on the actions of partners.
The game - Mathematical model of a conflict situation.
Win(Payment) - the outcome of the conflict.
Zero - A steam game in which the winning of one of the players is equal to the loss of another.
By way In the theory of games, it is called the choice of one of the options provided for by the rules.
Personal moveconscious choice is called one of the players of one of the moves possible in this situation and its implementation.
Random strokeit is called a choice from a number of possibilities, carried out by a player's decision, but by any mechanism of random choice.
Player strategy - A combination of rules determining the choice of its actions at each personal course depending on the current situation.
The goal of the theory of games - Determination of the optimal strategy for each player.
A mathematical description of the game is reduced to the listing of all players acting in it, an instruction for each player of all its strategies, as well as a numerical win, which he will receive after players choose their strategies. As a result, the game becomes a formal object, which is amenable to mathematical analysis.
Games can be classified by various features.
Firstly , infalliac gamesIn which each coalition (many players acting together) consists of only one player. The so-called cooperative theory of inflatational games allows temporary associations of players in the coalition during the game with the subsequent division of the received winnings or decision-making decisions.
Secondly, coalition gamesIn which decision-making players according to the rules of the game are combined into fixed coalitions. Members of one coalition can freely share information and make fully agreed solutions.
On winning games can be divided into antagonistic and games with nonzero sum.
By the nature of the receipt of information - on the game in normal form (Players receive all the information intended for them before the game starts) and dynamic Games (information enters players in the game development process).
By the number of strategies - on end and infinite games.
LITERATURE
Balabanov I.T.Risk-Management.- M.: Finance and Statistics, 1996. - 192 p.: Il.
[ 2 ] . Dubrov A.M., Lagosha B.A., Khrustalev E.Yu. Modeling risky situations in economics and business. Tutorial. - M.: Finance and Statistics, 2000. - 176 p.: Il.
Petrosyan L. A., Zenkevich N.A., Shevkoplyas E.V. Game theory. Textbook. - SPb.: BVH-Petersburg, 2012. -432 C.: IL.
Tepman L.N. Risks in the economy. Tutorial for universities. - M.: Uniti-Dana, 2002. - 380 p.
Shapkin A.S., Shapkin V.A. Risk theory and modeling of risky situations. Textbook. M.: Publishing and trading corporation Dashkov and K 0, 2005. - 880 p.
The book is revealed by the essence of risk management, its organization, strategy, techniques, risk reduction methods, including insurance.
The study guide addresses approaches to accounting for uncertainty and risk factors in economic practice, as well as mathematical models used for these purposes. Situations arising in the conditions of uncertainty and lack of information in making management decisions are analyzed. The content is illustrated by applied tasks with solutions.
The textbook is designed for both the initial and in-depth study of the theory of games. A systematic study of mathematical models of decision-making by several parties in conflict conditions has been carried out. A consistent presentation of the unified theory of static and dynamic games is presented. All basic gaming classes are considered: end and endless antagonistic games, infallonal and cooperative games, multisposed and differential games. To secure the material in each chapter, tasks and exercises of varying degrees of complexity are contained.
The textbook is intended for students, graduate students and teachers of economic universities of Iifaculty, listeners of business schools, managers of enterprises and organizations.
The textbook outlines the essence of uncertainty and risk, classification and factors acting on them; Methods for high-quality and quantifying economic and financial situations in uncertainty and risk are given.
CONTROL QUESTIONS.
1. What is the risk?
2. How do the concepts of "risk" and "uncertainty" differ?
3. What is a "risky situation"?
4. Economic consequences of risky situations. Give examples.
5. Give the definition of economic risk. Give examples of economic risks.
4. Give examples of classifications of economic risks.
6. Describe the connection between the risk and profit of financial transactions.
7. Is the concept of economic risks is connected exclusively with those
risks, the emergence of which leads to money damage?
8. What is the degree of risk?
9. What are the main factors of the uncertainty of the economic situation?
10. What is a measure of risk? How is it measured? Give examples.
11. Word the basic concepts of game theory.
12. Name the recognition of games. Give examples of games.
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Introduction
1.1 Introduction comments
1.4.2 Risk Management System
Chapter 2. Modeling the management of the operating risk of credit institutions
2.1 Mathematical formulation of the problem
2.2 Modeling losses
2.3 Modeling the dependent structures of random variables. Copular functions
2.4 Modeling the incidence of losses
2.5 Stochastic Model Monte Carlo Approximation Random
2.6 Calculation of risk capital values \u200b\u200b66
Chapter 3. Implementation of the operating risk management system
3.1 Development and implementation of an operating risk management system
3.2 Calculation of the magnitude of risk capital
3.3 Evaluation of the economic efficiency and sustainability of the model
Conclusion
List of used literature
Applications
Introduction
mathematical operational risk Economic
Economic and mathematical modeling is located at this stage when there is a high-quality jump. All over the world has accumulated a huge number of diverse models. Whatever the economy we would have taken, there is always a whole range of mathematical, computer, verbal - meaningful models, one way or another, related to it. Hundreds of scientific journals publish the descriptions of new models, or modifications and the development of older.
All of them, although they are called economy models, are actually models of some kind of its area, explain something one. Each of them contributes to the knowledge of the economy. The peculiarity of the process of understanding, the knowledge of the person of complex phenomena is to simplify, refer to the simple image. Therefore, Kohl knowledge is infinite, the creation of models, also, apparently, has no limit.
Within the framework of the mathematical economy, with the help of formal means, the study of complex economic mechanisms is already meeting significant difficulties. Models cease to be so beautiful and completed, as in classical cases, although they consider the most common or most economically informed combinations of simple mechanisms.
From a practical point of view, any, even a very large amount of information in itself has no value. The data in its pure form is not the knowledge that is called "force". Information becomes power when it allows you to foresee the future, i.e. Reply to the main question when choosing a solution: "What will happen if?" To answer this question, except for data, it is necessary to have a real world model.
Where do the models come from and why there are practically no bank management systems? In the banking business, the process of creating adequate models is complicated by two objectively existing factors. The first is that from the point of view of control, the Bank is an extremely complex object consisting of many different subsystems, between which there are a large number of heterogeneous bonds. The activities of the Bank develop out of a number of business processes that significantly depend on the set of external factors: legislative, economic, social, political.
In cybernetics, such objects such as the bank received the name of complex systems, and methods of studying them - methods of system analysis. The most significant results in this area are associated with the study of operations - an approach based on the use of quantitative mathematical methods for evaluating the decisions made. However, the use of quantitative methods is possible only in the case when the researcher has adequate mathematical models, which are just missing in banking activities.
The second factor is manifested in the fact that in banking activities (especially in the conservation of the market) it is impossible to conduct targeted experiments preceding the formation of the hypothesis and allowing it to test it in practice. The accumulation of analysts of personal experience prevents the dynamic change in the situation typical of modern Russia.
Most financial science is related to the analysis of the profitability of investment activities. In addition to measuring the yield, bank analysts also deal with the uncertainty of income generation; With this uncertainty, risk analysis is associated. The invertation of these issues in our practice explains the need to study foreign experience in the aspect of its use in Russia.
The combination of indicators used in assessing the profitability of a banking strategy of indicators, methods and models of settlements is the subject of new, dynamically developing scientific areas - financial mathematics and financial analysis, formed at the junction of modern theory of finance and a number of mathematical disciplines, such as: econometric, probability theory , mathematical statistics, research operations, theory of random processes.
The main goal of banking is to maximize profits; Almost equivalent task is to minimize bank risks. Reducing the rate of profit from banking operations, reducing the client base and reduce revolutions on customer accounts lead to the fact that the ratio between the bank's profit and its operational costs becomes extremely unfavorable. Thus, a situation is created when banks are forced to look for ways to reduce costs and minimizing risks. And this, in turn, causes banks to pay special attention to financial analysis and methods of managing their resources.
The ability to risk intelligently - one of the elements of the culture of entrepreneurship as a whole, and banking activities - especially. In the conditions of the market, each of its participants takes certain rules of business - games and to a certain extent depends on the behavior of partners. One of these rules can be readily readiness to take risk and take into account the possibility of its implementation in its activities.
