TAILIEUCHUNG - Simulation Concepts and Methods

Simulation allows the repeated solution of an evaluation model. Each solution randomly selects values from predetermined probability distributions. All solutions are summarized into an overall distribution of NPV values. This distribution shows management how risky the project is. | Chapter 9: Simulation Concepts and Methods Project risk analysis by simultaneous adjustment of forecast values. Introduction Simulation allows the repeated solution of an evaluation model. Each solution randomly selects values from predetermined probability distributions. All solutions are summarized into an overall distribution of NPV values. This distribution shows management how risky the project is. Simulation Terminology The treatment of risk by using simulation is known as ‘stochastic’ modeling. Other names for our term ‘Simulation’, are - ‘Risk Analysis’, ‘Venture Analysis’,’Risk Simulation’, ‘Monte Carlo Simulation’. The name ‘Monte Carlo Simulation’ helps visualization of repeated spins of the roulette wheel, creating the selected values. Each execution of the model is known as a ‘replication’ or ‘iteration’. The Role of Simulation Follows the initial creation and basic testing of the representative model. Is sometimes used as a test of the model. Emphasizes the need for formal forecasting, and requires close specification of the forecast variables. Draws managements attention to the inherent risk in any project. Focuses attention on accurate model building. Probability Distributions of Forecast variables Uniform: upper and lower bounds required. Probability Distributions of Forecast variables Uniform: upper and lower bounds required. Triangular: pessimistic, most likely, and optimistic values required Probability Distributions of Forecast variables Uniform: upper and lower bounds required. Triangular: pessimistic, most likely, and optimistic values required Normal: mean and variance required. Probability Distributions of Forecast Variables Uniform: upper and lower bounds required. Triangular: pessimistic, most likely, and optimistic values required Normal: mean and variance required. Exponential: initial value and growth factor required. Process of Computation per Replication A value of a variable is selected from its distribution using a random number generator. For example: Sales 90 units; selling price per unit $2,350; component cost per unit $1,100; labour cost per unit $280. These values are incorporated into the model, and an NPV is calculated for this replication. The NPV for this replication is stored, and later reported as one of many in an overall NPV distribution. Making the Replications Each replication is unique. Selection of values from the distribution is made according to the particular distributions The automated process is driven by a random number generator. Excel add-ons such as ‘@Risk’ and ‘Insight’ can be used to streamline the process. About 500 replications should give a good picture of the project’s risk. Using the Output Management can view the risk of the project. Probability of generating an NPV between two given values can be calculated. Probability of loss is the area to the left of a zero NPV. Benefits and Costs of Simulation Focuses on a detailed definition and analysis of risk. Sophisticated analysis clearly portrays the risk of a project Gives the probability of a loss making project Allows simultaneous analysis of variables -- -- -- -- -- -- Requires a significant forecasting effort. Can be difficult to set up for computation. Output can be difficult to interpret.

• Quỹ đầu tư
• Simulation Concepts
• Methods
• project costs
• project investment
• project evaluation
• project management
• technical project management
• project management for small business
• thủ thuật máy tính
• công nghệ thông tin
• tin học
• quản trị mạng
• computer network
• cash flows
• quantitative techniques
• Project analysis
• Resource constraints
• Applied statistics for civil
• Environmental engineers
• Preliminary data analysis
• Basic probability concepts
• Frequency analysis of extreme events
• Simulation techniques for design
• Energy Management
• Buildings Using MATLAB
• Control Applications
• Synchronous Generator
• Advanced Control
• Strategies Simulation
• Management science
• Basic concepts
• Decision analysis
• Nonlinear programming
• Queueing models
• Computer simulation
• Project Cash Flows
• Project Appraisal
• Essential Formulae
• Project Analysis Under Certainty
• Project Analysis Under Risk
• Project Analysis
• Techniques
• Routes
• Qualitative Forecasting
• Linear Programming
• Advanced Linear
• Investment Analysis
• Property Investment Analysis
• Capital Budgeting
• Financial Appraisal
• Breakeven Analysis
• Sensitivity
• Forestry Investment
• Financial Modeling
• Property Investments
• Forecasting
• economics
• management
• water source
• business has shifted
• situations and decisions
• entrepreneurs and small
• environment conducive
• small businesses