4. Sensitivity and scenario analysis Different techniques for analyzing project risk require different input variables and assumptions. Suppose you are using the scenario analysis technique to evaluate project risk. You would change several input variables together in the model to evaluate the effect of the input factors on the expected value. Paloma is a risk analyst. She is conducting a sensitivity analysis to evaluate the riskiness of a new project that her company is considering investing in. Her risk analysis report includes the sensitivity curve shown on the graph. NPV Millions of dollars) - Base Case NPV Base Case Units Sold -20 -15 -10 -5 0 5 10 15 20 CHANGE IN UNITS SOLD (Percent) This curve implies that the project is very sensitive to changes in units sold. The project's NPV is likely to become negative if the number of units sold decreases by 10% Along with the sensitivity analysis, Paloma is including a scenario analysis for the project in her report, giving the probability of the project generating a negative NPV. Her report includes the following information about the scenar analysis: Data Collected 0.4 Outcome Pessimistic Most likely Optimistic Probability (Pi) 0.50 0.35 0.15 NPV; -52.31 million $4.53 million $12.11 million 0.6 Probability Data for z 0.03 0.06 0.09 0.3336 0.3228 0.3121 0.26430.2546 0.2451 0.2033 0.1949 0.1867 0 .1515 0.1446 0.1379 0.8 1. 0 Complete the missing information in Paloma's report: The expected net present value of the project is million. Standard deviation of the net present value (the NPV of the project is likely to vary by) Assuming that probability distribution is normal, the value of zis 5.39 6.35 5.18 5.66 Thus, the project has a chance to generate an NPV of less than 50