Simulation Concepts and Methods doc

1 Chapter 9: Simulation Concepts and Methods Project risk analysis by simultaneous adjustment of forecast values. 2 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. 3 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’. 4 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. 5 Probability Distributions of Forecast variables  Uniform: upper and lower bounds required. 6 Probability Distributions of Forecast variables  Uniform: upper and lower bounds required.  Triangular: pessimistic, most likely, and optimistic values required 7 Probability Distributions of Forecast variables  Uniform: upper and lower bounds required.  Triangular: pessimistic, most likely, and optimistic values required  Normal: mean and variance required. 8 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. 9 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. 10 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. [...]... 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 11 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 . 1 Chapter 9: Simulation Concepts and Methods Project risk analysis by simultaneous adjustment of forecast values. 2 Introduction  Simulation allows. project is. 3 Simulation Terminology  The treatment of risk by using simulation is known as ‘stochastic’ modeling.  Other names for our term Simulation ,