Exam 11: Simulation Models

A tornado chart lets us see which random input has the most effect on a specified output in a financial model.

A key input variable in many marketing models of customer loyalty is the:

Exhibit 11-1 A company is considering investing $1.2M in a facility to manufacture a new product. The product will have a five year life, after which the facility will be shut down. A pro forma cash flow sheet for this project, with forecasted production levels, unit prices, and production costs, is shown below: -[Part 3] Refer to Exhibit 11-1.What is the standard deviation of the NPV What does it indicate

Exhibit 11-1 A company is considering investing $1.2M in a facility to manufacture a new product. The product will have a five year life, after which the facility will be shut down. A pro forma cash flow sheet for this project, with forecasted production levels, unit prices, and production costs, is shown below: -[Part 4] Refer to Exhibit 11-1.What does the distribution of the project NPV look like

The RISKSIMTABLE function is used to summarize the results of a single simulation of product lifetime.

Which of the following is typically not an application of simulation models

In bidding models,the simulation output variable is the number of competitors who will bid.

A common distribution for modeling product lifetimes is the normal distribution

Exhibit 11-2 Suppose we want to choose capacity for a plant that will produce a new drug. In particular, we want to choose the capacity that maximizes discounted expected profit over the next 10 years. Assume all cash flows occur at the end of the year. We have the following information: ∙Demand for the drug is expected to be normally distributed ˜ Normal (50,000, 12,000). Demand each year is an independent event. ∙A unit of capacity costs $16 to build in year 1. ∙The number of units produced will equal the demand, up to capacity limits. ∙The revenue per unit is $3.70 and the cost per unit is $0.20 (variable cost). ∙The maintenance cost per unit of capacity is $0.40 (fixed cost). ∙The discount rate is 10%. -[Part 1] Refer to Exhibit 11-2.Perform a simulation assuming the plant will be designed to meet the expected demand.What is the net present value (NPV)in that case

In financial simulation models,we are typically more interested in the expected NPV of a project than in the extremes of the outcomes.

For an NPV simulation,the value at risk (VAR)is typically defined as the:

Value at risk (VAR)is an indicator of:

Which of the following is the most likely characteristic of a distribution that is to be used to develop a simulation model for estimating the time until failure of a product in a simulation model

Exhibit 11-2 Suppose we want to choose capacity for a plant that will produce a new drug. In particular, we want to choose the capacity that maximizes discounted expected profit over the next 10 years. Assume all cash flows occur at the end of the year. We have the following information: ∙Demand for the drug is expected to be normally distributed ˜ Normal (50,000, 12,000). Demand each year is an independent event. ∙A unit of capacity costs $16 to build in year 1. ∙The number of units produced will equal the demand, up to capacity limits. ∙The revenue per unit is $3.70 and the cost per unit is $0.20 (variable cost). ∙The maintenance cost per unit of capacity is $0.40 (fixed cost). ∙The discount rate is 10%. -[Part 4] Refer to Exhibit 11-2.Are there any simulations which indicated there was a chance of getting negative NPV Briefly explain in one sentence.

RISKTARGET is a function that allows us to determine the cumulative probability of a particular value in an output distribution,such as the probability of meeting a due date in manufacturing.

In marketing and sales models,the primary issue is the uncertain amount of sales that can be obtained,given an assumed timing.

Suppose we compare the difference between the NPV of a financial model in which the means are entered for all input random variables and the NPV of a financial model in which the most likely values are entered for all input random variables.If we see a large difference between the NPV's,this illustrates:

Exhibit 11-2 Suppose we want to choose capacity for a plant that will produce a new drug. In particular, we want to choose the capacity that maximizes discounted expected profit over the next 10 years. Assume all cash flows occur at the end of the year. We have the following information: ∙Demand for the drug is expected to be normally distributed ˜ Normal (50,000, 12,000). Demand each year is an independent event. ∙A unit of capacity costs $16 to build in year 1. ∙The number of units produced will equal the demand, up to capacity limits. ∙The revenue per unit is $3.70 and the cost per unit is $0.20 (variable cost). ∙The maintenance cost per unit of capacity is $0.40 (fixed cost). ∙The discount rate is 10%. -[Part 2] Refer to Exhibit 11-2.Use a RISKSIMTABLE to with the following values for capacity: 20,000,25,000,30,000,35,000,40,000.Which of these capacities produces the largest expected NPV

The main issue in marketing and sales models is:

Which of the following functions is not an @RISK statistical function