One of the main types of risks of credit institutions is an operational risk due to the uncertainty of the state and the functioning of their internal and external environment. Losses from the onset of operational risk events can lead to significant direct and indirect losses, ruin of companies and even the death of people. Loud bankruptcy of recent years, including those who have become errors in the organization of the operational risk management system, indicate the scale and insufficient developments of the assessment, prevention and minimization of losses from the onset of events related to operational risks. The lack of representative statistical information, heterogeneous and individual for each credit organization, the operating risk profile makes it impossible to apply the generally accepted methods and models of measurement and management of financial risks used in the theory of risk management, for analyzing and managing operational risk.
The need for capital reservation for operational risk (the inclusion of operational risk into calculating the capital adequacy ratio of H1) has become a reality for Russian commercial banks already in August 2010, as this reflects the strategy for the development of the banking sector and the course of the Central Bank of the Russian Federation to introduce risk-oriented approaches in the credit assessment organizations.
Thus, the tasks of building an effective measurement system, forecasting and minimizing the operational risk arising during the activities of credit institutions determine the relevance of the study.
The purpose of the study is to develop methods and models of integrated management of the operational risk of credit institutions. In accordance with the specified purpose, the following tasks were also solved:
1. To study existing models and methods for analyzing and managing financial risks in relation to the specifics of operational risk.
2. Develop a comprehensive classification of events and operational risk factors, taking into account the specifics of the activities of credit institutions.
3. Develop mathematical tools required for analysis, measurement and management of operational risk, including:
· Put and implement the problem of mathematical modeling of random damages, taking into account the availability of the effect of correlations between them;
· Develop and programmatically implement a stochastic algorithm for modeling a total amount of losses with a given structure of dependencies and calculating the magnitude of the risky capital on their coverage (taking into account the availability of various insurance coverage and risk measures).
4. Develop a programming implementation of modeling the management of the operating risk of a credit institution, to assess the sensitivity of the implemented methods to various perturbations of input parameters.
5. Determine the economic efficiency of the implemented operating risk management model. Develop guidelines for the organization of the operational risk management process in credit institutions.
The object of the graduation research is the operational risks arising during the current activities of credit institutions. The subject of the graduation research is economic and mathematical methods and models of the operational risk management process as an element of the risk management system of a credit institution.
The theoretical and methodological basis of the study was the works of domestic scientists in the field of insurance business, financial and actuarial mathematics, theory of games, theory of probability and mathematical statistics, the theory of extreme values, random processes, numerical methods, risk management.
The scientific novelty of the study is to develop a comprehensive approach to operating risk management based on the synthesis of the following problems of economic and mathematical modeling: an analysis of damages processes, an assessment of the cumulative amount of losses, the calculation of the magnitude of the risky capital on their coverage. The subject of protection is the following provisions and results containing elements of scientific novelty:
1. The task of mathematical modeling of random processes for the occurrence of losses of credit institutions related to operational risk has been solved, which allows to carry out a more accurate estimate of the operational risk, compared with the existing calculation techniques.
2. Probabilistic modeling of the aggregated loss value, taking into account the presence of correlations between them, allowing more accurate to estimate the total amount of losses, reasonably reduce the calculated value of the required risk capital on their coverage.
3. The program implementation of stochastic modeling of random processes (losses) with a predetermined structure of dependencies and the calculation of the amount of capital on their coverage, taking into account the availability of various insurance programs and risk measures. The sensitivity of the developed methods to different perturbations of input parameters was carried out.
4. The economic efficiency of the application of the developed integrated model of operational risk management model in credit institutions is proved compared with existing methods and modeling and operational risk management models (in terms of saving risk capital values).
The first chapter discusses the features of simulation modeling of bank processes, the bank's functioning model, the concept of risk in banking, classification of bank risks and risk management system.
The second chapter was set and solved the problem of mathematical modeling of the processes of the onset of credit institutions related to the operational risk. Mathematical models and: methods of assessment, measurement and prediction of the aggregate value of aggregated losses, calculation and coherent distribution of risky capital, proposed mechanism for supplementing its own data at the expense of mapping information on the loss of external organizations, accountable effect of the temporary structure of money and the presence of a significance threshold values \u200b\u200bof losses. In the third section of the chapter, the main facts of the theory of the Cole, necessary for modeling dependent random processes, are discussed by correlation measures invariant to monotonous transformations. Implemented algorithm for stochastic modeling of random processes with known distribution functions and a predetermined dependence structure, using Gauss Cowles. Using the theory of copul is implemented by an algorithm for generating dependent processes that simulate loss frequencies. Section 2.5 describes the Monte Carlo stochastic model, developed and implemented in the MATLAB package, to assess the probabilistic distributions of the total losses of the credit institution for a general case, using Gaussian and T-Cole Student and the Fourier quick conversion. This model was based on the AMA model, the results of the implementation of which are discussed in the third chapter. Alternatively, the proposed Basel II quantile function VAR for calculating the amount of capital coating, in Section 2.6, the use of coherent risk measures is proposed. The measure is considered (EXPECTED shortfall - es), satisfying the subadtitivity condition, allowing, to obtain more resistant to various extreme distributions of losses value results. The problem of the coherent distribution of risky capital between the directions of activities - and / or departments of the credit institution has been solved and solved. The result obtained is that in terms of the neatomic game theory of games, the principle of coherent distribution of risky capital can be uniquely defined through the vector of AUman-whisper, which always exists and belongs to the game core.
The third chapter has developed the main stages of the introduction and information support of the system of integrated management of the operating risk of the credit institution. The key points of the creation of internal regulations and methodologies governing the operational risk management process to be mandatory in accordance with the requirements of the Central Bank of the Russian Federation and the recommendations of Basel II are given. In addition to calculating the quantitative indicators of operational risk, it is recommended to monitor the qualitative indicators of operational risk, which most characterized by the main activities of the credit institution subject to operational risk. Section 3.1 has developed a comprehensive system of indicators (Cyrus - key risk indicators) for medium-value credit institutions.
As a demonstration of the developed quantitative operational risk management methods in the second part of the third chapter, the simplified implementation of the AMA model was considered on the example of calculating the CAR value for the credit bank of the average value. A comparison of risk capital values \u200b\u200bcalculated on the basis of various approaches and for different risk measures and levels of significance was made. Section 3.3 analyzed the sensitivity of the implemented model at various perturbations of input parameters. The estimated economic effect was evaluated from the implementation of the developed models and methods for managing the operational risk of credit institutions compared to existing approaches.
In conclusion, the main results obtained and studies are formulated.
Chapter 1. Analysis of existing mathematical models of the bank
1.1 Introduction comments
As mentioned above, the main goal of banking activity is to maximize profits; Almost equivalent task is to minimize bank risks. This means that the policy of a commercial bank should be based on a thorough assessment and imitation of various situations, analyzing the set of factors affecting the amount of profits. These factors determine the level of banking risk; The Bank's task is to minimize it.
Bank yield \u003d credit resource yield + investment profitability:
where - the proportion of the go and the type of resources,
DB - bank yield,
KR - credit resources
Central Bank - investment in securities.
Investors acquire assets, such as stocks, bonds or real estate, in order to receive income or from selling them at a higher price, or in the form of dividends, percentage of coupons or rental payments. Lenders are drawn money in the hope of getting income in the form of interest payments with full repayment of the loan by the borrower. Thus, lenders and investors have a common goal - get income or percentage as a result of investment or payables.
Reducing the rate of profit from banking operations, reducing the client base and reduce revolutions on customer accounts lead to the fact that the ratio between the bank's profit and its operational costs becomes extremely unfavorable. Thus, a situation is created when banks are forced to look for ways to reduce costs and minimizing risks. And this, in turn, makes Russian banks pay special attention to financial analysis and methods of managing their resources.
The most important rule on which decision-making strategies are based in business risk conditions:
Risk and yields are changed in one direction: the higher the yield, the usually higher risk of operation.
If banks want to attract additional funds, they must demonstrate to their customers that they fully take into account the ratio of "risk-income".
It is this thesis that is currently used in a number of largest foreign banks.
Under the conditions of the planned economy, an understanding of risk and uncertainty was expelled as essential components of socio-economic development, as the most important scientific categories requiring comprehensive study. The formation of market relations and economic mechanisms in Russia led to the return of the concept of risk to the theory and practice of managing economic objects of all levels and forms of ownership.
