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A manufacturer is planning to produce and sell a new product. It would cost $20 million...

A manufacturer is planning to produce and sell a new product. It would cost $20 million at Year 0 to buy the equipment necessary to manufacture the product. The project would require net working capital at the beginning of each year in an amount equal to 15% of the year's projected sales; for example, NWC0 = 15%(Sales1). The product would sell for $30 per unit, and believes that variable costs would amount to $15 per unit. After Year 1, the sales price and variable costs will increase at the inflation rate of 3%. The project's fixed costs would be $500,000/year in Year 1 and would increase with inflation.

    The products will be sold for 4 years. If the project is undertaken, it must be continued for the entire 4 years. The firm believes it could sell 500,000 units per year.

     The equipment would be depreciated over using straight-line depreciation. The estimated market value of the equipment at the end of the project’s 4-year life is $500,000. The federal-plus-state tax rate is 40%. Its cost of capital is 10%.

Do parts a-e in Excel with separate tabs for each part.    Do part f) in Word.

Develop a spreadsheet model, and use it to find the project’s NPV, IRR, and payback. (Suggestion:   Use the ch. 13 Build A Model as a reference. However, your spreadsheet model should be clearly built from scratch, not copied and pasted in that one.   The capital budgeting metrics are covered in chapter 12 ).

Now conduct a sensitivity analysis to determine the sensitivity of NPV to changes in the sales price, variable costs per unit, and number of units sold. Set these variables’ values at least 5%, 10%, and 20% above and below their base-case values. Include a graph in your analysis. To which variable does NPV appear most sensitive?   (Suggestions: Use Excel’s Data Table feature, or re-calculate the NPV of each input level and then copy and paste the results).                                                                                                               

Now conduct a scenario analysis. Assume that there is a 25% probability that best-case conditions, with each of the variables discussed in Part b being 20% better than its base-case value, will occur. There is a 25% probability of worst-case conditions, with the variables 20% worse than base, and a 50% probability of base-case conditions.     (Suppose the average CV of this company's projects is 2.0. Is this project more or less risky than the average project for this company?).   Use the approach in the Build-A-Model.                                                                                                     

Set up your own numerical example of a real option. You can choose either a timing or an abandonment option. Use any probabilities and cash flows that make sense.

Extra credit: Set up your own Monte Carlo simulation. (See discussion in ch. 13 and the Excel ToolKit)

                                                                                                                               

Write an approximately 2 page report suitable for a CFO with your recommendation about whether to approve or reject this project.   The recommendation should have separate sections including summary results from the spreadsheet model, interpretations of the capital budgeting metrics, interpretations of your sensitivity and scenario analysis, the analysis of your real option, and the Monte Carlo simulation, if applicable. Include any other factors in your recommendation that you believe are relevant.                                                                                                                                                                                                                                                                                                                                                

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