ACCA P3考试:Project Appraisal Under Risk

1. Sensitivity Analysis

Sensitivity analysis—the analysis of changes made to significant variables in order to determine their effect on a planned course of action.


Sensitivity analysis has TWO steps:

Step 1 Calculate the NPV of the project on the basis of best estimates.

Step 2 For each element of the decision (cash flows, cost of capital), calculate the change necessary for the NPV to fall to zero.*


---It gives an idea of how sensitive the project is to changes in any of the original estimates.

---It directs management attention to checking the quality of data for the most sensitive variables.

---It identifies the critical success factors for the project and directs project management.

---It can be easily adapted for use in spreadsheet packages.


Although it can be adapted to deal with multi-variable changes, sensitivity analysis is normally used to examine what happens when one variable changes and others remain constant.

It assumes data for all other variables is accurate. Without a computer, it can be time-consuming. Probability of changes is not considered.


Stages in a Monte Carlo Simulation

---Specify the major variables.

---Specify the relationship between the variables.

---Attach probability distributions to each variable and assign random numbers to reflect the distribution.

---Simulate the environment by generating random numbers.

---Record the outcome of each simulation.

---Repeat the simulation many times to obtain a probability distribution of the possible outcomes.


---It gives more information about the possible outcomes and their relative probabilities.

----This data can be used to calculate an expected NPV (and the standard deviation of the expected NPV).


---It is not a technique for making a decision, only for obtaining more information about the possible outcomes.

---It can be very time-consuming without a computer.

---It could prove expensive in designing and running the simulation, even on a computer.

---Simulations are only as good as the probabilities, assumptions and estimates used.