Much attention is paid to modeling bank processes abroad. The idea of \u200b\u200bmanaging a banking portfolio or end-to-end balance of the balance is originated in the modern portfolio theory (Portfolio Theory) developed in the mid-50s. The first attempts to apply the current portfolio theory to the banking were carried out in the form of linear and quadratic models of mathematical programming. Although these models were slightly slim in a classical understanding, they were too limited and difficult for practical use. Their main value is the possibility of penetration into full balance management. It is useful as a help to understand how to manage the banking portfolio and risk.
The concept of portfolio management is illustrated using a linear programming model. Of course, to carry reality to a two-dimensional task, I had to seriously easily simplify the task.
Imagine the balance of the bank in the following simplified form:
where the Central Bank is securities,
Cr - loans,
DV - demand deposits,
SD - Urgent deposits,
K - Capital. Egorova N.E., Spelov A.S.Predprinities and banks: interaction, economic analysis and modeling. - M.; Case, 2002. P.61.
Profit on securities and profit on loans we denote the Central Bank and P cr respectively. The costs of attracting deposits and on capital are assumed to be zero. Hence the income or profit of the Bank PR set by the equation:
We also give the classification of analytical banking programs:
1. Level in the organizational structure of the bank: top management, the average level, performers.
2. Type of the analyzed operation: Credit operations, securities, currency transactions, other operations.
3. Type of task solved: monitoring, analysis, optimization, modeling, forecast, planning, control.
4. Temporary lag analysis: current moment, short-term assessments, medium-term assessments, long-term assessments.
1.2 Features of imitation modeling of bank processes
The need to use imitation modeling is due primarily to the peculiarities of the Russian market. A distinctive feature of the Russian financial market is its "subjectivity", extreme dependence on non-economic factors and, as a result, a high degree of uncertainty, which makes it difficult to adopt informed financial solutions.
This uncertainty creates:
1. The instability of the external environment of Russian banks, the lack of clearly established rules and procedures for organizing various sectors of the financial market (institutional aspect);
2. The absence of a fairly developed apparatus for predicting the macroeconomic situation under uncertain conditions and analyzing the multiplicity of factors (instrumental aspect);
3. The impossibility of accounting and formalizing all connections to build an economic and mathematical model adequately reflecting the structure of the financial market (cognitive aspect);
4. Inaccessibility of reliable information - the absence of a single information space "Bank - Client - Financial Market - State" (information aspect);
5. Inadequate reflection of the real financial state of the Bank in the accounting statements (balance, etc.) and, thereby, is the lack of financial transparency in the bank (accounting aspect). The use of traditional means of supporting management solutions and forecasting under these conditions is difficult, and the more value is the possibility of using the simulation method. Emelyanov A.A. Simulation modeling in risk management. - St. Petersburg: St. Petersburg Engineering and Economic Academy, 2000. P.132.
Many modern software products are designed specifically to predict the situation in the financial market. This includes funds for technical analysis of the stock market, expert systems and statistical packages. These products are mainly intended to mainly make decisions on the state debt market.
The practice of applying by banks and investment companies of funds to trade in the securities market shows that the forecast is far from always reliable even in terms of the trend. One of the reasons for this is a limited period of statistical observations.
In turn, simulation modeling is a tool with which it is possible to cover all areas of the Bank's activities: credit and deposit, stock, work with currency assets. The simulation model of the bank (IMB) does not predict the behavior of the market. Her task is to account for the maximum possible number of financial factors of the external environment (foreign exchange market, the securities market, interbank loans, etc.) to support the adoption of financial decisions at the level of the head of the Bank, the Treasury, the Committee for Asset Management and Liabilities.
In this sense, the IMB in its functions closely adjoins the developed automated banking systems (ABS) of Western development, which are used by major international trading banks.
Modeling the processes in the bank allows you to imitate the registration of bank transactions and take into account the information that the transaction contains. The application of this construction ideology is quite acquitted not only in terms of simulating real financial flows in a bank, but also from the point of view of the practical applicability of modeling results in the activities of the Bank's financial manager.
Indeed, the balance sheet turns out to be the secondary result of the decisions taken. Both in practice and in the IMB manager, accepting this or that decision on the transaction, assesses its risks and consequences for the Bank is not simultaneously, but throughout the life cycle of the transaction.
Simulation models - an integral part of modern bank management. Asset and liabilities management, planning large-scale operations requires reliable analytical techniques.
Simulation systems are widely used for analysis, forecasting and studying a variety of processes in various areas of the economy, industry, scientific research as a purely theoretical and practical direction.
The use of such systems is most efficient and justified for promising forecasting and in situations where the practical experiment is impossible or difficult. Simulation modeling is an information technology that works with a simulation model and allowing its parameters (consequently, efficiency) at an expedited scale of time.
The simulation model is software that allows you to imitate the activities of a complex object. Sometimes imitated objects can be so complicated, and have such a large number of parameters that the creation of a simulation model in the standard high-level programming language may require too much time to justify the results. Emelyanov A.A. Simulation modeling in risk management. - St. Petersburg: St. Petersburg Engineering and Economic Academy, 2000. p.24
There are many tasks and situations requiring the use of imitation technologies. These include modeling of bank work scenarios, "Check" of certain solutions, an analysis of alternative strategies and much more. A qualified specialist is able to bring tens of typical and private tasks requiring analytical techniques. These include the classic tasks of bank planning, and the task of "home" origin, for example, coordination of charts of obligations and revenues. Imitation models allow you to do both exemplary assessments and express audit of decision-made solutions and detailed numerical forecasts and calculations. A quick analysis of the situation on the basis of a compact model of medium complexity is a valuable opportunity for any bank manager.
Imitation models make it possible to linet into a single whole activity of all divisions of the bank. On this basis, it becomes possible to effectively organize the entire system of operational and strategic planning of a commercial bank. Thanks to the use of streaming approaches, information on the activities of the Bank and its services acquires a compressed and easily readable form. It is amenable to quantitative and high-quality (meaningful) analysis. The simulation model on the basis of one of the expert packages is a reliable reference point for the management of the bank. The flow "picture" of the Bank's activities significantly facilitates both operational management and prospective planning of the Bank's work.
Imitation models may be based on an expert complex of a commercial bank. In this case, the simulation model created on the basis of one of the expert packages is associated with data exchange channels with other specialized software packages and database spreadsheets. Such a complex can act in real time. In terms of its capabilities, it approaches great expensive bank management automation systems.
Optimization models, including multicracterities, have a common property - aim is known to achieve which it often has to deal with complex systems, where it is not so much about solving optimization tasks, how much about research and prediction of states depending on the elected management strategies. And here we are faced with the difficulties of implementing the former plan. They are as follows:
1. The complex system contains many bonds between the elements;
2. The real system is influenced by random factors, the accounting of which is impossible analytically;
3. The ability to match the original with the model exists only at the beginning, and after applying the mathematical apparatus, since intermediate results may not have analogues in the real system. Emelyanov A.A. Simulation modeling in risk management. -Spb: St. Petersburg Engineering and Economic Academy, 2000. S.58.
Due to the various difficulties arising from the study of complex systems, the practice demanded a more flexible method, and it appeared - simulation modeling (Simulation Modeling).
Usually under the simulation model is a complex of computer programs that describe the functioning of individual blocks of systems and rules of interaction between them. The use of random variables makes it necessary to multiple experiments with the simulation system (on a computer) and the subsequent statistical analysis of the results obtained. A very common example of using simulation models is the solution of the problem of mass maintenance by Monte Carlo.
Thus, work with the simulation system is an experiment carried out on a computer. What are the advantages?
1. Greater proximity to the real system than in mathematical models;
2. The block principle makes it possible to verify each unit before turning on it into the general system;
3. Using dependencies of a more complex nature not described by simple mathematical ratios.
Listed advantages determine the shortcomings:
1. Build a simulation model longer, harder and more expensive;
2. To work with the simulation system, it is necessary to have a suitable computer;
3. The interaction of the user and the simulation model (interface) must not be too complex, convenient and well known;
4. Building a simulation model requires a deeper study of the actual process than mathematical modeling. Emelyanov A.A. Simulation modeling in risk management. -PB: St. Petersburg Engineering and Economic Academy, 2000. P.79.
The question arises: can imitation modeling replace optimization methods? No, but conveniently complements them. The simulation model is a program that implements some algorithm to optimize the control overcoming the optimization task.
