Lili Romero and Brent Gibbs analyzed a lite orange juice project for the Indian River Citrus Company. The project required an initial investment of $570,000 in fixed assets (including shipping and installation charges), plus a $10,000 addition to net working capital. The machinery would be used for 4 years and be depreciated on the basis of a 3-year MACRS class life. The appropriate MACRS depreciation allowances are 0.33, 0.45, 0.15, and 0.07 in Years 1 through 4, respectively, and the machinery is expected to have a salvage value of $100,000. If the project is undertaken, the firm expects to sell 400,000 cartons of lite orange juice at a current dollar (Year 0) wholesale price of $2 per carton. However, the sales price will be adjusted for inflation, which is expected to average 5 percent annually, so the actual expected sales price at the end of the first year is $2.10, the expected price at the end of the second year is $2.205 and so on. The lite orange juice project is expected to cannibalize the before-tax profit Indian River earns on its regular orange juice line by $20,000, because the two product lines are somewhat competitive. Further, the company expects cash operating costs to be $1.50 per unit in Time 0 dollars, and it expects these costs to increase by 2 percent per year. Therefore, total operating cash costs during the first year of operation (Year 1) are expected to be ($1.50) (1.02) (400,000) = $612,000. Indian River's tax rate is 25 percent, and its cost of capital is 10 percent. Cash flow data and other information, as developed by Lili and Brent given in Table 1. When Lili and Brent presented their initial (Case 12) analysis to Indian Rivers executive committee, things went well, and they were congratulated on both their analysis and their presentation. However, several questions were raised. In particular, the executive committee wanted to see some type of risk analysis on the project it appeared to be profitable, but what were the chances that it might nevertheless turn out to be a loser, and how should risk be analyzed and worked into the decision process? As the meeting was winding down, Lili and Brent were asked to start with the base case situation they had developed and then to discuss risk analysis, both in general terms and as it should be applied to the lite orange juice project. To begin, Lili and Brent met with the marketing and production managers to get a feel for the uncertainties involved in the cash flow estimates. After several sessions, they concluded that there was little uncertainty in any of the estimates except for unit sales cost and sales price estimates were fairly well defined, but unit sales could vary widely. (In theory, unit sales price is also uncertain, but companies typically set sales prices on the basis of competitors prices, so, at least initially, it can be treated as certain.) As estimated by the marketing staff, if product acceptance were normal, then sales quantity during Year 1 would be 400,000 unit; if acceptance were poor, then only 220,000 units would be sold (the price would be kept at the forecasted level); and if consumer response were strong, then sales volume for Year 1 would be 620,000 units. In all cases, the price would increase at the inflation rate; hence, Year 1 revenues stated in Year 1 dollars, as they would appear on the cash flow statement, would be $840,000 under the expected conditions, they would be only $462,000 if things went badly, and they would amount to $1,302,000 if things went especially well. Cash costs per unit would remain at $1.50 before adjusting for inflation, so total cash operating costs in Year 1 would be approximately $612,000 under normal conditions, $336,600 in the worst-case scenario, and $948,600 in the best-case scenario. These costs would be expected to increase in each successive year at a 2 percent rate. Lili and Brent also discussed the scenarios probabilities with the marketing staff. After considerable debate, they finally agreed on a guesstimate of 25 percent probability of poor acceptance, 50 probability of average acceptance, and 25 percent probability of excellent acceptance. Lili and Brent also discussed with Victor Courtland, Indian Rivers director of capital budgeting, both the risk inherent in Indian Rivers average project and how the company typically adjusts for risk. Based on historical data, Indian River's average project has a coefficient of variation of NPV in the range of 0.50 to 1.00, and Courtland has been adding or subtracting 3 percentage points to the cost of capital to adjust for differential project risk. When Lili and Brent asked about the basis for the 3 percentage point adjustment, Courtland stated that the adjustment apparently had no basis except the subjective judgment of John Gerber, a former director of capital budgeting who was no longer with the company. Therefore, maybe the adjustment should be 2 percentage points, or maybe 5 points, or maybe some other number. The discussion with Courtland raised another issue: Should the project's cost of capital be based on its stand- alone risk, on its risk as measured within the context of the firm's portfolio of assets (within-firm, or corporate, risk), or in a market risk context? Indian River's target capital structure calls for 50 percent debt and 50 percent common equity, and the before-tax marginal cost of debt is currently 10 percent. Lili and Brent also determined that the T- bond rate, which they use as the risk- free rate, is 8 percent, and that the market risk premium is 6 percent. Since most members of Indian River's executive committee are unfamiliar with modern techniques of financial analysis, Lili and Brent planned to take a tutorial approach in the presentation. To structure the analysis, Lili and Brent developed the following set of questions, which they planned to ask and then answer as a method of presenting the analysis to the board. However, Lili and Brent contracted a contagious, though not fatal, viral infection. Neither will be able to attend the meeting. Therefore, you must make the presentation and answer any questions. Keep in mind that anyone on the board might interrupt you with a probing question at any time, so be sure you understand the logic, and the weaknesses, behind every technique you use and every statement you make. Questions 1. Assuming initially that the project has average risk, then develop a new table which shows a sensitivity analysis of NPV to sales quantity, salvage value, and the cost of capital. Assume that each of these variables can deviate from its base case, or expected value, by plus or minus 10 percent. See Table 2 for partial results. 3. Complete the scenario analysis initiated in Table 3. What is the worst case NPV? The best-case NPV? Use the worst-case most likely, and best-case NPVs, and their probabilities of occurrence, to find the project's expected NPV. 4. Indian River is also evaluating two different systems for disposing of wastes associated with another product, frozen grapefruit juice. Plan W requires more workers but less capital, while Plan C requires more capital but fewer workers. Both systems have an estimated 3-year life, but the one selected will probably be repeated at the end of its life into the foreseeable future. Since the waste-disposal choice has no impact on revenues, Lili and Brent think that the decision should be based on the relative costs of the two systems; these costs are set forth next (in thousands of dollars). The Year 0 costs represent the capital outlays. Expected Net Costs Year Plan W Plan C 0 1 2 3 ($2,000) (2,000) (2,000) (2,000) ($4,000) (1,200) (1,200) (1,200)

a. Assume initially that the two systems are both of average risk. Which one should be chosen?

b. Assume that the labor intensive Plan W is judged to be riskier than an average project, because future labor costs are very difficult to forecast, but Plan C is still of average risk, which one would you choose?

TABLE 2 Sensitivity Analysis Results Variable Change from NPV after change Base Level Quantity Salvage Value WACC -10% 0% +10%

TABLE 3 Scenario Analysis Results Scenario Probability NPV Worst 25% Most Likely 50% Best 25% Expected NPV =