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Capital budgeting in uncertainty


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Лекц 10 Capital budgeting in uncertainty

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Capital budgeting in uncertainty

  1. 1. Capital Budgeting in Uncertainty
  2. 2. Sensitivity Analysis, Scenario Analysis, and Break-Even Analysis  Allows us to look behind the NPV number to see how firm our estimates are  When working with spreadsheets, try to build your model so that you can just adjust variables in a few cells and have the NPV calculations respond to that
  3. 3. Sensitivity Analysis: Baldwin Company  We can see that NPV is very sensitive to changes in price  In the Baldwin Company example, a 10% drop in price leads to a 82% drop in NPV  For every 1% drop in price we can expect roughly a 8.2% drop in NPV
  4. 4. Scenario Analysis: Baldwin Company   A variation on sensitivity analysis is scenario analysis. For example, the following three scenarios could apply to Baldwin Company: 1. 2. 3.  In the next years bowling becomes very popular because of a blockbuster movie showing it as a cool and hip pastime for young people. The next years are normal and sales meet expectations. The next years see a 3 D computer graphics breakthrough introducing a virtual form of bowling that begins to compete with the physical version. For each scenario, calculate the NPV.
  5. 5. Break-Even Analysis: Baldwin Company  Another way to examine variability in our forecasts is break-even analysis  In the Stewart Pharmaceuticals example, we could be concerned with break-even sales volume or break-even price  To find either, we need to find the level of sales volume or price at which NPV becomes zero
  6. 6. Monte Carlo Simulation  Monte Carlo simulation is a further attempt to model real-world uncertainty  Monte Carlo simulation of capital budgeting projects is often viewed as a step beyond either sensitivity analysis or scenario analysis  Replace deterministic point estimates with probabilistic range estimates
  7. 7. Monte Carlo Simulation (contd.)  Run large number of iterations  For each iteration a random number is picked for each of the variables modeled probabilistically  For each iteration, NPV is calculated  Based on all iterations, a probability distribution of NPV is obtained  Different levels of NPV at different confidence levels instead of a single NPV number