So, neither a computer, nor a mathematical model, nor the algorithm for its study, can solve a rather complicated task. But together they represent the power that allows you to learn the world around, manage it in the interests of a person.
Given the set of tasks facing banking analysts, this system should provide:
1. Calculation of indicators of the current and future financial states of the Bank;
2. The forecast of the state of individual financial transactions and the balance of the Bank as a whole;
3. Assessing the attractiveness of individual financial transactions;
4. Synthesis (formation) of management solutions;
5. Evaluation of the effectiveness of the adopted management decision;
6. Evaluation of the completeness and disadvantage of sets of indicators of the financial condition of the bank.
Performing any of the listed functions requires the modeling of the Bank's financial activities.
1.3 Bank functioning model
A set of methods used for analyzing and modeling banking is also wide and diverse. Throughout the evolution of the mathematical theory of banks, methods of mathematical statistics, the theory of optimal control, theory of random processes, game theory, theory of research of operations, etc. were used. It should be remembered that the bank is a complex object that requires an integrated approach. Create an integrated model of the Bank simultaneously covering liquidity management, the formation of a portfolio of assets, the formation of credit and depositive policies, etc., will be extremely difficult, therefore we will describe the functioning of the bank quite aggregated.
Consider the work of the bank at a sufficiently large time interval.
Let the Bank receives revenues in the form of payment of its services for carrying out the calculations of warranty operations, brokerage services (or other income independent assets from the portfolio) - and revenues from the portfolio of banking assets acquired on the free funds of securities.
Revenues from acquired securities are addressed from interest on the papers - and the payment of invested funds in redemption or sale of securities -
(in the event of a promotion
where is the interest rate on acquired securities
average time to repay securities purchased by the Bank. Kumaev V.A. Mathematical economy. - M.: Uniti, 1998. p.68.
The bank comes, also borrowed funds from placing their securities at speed - W. We will assume that securities issued by the bank are initially placed, and they are repaid at par, and interest income on them is determined on the basis of the situation in the financial market at the time of the issue of emissions .
The Bank's received income is primarily aimed at paying expenses to attract funds, which consist of interest payments on placed securities - and payments of the main amounts of borrowed funds -
where is the interest rate on placed securities
Average time to repay securities issued by the bank.
In addition, the Bank bears the costs independent of its liabilities -, where:
Consumer price index,
To pay for the rental of premises, for payment of telecommunication costs, as well as other expenses that do not depend on the volume of attracted funds (liabilities).
Then the bank pays the necessary taxes. The remaining funds of the Bank uses to invest in its own infrastructure (internal investments) - and for dividend payments -.
The fact that some expenses Bank must pay from its net profit can be taken into account by increasing amounts of expenses by dividing on (1-rate of taxation). There are also taxes levied with income amounts regardless of the costs associated with obtaining this income, such as taxes on road users. Such taxes can be taken into account in advance multiplying the amount of income on (1-rate of taxation). Such methods can also be taken into account other features determined by tax deductions, so we will not consider the problems below the problems associated with taxation and tax breaks on some securities, such as state. Note that expenses are paid by the bank in a certain order. First of all, the Bank is obliged to repay the issued previous securities and pay interest on them, then it pays expenses that do not depend on the volume of liabilities, taxes, and only after that can pay dividends.
If the bank has free money, he sends them to the purchase of securities (external investment) at speeds -. In the event of a lack of funds, securities in the bank's portfolio can be sold, then has a negative sign. Artyukhov St., Basyukina O.A., Korolev V.Yu., Kudryavtsev A.A. The optimal pricing model based on risk processes with random premiums. // Systems and computer science. Special issue. - M.: Ipian, 2005. C.102
The amount of money, securities acquired by the Bank and securities posted by the Bank vary with time as follows:
where - the consumption of money for the purchase of securities (the arrival of money from their sale), and is a fairly small time constant, which characterizes the quality of the bank's assets, in terms of liquidity. If the bank places all its assets on any one segment of the financial market, then it has a value that characterizes the degree of development of this segment. In general, it turns out as weighted average in terms of assets from the values \u200b\u200bcharacterizing the degree of development of each of the "financial market segments on which assets are placed. Since we do not consider the problem of forming assets in this work, but is assumed to be given values.
The maximum amount of funds that the bank can attract by placing its own securities is limited and depends mainly on the volume of own capital of the bank, the structure of its balance, the quality of the Bank's investment portfolio and on other less important indicators of his work. We assume that
where is the bank's reliability ratio,
The volume of bank's own funds.
Accommodation by the bank of own securities, to attract borrowed funds, also takes place at some limited speed, so
where is the time constant characterizing the degree of development of the market of other papers emitted by the Bank. It depends on how developed the Bank's infrastructure is how large the number of market participants with which the Bank has been cooperating with.
We introduce a variable - the value of the portfolio of the acquired securities. Then equations (1.4) - (1.6) will take a look
We introduce dimensionless management: through which the speed of spending money for the purchase of securities and the rate of receipt of money from the placement of securities of the Bank are expressed as follows:
The value corresponds to the buying / sale of third-party securities as quickly as far as the efficiency of the securities market allows. The value corresponds to the most rapid attraction of borrowed funds by the Bank, and to the total failure to attract funds.
The main line of money - which makes them essentially different from the securities acquired by the Bank, even state - this is the possibility of their use to pay for the current expenses of the bank. The payment flow cannot be implemented if there is no sufficient stock of money, therefore, the rate of payments is limited and depends on the amount of money:
where - the characteristic time of receipt of the cash bank (payments). Limitations of this species are called liquidity limitations.
Payments conducted by the Bank must be divided into two groups:
Obligatory payments. These include payments on the repayment of securities issued by the Bank -, the payment of interest on securities - expenses that do not depend on the volume of liabilities - in practice the bank can delay compulsory payments, but this will lead to serious financial losses, and with a long delay to recognize it insolvent and as a result of liquidation. We will assume that the delay of mandatory payments is completely excluded, i.e., the Bank requires constant preservation of liquidity.
Optional payments. Conducting these payments depends on the management and owners of the bank. These include internal investments - and dividends - RS 2.
To save the liquidity bank, it is necessary to:
for all (1.11)
Thus, we obtain the first phase restriction for our task - condition (1.11).
Note that from this inequality, under the condition of non-negativity, in particular, it follows that for all
Conducting optional payments is also limited by speed:
According to this inequality, you can enter dimensionless management so:
Because the volume of internal investment depends on the bank's maintenance in the financial services market, it is possible to include expenses, in some sense, to the obligatory, at least for the most part of the planning site. (After reaching the planning horizon, the T Bank can be eliminated by its owners). Since dividend payments cannot be negative, we get another phase restriction:
for all (1.13)
Thus, we came to the fact that internal investments are really mandatory in the sense of restriction (1.13).
We will assume that in the planning site, the Bank does not receive "extensions", i.e., the profits are large compared to their own capital, independent of assets. Consequently, the maximum amount of money that it can attract and gets in the form of profit is limited to some constant i. For all, this is the third phase restriction (1.14).
The assessment can be obtained based on the maximum amount of borrowing the ratio of interest rates on attracting and placing funds, the volume of income that do not depend on the amount of assets.
Note that most of the planning site should be close to zero, as the bank is not profitable to hold cash non-income cash, because in the financial market there are always absolutely reliable state securities that bring fixed positive income.
The absence of "extensions" means also limitations on the planning area of \u200b\u200bthe relative rate of growth rate of securities:
We will describe the interests of the bank (its owners) to the desire to maximize the discounted utility of future dividend payments at a sufficiently large time interval, we will assume that the usefulness obtained from the immediate payment seems more than the usefulness of the amount of funds, taking into account inflation, but through time . The coefficient is called the coefficient of discounting the utility of dividend payments. Then the maximized functionality is recorded as follows:
where is the function of the usefulness of dividend payments.
When the use of consumption is played, it is usually required that it is continuous, monotonous, concave and limited from above, and also overlaps the last condition guarantees the positivity of the current consumption at each time. Since dividends may not be paid, we will not require the fulfillment of the condition, believing that the utility function has a low disgust for zero consumption.
