Table of contents (expand)
- The concept of planning
- The subject of planning. The essence and structure of planning objects in the organization
- The essence and necessity of business planning
- The role, place and importance of business planning in the management system of an organization (enterprise)
- The need for a business plan for the leader and entrepreneur
- Forms of planning and factors influencing the choice of planning forms
- Requirements for the development of business plans. Information support of business planning
- Structure, functions and content of sections of the business plan. section of the business plan "concept, overview, summary"
- Section of the business plan "description of the underlying enterprise"
- Business plan sections "product description (products, services, products)", "market analysis, marketing and sales"
- Business plan sections "production plan", "organizational plan"
- Business plan sections "environment and regulatory information", "project risks and insurance", "project implementation schedule"
- The concept, economic content, the main elements of strategic planning. concept and classification of strategies
- Goals of the organization (enterprise)
- Goals and strategy for the implementation of projects
- Investment plan (project). Investment cost budget
- Primary documents of the financial plan. Purpose, structure and methodology for calculating the main documents of the financial plan
- Cash flow plan
- Profit and loss plan
- Profit distribution plan. balance plan
- Requirements for the main documents of the financial plan. International Financial Reporting Standards. financial planning technology
- Project financing strategy. Information support, methodology for calculating planned indicators and determining cash flows
- Basic technological processes of business planning. terms of reference and schedule (work schedule) for the development of a business plan
- Types of models used in business planning
- Features of the development of business process models. information technology for business plan development
- Purpose of the analytical system Project Expert
- The main stages in the development of the financial model (budgets) of the business plan. Preparation of the necessary initial information for the development of a financial model
- Competitiveness. Operations. The financial position of the company. strategic plan
- Sales plan and production plan in the Project Expert system
- Definition of a funding strategy. Project financing plan in the Project Expert system
- Effect of Payment Terms, Inflation and Taxation on Calculation Results
- Scenario analysis
- Simulation
- Evaluation and analysis of investment projects. Investment efficiency indicators. Calculation and analysis of the main indicators of the effectiveness of investment costs, taking into account the discount rate
- Payback period. discounted payback period
- Average rate of return. net present value
- profitability index. Internal rate of return
- Modified internal rate of return
- Calculation, evaluation and analysis of financial ratios of a business plan
- Liquidity indicators
- Business Activity Indicators
- Turnover ratios of working capital, fixed assets, assets
- Capital structure indicators
- Profitability indicators
- Investment indicators
- Calculation and definition of risk factors. Factor analysis. expert method
- Sensitivity analysis
- Monte Carlo method
- Project break-even analysis
- Project break-even indicators
- Statistical and scenario analysis. Modeling conditions, calculation and interpretation of the results of statistical and scenario analysis in the Project Expert system
- Making decisions on the need to invest in projects (business plans) based on performance indicators. Making decisions based on the results of the analysis in order to optimize income, costs
48. MONTE CARLO METHOD
Purpose of statistical analysis - determine the degree of impact of random factors on project performance indicators.
The analysis is carried out as follows. Let us assume that it has been determined which data should be considered uncertain, and also a range of values within which they can vary randomly has been established. If we are talking, for example, about two parameters, this means that the range of values of the source data has been defined, having the shape of a rectangle. For three variables, this region is a parallelepiped. The set of initial data on which the fate of the project depends is displayed by a point lying inside the selected area. There are a great many such points, so it is impossible to perform project calculations for each of them. However, it is necessary to determine what effect the uncertainty of the input data has on the behavior of the model. This problem is solved using the Monte Carlo method.
Suppose we have a way to select points in a selected data area randomly, similar to roulette in a gambling establishment. For each point chosen in this way, we will calculate the performance indicators and write them down in a table. Having done a sufficiently large number of experiments, we can draw some conclusions.
Two criteria are used to quantify the results. mean value and uncertainty. Suppose we have done N experiments and obtained a set of values for some indicator f(n = 1, N). Then the average value of M is determined by the formula
where M is the expected value of fn; f - a certain indicator under study; N is the number of experiments performed.
The uncertainty (or coefficient of variation) is calculated as follows:
The value M can be interpreted as the expected value of the random variable fn.
Uncertainty can also be viewed as an assessment of the risk associated with the fact that the value of fn deviate from the expected value of M.
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