If the usefulness function has a constant relative disgust to risk on Errow Pratt: it can be shown that it can be recorded in the form:
To get rid of high disgust for zero consumption Consider a somewhat modified utility function
In this case, relative disgust for risk will depend on the volume of consumption :. Based on (1.9) and (1.11) we get
Consider instead of function (1.13) direct passing through points
Since the function (1.17) will be negative for any volume of dividends, i.e., it is limited from above zero, as well as continuous and monotonne for any. This utility function has zero relative disgust to risk along Errow Pratt, and varying parameter can be changed only with the nominal value of dividend payments. This fact emphasizes differences in relation to risk between private consumer and commercial organization. On the one hand, the latter does not have disgust to risk, as it may exist indefinitely for a long time, compared with the life expectancy of a person, and is not susceptible to hazards as living beings. On the other hand, a private consumer is a spectacular amount of 2 * rubles receives satisfaction from the first 3 rubles spent greater than that of subsequent, which determines the bentness of the use of consumption for individuals. We will assume that the doubling of dividend payments leads to the doubling of their utility for recipients, which are quite large and their number includes both individuals and legal entities. This determines the linearity of the usefulness of dividend payments. In the future, we will use the utility function (1.17).
Thus, we get the task of optimal control in continuous time
In addition, there is a boundary condition with which means that the bank is obliged to repay its debt to the end of the planned period.
Here - phase variables, - management. Here, the predicted values \u200b\u200bof the corresponding variables are considered to be given non-negative functions of time, are constant with dimension of time.
Note, if at a certain point adds to zero, then according to equation (1.21), i.e. The solution at this point does not decrease. Accordingly, if at some point reaches the value, then that is, the solution does not increase. Thus, under management, from equation (1.21), conditions and continuity, we obtain that, on the entire segment, the volume at the par value of the bank's placed securities of the Bank is non-negative, i.e., and does not exceed a permissible maximum - for all (generally speaking ).
Then, from the condition and conditions of non-negativity of the specified functions, as well as non-negativity, we get that for all. Assuming continuity, you can show using equation (1.20) as for all. Next, we will be | to believe that continuously, and piecewise-continuous on.
Since and from equation (1.20) it follows that. Using this inequality, it is easy to show the existence of such that for everyone.
We will not, as assumed earlier, to consider how it is formed by a portfolio of securities purchased by the Bank, depending on the reliability, profitability and liquidity of the latter, as well as the preferences of the Bank's management. All bank assets will be presented in aggregated form - one variable.
From the foregoing, it is clear that the Bank's credit and deposit policy, determined in the management model and, is inextricably linked with the policy of conducting dividend payments set by the Office, so further we will explore them together.
For the convenience of further study of the work, we drink separately designations:
The amount of free cash banks - cash signs at the bank's office, or the money for Corr. Bank accounts in the settlement centers of the Central Bank of the Russian Federation, as well as on the cor. accounts in other banks
The volume of acquired securities at par
Volume of placed securities at par
Income independent of assets (commission for settlement and cash services, conducting warranty operations, brokerage services, etc.)
Horizon planning
The volume of own funds of the bank (capital)
Reliability coefficient of bank
The rate of spending by the Bank of funds for the content of the control apparatus, payment of the rental of the room, etc. or expenses independent of bank liabilities in prices at the initial time
The rate of reinvestment in the infrastructure of the bank (internal investment) at the prices at the initial time
The rate of dividend payments in prices at the initial time
Current Market Securities Course Acquired by the Bank
Market value of the bank securities portfolio
Time constant characterizing the degree of development of the financial market, taking into account the distribution of bank assets for its sectors
Time constant characterizing the degree of development of the securities market issued by the Bank
Nominal index portfolio of securities purchased by the Bank. For each acquired security, the nominal rate is given to the annual, taking into account the reinvestment, is then calculated by the annual rate portfolio on all securities in the Bank's portfolio. The index is defined as LN (1 + "Weighted average annual bid")
Effective Independent Securities Portfolio Growth Index
The growth index of aggregate debt on placed securities. For each placed valuable paper, the nominal rate is given to the annual, taking into account the refinancing of debt due to new papers, is then calculated by the annual rate weighted average for all placed securities. The index is defined as ln (1 + + "Weighted average annual bid")
The average redemption time of securities acquired by the Bank is the average redemption time of securities issued by the Bank - the consumer price index
Inflation index
Characteristic time of payments (cash receipt)
The speed of circulation of money in the banking system
Speed \u200b\u200brate of money for the purchase of securities of third-party issuers, or the receipt of money from their sale
The rate of money from the placement of securities of the bank
Discount Discount Coefficient of Dividend Payments
Relative Risk Disgusted by Herrow Prattu, the parameter used when specifying the utility function of dividend payments
M * - the maximum amount of money that can belong to the jar
Dividend payout utility function, continuous, monotonous
Bank Dividend Payments Management
Management of placement of free cash banks
Management attraction to the cash bank.
1.4 Risk concept in banking
The risk is the possible danger of any unfavorable outcome.
In market conditions, each of its participants takes certain rules of the game and to a certain extent depends on the behavior of partners. One of these rules can be readily readiness to take risk and take into account the possibility of its implementation in its activities.
Under risk it is customary to understand the likelihood, or rather threatening the loss by the bank of part of its resources, lack of income or the emergence of additional expenses as a result of the implementation of certain financial transactions. Slitz O. Operational risk management in a commercial bank. Accounting and banks, 2006 - №6. P.112
In the context of the crisis, the problem of professional bank risk management, the operational accounting of risk factors are primarily acquired for the participants of the financial market, and especially for commercial banks.
The leading principle in the work of commercial banks in the context of the transition to market relations is the desire to obtain as much profit as possible. Risks are the greater the higher the expected profitability of the operation. Risks are formed as a result of deviations of valid data from today's assessment of today and future development.
The modern banking market is unthinkable without risk. The risk is present in any operation, only it can be different scales and "soften" differently, compensated. It would be highly naive to look for the embodiments of banking operations that would fully exclude risk and pre-guarantee a certain financial result.
1.4.1 Classification of banking risks
In the course of its activities, banks face a combination of various types of risks, differing among themselves the place and time of occurrence, external and internal factors affecting their level, and, therefore, on how to analyze their analysis and methods of their description. Lobanov A.A., Chugunov A.V. Encyclopedia of financial risk management. - M., Alpina Business Buks, 2005. p.89. All types of risks are interconnected and have an impact on the activities of the Bank.
Depending on the sphere of influence or the occurrence of banking risk, they are divided into external and internal.
External are risks that are not related to the activities of the Bank or a specific client, political, economic and others. These are the losses resulting from the beginning of the war, revolution, nationalization, ban on payments abroad, debt consolidation, the introduction of the embargo, the abolition of the import license, the exacerbation of the economic crisis in the country, natural disaster. Internal risks in turn are divided into losses on the main and auxiliary activities of the Bank. The first represent the most common risk group: credit, interest, currency and market risks. The second includes losses on the formation of deposits, risks on new activities, risks of bank abuse.
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When running risks, it is often necessary to compare real situations with hypothetical (which it would be if everything went differently). This sharply complicates the analysis of risky situations, as it requires the basis for studying and measuring what was not. Currently, to describe such hypothetical situations, a path of a different way, except for the use of mathematical models called models of risky situations. This represents the basis for quantitative Risk Management. Its essence is to use economic and mathematical models for predicting situations characterized by risk and uncertainty, and the rationale for relevant management decisions.
The model is a simplified description of a real object or process that focuses on important properties for researcher and ignores those aspects that researchers are irrelevant. The main complexity of modeling is precisely to find out what properties are important, and which - no. A faithful description of important properties ensures the adequacy of the model, and the correct choice of secondary, ignored properties helps sufficiently simplify such a presentation. The model should serve as a decision-making tool, i.e., should clarify for a decision on a decision, how the process may develop, what outcomes will occur, and suggest various actions (for example, to prevent damage).
Mathematical models used in risk management are the most important class of models. They allow you to describe the essential sides of the studied process or phenomenon in the form of mathematical ratios, and then analyze them using the appropriate mathematical apparatus. It is especially important to apply mathematical models to predict alternatives to future development. This allows the manager to numerically evaluate the future consequences of the decisions made.
Mathematical models used in risk management are distinguished by a large variety and various capabilities. There is no such thing as a universal model. The multiplicity of risk types and a variety of mechanisms of their occurrence makes it impossible. In different situations, we will use specific tools (in this case - models), for each model is unique in its own way, since when it is built, it is necessary to repel from the properties of the modeling object itself. However, similar situations allow us to apply similar (if not the same) tools: there are some common approaches to modeling (for example, the use of stochastic differential equations or other mathematical apparatus). If you can replace a more or less standard approach, the modeling process will be easier (approaches to the construction of the model and the solution obtaining) are known.
In the field of quantitative risk management, the theoretical and statistical models are most common.
For some types of risks, the widespread use of mathematical models is standard, there is still no other. Nevertheless, there is an intensive operation of various techniques that use the characteristics of risk management. Quantitative risk management becomes a separate "branch" of risk management.
Name: Theory of risk and modeling of risky situations.
The textbook outlines the essence of uncertainty and risk, classification and factors acting on them; Methods for high-quality and quantifying economic and financial situations in uncertainty and risk are given.
Classification of service technologies is given, examples of service organizations in risky situations are considered.
The methodology for managing investment projects in risk conditions is given, recommendations on the management of the investment portfolio are given, the financial condition and prospects for the development of the investment facility are being evaluated, the risk accounting model in investment projects is proposed.
Considerable attention is paid to methods and models of management in the conditions of risk and psychology of behavior and assessment of a decision maker.
For students and graduate students of economic universities and faculties, listeners of Bisnes and risk managers, innovation managers, investments, as well as specialists of banking and financial structures, employees of pension, insurance and investment funds.
Content
Preface
Chapter 1 Place and role of economic risks in managing the activities of organizations
1.1. Organizations, types of enterprises, their characteristics and goals
1.2. Place and role of risks in economic activity
1.2.1. Risk definition and essence
1.2.2. Management of risks
1.2.3. Risk classification
1.2.4. Uncertainty system
1.3. Risk management system
1.3.1. Management activities
1.3.2. Risk management
1.3.3. Risk Management process
1.3.4. Mathematical methods for assessing economic risks
Chapter 2. Risks of enterprises of the service sector
2.1. Service technologies
2.2. Classification of risks of services of the service sector
2.3. Dynamic analysis of the service market
2.4. Management Risk Management Model Service Organizations
Chapter 3. The effect of major market equilibrium factors for risk management
3.1. Risk limitation factors
3.2. Effect of market equilibrium factors for risk change
3.2.1. Relationship of market balance and commercial risk
3.2.2. Effect of market equilibrium factors for a change in commercial risk
3.2.3. Simulation of the equilibrium achievement process
3.2.4. The impact of changes in demand for commercial risk
3.2.5. The impact of a change in the sentence to the degree of commercial risk
3.2.6. Building demand dependency
3.3. Effect of time factor on the degree of risk
3.4. The influence of the elasticity of the supply and demand for the level of risk
3.5. Effect of tax factor in market equilibrium at risk
Chapter 4. Financial Risk Management
4.1. Financial risks
4.1.1. Classification of financial risks
4.1.2. Communication of the financial and operational lever with cumulative risk
4.1.3. Risks of development
4.2. Interest risks
4.2.1. Views of interest risks
4.2.2. Percent operations
4.2.3. Middle percentages
4.2.4. Variable interest rate
4.2.5. Risks of interest rates
4.2.6. Interest risk of bonds
4.3. Risk of loss from changing payment flow
4.3.1. Equivalent flows
4.3.2. Payment flows
4.4. Risk investment processes
4.4.1. Investment risks
4.4.2. Risk assets return rates
4.4.3. Pure discounted value
4.4.4. Annuity and repayment fund
4.4.5. Evaluation of investments
4.4.6. Risk investment plates
4.4.7. Discounting in time
4.5. Credit risks
4.5.1. Factors contributing to the emergence of credit risks
4.5.2. Analysis of credit risks
4.5.3. Credit risk reduction techniques
4.5.4. Payments on loans
4.5.5. Importance and payment of interest in consumer loan
4.5.6. Credit guarantees
4.6. Risk of liquidity
4.7. Inflationary risk
4.7.1. Interest rates with inflation rate
4.7.2. Inflationary premium
4.7.3. Influence inflation on different processes
4.7.4. Inflation reduction measures
4.8. Currency risks
4.8.1. Currency Conversion and Percentage
4.8.2. Currency courses in time
4.8.3. Reducing currency risks
4.9. Risks of assets
4.9.1. Stock risks
4.9.2. The influence of the risk of default and taxation of the value of assets
4.10. Probabilistic assessment of the degree of financial risk
Chapter 5. Quantitative estimates of economic risk in uncertainty
5.1. Methods for making effective solutions in uncertainty
5.2. Matrix Games
5.2.1. The concept of playing with nature
5.2.2. The subject of game theory. Basic concepts
5.3. Efficiency criteria in conditions of complete uncertainty
5.3.1. Criterion guaranteed results
5.3.2. Criterion of optimism
5.3.3. Criteria pessimism
5.3.4. Minimax Risk Criteria Savage
5.3.5. Criteria of generalized maximism (pessimism - optimism) Gurvitsa
5.4. Comparative assessment of solutions depending on efficiency criteria
5.5. Multi-criteria tasks of selecting effective solutions
5.5.1. Multi-criteria tasks
5.5.2. Pareto optimality
5.5.3. Selection of solutions in the presence of multi-criteria alternatives
5.6. The decision model in terms of partial uncertainty
5.7. Determination of the optimal volume of sewing production in conditions of uncertainty
5.7.1. Top and Lower Game Price
5.7.2. Matching a matrix game to the task of line programming
5.7.3. Choosing an optimal product range
5.8. Risks associated with the work of the sewing enterprise
Chapter 6. Taking the optimal solution in economic risk
6.1. Probabilistic formulation of preferred solutions
6.2. Risk assessment in definiteness
6.3. Choosing the optimal number of workplaces in the hairdresser, taking into account the risk of service
6.4. Statistical methods of decision-making under risk
6.5. Choosing an optimal plan by building trees of events
6.5.1. Tree solutions
6.5.2. Optimization of the market entry strategy
6.5.3. Maximization of profits from stock
6.5.4. The choice of the optimal project of the reconstruction of the dry cleaning factory
6.6. Comparative score options
6.6.1. Select the optimal solution option using statistical estimates
6.6.2. Normal distribution
6.6.3. Risk curve
6.6.4. Choosing an optimal solution with trust intervals
6.6.5. Model forecasting production costs
6.7. The emergence of risks when setting the mission of the company's goals
6.8. Activity of service enterprises under risk
6.8.1. Firm for decoration and design Enterprise for baking bakery products and their subsequent sale
6.8.3. Beauty saloon
Chapter 7. Management of investment projects in risk
7.1. Investment projects in uncertainty and risk
7.1.1. Basic concepts of investment projects
7.1.2. Analysis and assessment of investment projects
7.1.3. Risks of investment projects
7.2. Optimal selection of investment, providing maximum production output
7.3. Investments in securities portfolio
7.3.1. Investment Management Process
7.3.2. Diversified portfolio
7.3.3. Risks associated with investing in securities portfolio
7.3.4. Practical recommendations for the formation of an investment portfolio
7.4. Analysis of the economic efficiency of the investment project
7.4.1. Analysis of concomitant risk factors
7.4.2. Preliminary assessment and selection of enterprises
7.4.3. Evaluation of the financial condition of the enterprise as an investment object
7.4.4. Examples of analysis using financial coefficients
7.4.5. Evaluation of the development prospects of the organization
7.4.6. Comparative financial analysis of investment projects
7.4.7. Analysis of organization examination methods on site
7.5. Risk accounting in investment projects
7.5.1. Project risk assessment model
7.5.2. Risk accounting for investing
7.5.3. Practical conclusions for risk investment project management
Chapter 8. Risk management of tourism
8.1. Factors affecting the dynamics of tourism development
8.1.1. Tourism development in Russia
8.1.2. Types and forms of tourism
8.1.3. Features of tourism - as factors of uncertainty of development
8.2. Psychology of the impact of tourism on participants and others
8.2.1. Motivation of travel
8.2.2. Impact of tourism
8.3. Risks associated with tourist activities
8.3.1. Factors affecting tourism and tourism economy
8.3.2. Classification of tourism risks
8.4. Economic impact of tourism
8.5. Adoption of a managerial decision
8.6. Analysis of the activities of the organization for the provision of tourist services under risk
Chapter 9. Risk management of hotels and restaurants
9.1. Development of hotel enterprises
9.2. Restaurant business development factors
9.3. Features and specificity of hospitality
9.4. Risks inherent in hospitality industry and management of them
9.4.1. Revealing risks
9.4.2. Risks of investment projects
9.4.3. Reducing the risks of the hospitality industry
9.5. Management solutions in hospitality business
Chapter 10. Major methods and ways to reduce economic risks
10.1. General Risk Management Principles
10.1.1. Risk Management Process Scheme
10.1.2. Sample risks
10.1.3. Selection of risk management techniques
10.2. Diversification
10.3. Risk insurance
10.3.1. Insurance essence
10.3.2. The main characteristics of insurance contracts
10.3.3. Calculation of insurance operations
10.3.4. Insurance contract
10.3.5. Advantages and disadvantages of insurance
10.4. Heading
10.4.1. Risk Management Strategies
10.4.2. Basic concepts
10.4.3. Forward and futures contracts
10.4.4. Hedging currency rate
10.4.5. Main aspects of risk
10.4.6. Currency Hedge with Swip
10.4.7. Options
10.4.8. Insurance or hedge
10.4.9. Synchronization of cash flows
10.4.10. Hedge model
10.4.11. Measuring Hedge Efficiency
10.4.12. Minimizing hedging expenses
10.4.13. Correlated hedging operation
10.5. Limit
10.6. Reservation of funds (self-insurance)
10.7. Quality risk management
10.8. Acquisition of additional information
10.9. Evaluation of the effectiveness of risk management methods
10.9.1. Risk financing
10.9.2. Risk Management Evaluation
Chapter 11. Psychology of behavior and assessment of a decision maker
11.1. Personal factors affecting the degree of risk when making management decisions
11.1.1. Psychological problems of the behavior of an economic personality
11.1.2. Management actions of an entrepreneur in the service sector
11.1.3. Personality ratio
11.1.4. Intuition and risk
11.2. Theory of expected utility
11.2.1. Graphs of the functions of utility
11.2.2. Theory of expected utility
11.2.3. Accounting for a person who makes a decision to risk
11.2.4. Group decision making
11.3. Theory of rational behavior
11.3.1. Perspective theory
11.3.2. Rational approach to decision making
11.3.3. Asymmetry making decisions
11.3.4. Invariance of behavior
11.3.5. The role of information in decision-making
11.4. Conflict situations
11.5. The role of the head in the adoption of risky decisions
11.5.1. Risk decision making
11.5.2. Requirements for a decision making a decision
11.5.3. Principles for evaluating the effectiveness of solutions received by the LPR
Questions for repetition
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Quality Risk Analysis Methods
After all possible risks were identified on a specific project, it is necessary to determine the feasibility of investments, development and work on this project. This analyzes the risks of the investment project.
All possible and proposed methods for analyzing risks can be conditionally subjected to high-quality and quantitative approaches. A qualitative approach, in addition to identifying risks, implies the definition of sources and the causes of their occurrence, as well as the valuation of the consequences. The main features of the qualitative approach is: allocating simple risks on the project, determining dependent and independent risks both from each other and from external factors, and the definition of whether the risks are eliminated or not.
With the help of high-quality analysis, all risk factors are determined, entailing into one way or another loss or loss of the enterprise, as well as the likelihood and time of their occurrence. For the worst draft development scenario, the maximum value of the company's losses is calculated.
In a qualitative approach, the following risk analysis methods are distinguished: the method of expert assessments; The method of expediency of costs; Method of analogy.
Expert assessment method.
The method of expert assessments includes three main components. First, the intuitive and logical analysis of the problem is based only on the intuitive assumptions of certain experts, the guarantor of the correctness and objectivity of the conclusions can serve only their knowledge and experience. Secondly, the issuance of evaluating experts, this stage is the final part of the work of the expert. The experts are a decision on the feasibility of working with the project under study, and the evaluation of the expected results is proposed, according to various project development scenarios. The third stage, the final for the method of expert assessments, is the processing of all the results of the solution. In order to obtain a summary assessment, all the evaluations received from experts should be processed, and a total relatively objective assessment and a decision was revealed relative to a specific project.
Experts are invited to fill out a questionnaire with a detailed list of risks relating to the analyzed project in which they need to determine the likelihood of the onset of risks on a specific scale. The most common methods of expert risk assessments include the Delphi method, the method of ballest estimates, ranking, pairwise comparison, and others.
Delphi method is one of the methods of expert assessments, providing a quick search for solutions, including in the consequence the best solution is selected. The use of this method allows you to avoid contradictions among experts, and get independent individual decisions, excluding communication between experts during a survey. The experts are issued a questionnaire sheet, whose questions, it is necessary to give independent, the most objective assessments, and reasonable estimates. Based on the completed questionnaires, the solution of each expert is analyzed, the prevailing opinion is revealed, extreme judgments, justified, and reasonable decisions are also available and reasoned. In consequence, experts can change their opinion. The entire operation is usually carried out in 2-3 rounds, until the topics of expert opinions, which will be the final result of the study.
The method of a scoring risk assessment is made on the basis of a generalizing indicator determined by a number of private expertly estimated rates of risk. It consists of the following steps:
- 1) the definition of factors that affect the occurrence of risk;
- 2) the choice of a generalized indicator and a set of private criteria characterizing the degree of risk for each of the factors;
- 3) drawing up a system of weighting coefficients and scales of estimates for each indicator (factor);
- 4) integral assessment of a generalized criterion for the degree of project risks;
- 5) Development of risk management recommendations.
The ranking method implies the location of objects in ascending order or decrease of any properties inherent in them. Ranking allows you to choose from the existing set of factors most significant. The ranking result is the ranking.
If available n. Objects, as a result of their rankings with a J-th expert, each object receives an estimate of X ij - rank attributed to the I-MU object by the Jth Expert. The x ij values \u200b\u200bare in the range from 1 to n. The rank of the most important factor is equal to one, the least significant - number N. The ranking of the J-th expert is a sequence of ranks X 1J, X 2J, ..., X NJ.
This method is simply in its implementation, however, when evaluating a large number of parameters, experts face the difficulty of building a ranked row, due to the fact that it is necessary to take many complex correlations at the same time.
The method of pairwise comparison is to establish the most preferred objects when comparing all possible steam. In this case, there is no need, as in the ranking method, organize all objects, it is necessary to identify a more significant object in each pair or establish their equality.
Again, in comparison with the ranking method, the pair comparison can be carried out with a large number of parameters, as well as in cases of a minor difference in parameters (when it is practically not possible to rank them, and they are combined into one).
When using the method, the matrix is \u200b\u200bmost often drawn up nXN.where n. - Number of compared objects. When comparing objects, the matrix is \u200b\u200bfilled with elements a ij as follows (there may be a different filling circuit):
The sum (on line) in this case makes it possible to estimate the relative importance of objects. The object for which the amount will be the highest can be recognized as the most important (significant).
The summation can also be done in columns (), then the most significant will be a factor that scores the smallest number of points.
Expert analysis is to determine the degree of risk impact on the basis of expert assessments of specialists. The main advantage of this method is the simplicity of calculations. There is no need to collect accurate source data and the use of expensive and software. However, the risk level depends on the knowledge of experts. And the disadvantage is the difficulty in attracting independent experts and the subjectivity of their estimates. For the clarity and objectivity of the results, this method can be used together with other methods quantitative (more objective).
The method of relevance and feasibility of costs, the method of analogy.
At the heart of the analysis of the relevance or feasibility of costs, there are assumptions that certain factors (or one of them) are the cause of recalculation of funds for the project. These factors include:
- · The initial underestimation of the project value as a whole or its individual phases and components;
- · Changes in design boundaries due to unforeseen circumstances;
- · The difference between the performance of machines and mechanisms from the provided by the project;
- · Increase the cost of the project in comparison with the initial, due to inflation or changes in tax legislation.
For analysis, it is primarily a detail of all the above factors, then a presumptive list of possible costs of project costs are drawn up for each development option. The entire project implementation process is divided into steps, on the basis of this, the financing process in the development and implementation of the project is also divided into steps. However, the financing stages are conditional, as some changes can be made as the development and development of the project. The phased investment of funds allows the investor to carefully track work on the project, as well as in the event of risks, or stop or suspending financing, or begin to take certain measures to reduce costs.
Among the qualitative methods for analyzing risks, the method of analogy is also common. The main idea of \u200b\u200bthis method is to analyze other projects similar to being developed. Based on the same risky projects, possible risks, the reasons for their occurrence, the effects of the influence of risks, as well as the consequences of the impact on the project of adverse external or internal factors. Then received information is projected into a new project, which allows you to determine all the maximum possible potential risks. The source of information can be regularly published by Western insurance companies, the ratings of reliability of project, contracting, investment and other companies, analyzes the trends in demand for specific products, prices for raw materials, fuel, land, etc.
The complexity of this method of analysis is the impected subpode of the most accurate analogue, due to the fact that there are no formal criteria that exactly establish the degree of similarity of situations. But, as a rule, even in the case of a selection of a correct analogue, the complexity of the wording of the correct prerequisites for analysis, full and close to the reality, a set of scenarios of the project disruption appears. The reason is that completely identical projects are extremely small or not found at all, any studied project has its own individual features and risks that are interconnected according to originality of the project, therefore it is not always possible to absolutely determine the reason for the occurrence of one or another risk.
A brief description of the moderation method and the analogy method indicates that they are more suitable for determining and describing possible risky situations for a specific project than to obtain even relatively accurate assessment of the risks of the investment project.
Quantitative Risk Analysis Method
To assess the risks of investment projects, the following quantitative methods of analysis are most common as:
- · Sensitivity analysis
- · Script method
- · Imitation modeling (Monte Carlo method)
- · Discount rate adjustment method
- · Tree solutions
Sensitivity analysis
In the sensitivity analysis method, the risk factor is made as a degree of sensitivity of the resultant indicators of the project being analyzed to change the external or internal conditions of its functioning. Efficiency (NPV, IRR, PI, PP) or annual project indicators (net profit, accumulated profit) usually act as the result resulting indicators. The sensitivity analysis is divided into several consecutive stages:
- · The basic values \u200b\u200bof the resultant indicators are established, mathly establishes the relationship between the source data and the result
- · The most likely values \u200b\u200bof the initial indicators are calculated, as well as the range of their changes (as a rule, in the range of 5-10%)
- · Determined (calculated) The most likely values \u200b\u200bof the resultant indicators
- · The initial test parameters in turn are revised within the received range, new values \u200b\u200bof the resultant parameters are obtained.
- · The initial parameters are ranked by their degree of influence on the resultant parameters. Thus, they are grouped based on the degree of risk.
The degree of exposure to the investment project to the relevant risk and sensitivity of the project to each factor is determined by calculating the indicator of the elasticity, which is the percentage ratio of the resultant indicator to change the value of the parameter by one percent.
Where: E - Elasticity Indicator
NPV 1 - the value of the basic resulting indicator
NPV 2 - the value of the resultant indicator when the parameter changes
X 1 - the basic value of the variable parameter
X 2 - the changed value of the variable parameter
The higher the values \u200b\u200bof the elasticity indicator, the more sensitive project to changes in this factor, and the stronger the project is subject to relevant risk.
Also, the sensitivity analysis can be carried out graphically by constructing the dependence of the resultant indicator from the change in the factor under study. The sensitivity of the NPV value to the change in the factor is changed by the level of tilt dependence than the angle more, the meanings are more sensitive, as well as the greater the risk. At the point of intersection of direct response to the abscissa axis, the value of the parameter in percentage expression is determined, in which the project will become ineffective.
After that, on the basis of the calculations carried out, all parameters obtained are ranked according to the degree of importance (high, medium, low), and a "sensitivity matrix" is built, with which the factors that are the most and least risky for the investment project are distinguished.
Regardless of the inherent method of advantages - objectivity and visibility of the results obtained, there are also significant drawbacks - the change in one factor is considered isolated, whereas in practice all economic factors are in one degree or another correlated.
Script method
The script method represents a description of all possible project implementation conditions (or in the form of scenarios, or in the form of a system of restrictions on the values \u200b\u200bof the basic parameters of the project) as well as a description of possible results and performance indicators. This method, as any other, also consists of certain consecutive stages:
- · At least three possible scenarios options are built: pessimistic, optimistic, realistic (or most likely or medium)
- · Initial information on uncertainty factors is transformed into information on the likelihood of certain conditions of implementation and certain performance indicators
Based on the data obtained, the indicator of the economic efficiency of the project is determined. If the probabilities of an occurrence of a particular event reflected in the scenario are known for sure, the expected integral effect of the project is calculated by the formula of the expectation:
Where: NPVI is an integral effect when implementing the I-th scenario
pI - the probability of this scenario
At the same time, the risk of the ineffectiveness of the project (RE) is estimated as the total probability of those scenarios (K), in which the expected project efficiency (NPV) becomes negative:
The average damage from the project implementation in the case of its ineffectiveness (UE) is determined by the formula:
The main disadvantage of the method of scenario analysis is allocated the accounting factor of only several possible outcomes on an investment project, but in practice the number of possible outcomes is not limited.
PERT-analysis method (Program Evaluation and Review Technique)
One of the methods of scenario analysis, specialists allocate the PERT-analysis method (Program Evaluation and Review Technique). The main idea of \u200b\u200bthis method is that when developing a project, three project parameters are set - optimistic, pessimistic, most likely. Next, the expected values \u200b\u200bare calculated by the following formula:
The expected value \u003d [Optimistic value of 4KHNIs Morely probable value + pessimistic quantity] / 6
The coefficients 4 and 6 are obtained empirically based on the statistical data of a large number of projects. Based on the results of the calculation, the remaining project analysis is carried out. The effectiveness of the PERT analysis is maximum, only if you can justify the values \u200b\u200bof all three estimates.
Tree solutions
The solutions method represents network graphs in which each branch, the various alternative project development options. Following each conveyed project branch, you can trace all possible stages of project development, and accordingly, and choose the most optimal of them, and with the least risks. This analysis method is divided into the following steps:
- · The vertices are determined for each problem and ambiguous moment of development of the project, and branches are built (possible ways to develop events)
- · For each arc is determined by the expert method probability and possible losses at this stage.
- · Based on all the obtained vertices values, the most likely value of NPV (or otherwise significant for the indicator project) is calculated)
- · Analysis of the probabilistic distribution is carried out.
The only limitation and possibly a lack of a method is the mandatory presence of a reasonable number of project development options. The preferred difference is the possibility of full and detailed accounting of all factors and risks affecting the project. The method is especially used in situations where decisions on project implementation are made gradually, and depend on previous decisions, thus, each decision in turn defines the scenario of the further development of the project.
Simulation modeling (Monte Carlo method)
Analysis of the risks of investment projects by Monte Carlo, combines two previously studied methods: a method of analyzing sensitivity and analysis of scenarios. In imitation modeling, instead of the compilation of the best and worst scenarios, hundreds of possible combinations of project parameters are generated using a computer, given their probabilistic distribution. Each obtained combination issues its NPV value. Such a calculation is possible only using special computer programs. The phased scheme of imitation modeling is built as follows:
- · Formulate factors affecting cash flows of the project;
- · A probabilistic distribution for each factor (parameter) is built, while it is usually assumed that the distribution function is normal, therefore, in order to set it, it is necessary to determine only two points (mathematical expectation and dispersion);
- · The computer randomly selects the value of each risk factor based on its probabilistic distribution;
Fig.1.3
Fig.1.4.
Among the disadvantages of this method of risk modeling are identified:
- · The existence of correlated parameters greatly complicates the model
- · The type of probabilistic distribution for the parameter under study may be difficult to determine
- · When developing real models, it may be necessary to attract specialists or scientific consultants from;
- · Study of the model is possible only in the presence of computing equipment and special application packages;
- · The relative inaccuracy of the results obtained compared to other methods of numerical analysis.
Method for adjusting the rate of discount
Due to the simplicity of calculations, the method of adjusting the rate of discount, taking into account the risk, is the most applicable in practice. This method is the adjustment of the specified base rate of the discount, which is considered rigless and minimally acceptable (for example, the maximum cost of capital for the company). Adjustment is carried out as follows: The value of the required risk premium is added then the criteria for the effectiveness of the investment project (NPV, IRR, PI) are calculated. The project's effectiveness is made according to the rules of the chosen criterion. The higher the risk, the greater the amount of the premium.
Risk amendments are specified separately for each project separately, since they are fully dependent on the specifics of the project under study.
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