Project Appraisal Under Risk

ACCA P3考試：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.

Method

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.*

Advantages

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.

Limitations

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.

2．Simulation

Stages in a Monte Carlo Simulation

1. Specify the major variables.

2. Specify the relationship between the variables.

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

4. Simulate the environment by generating random numbers.

5. Record the outcome of each simulation.

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

Advantages

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).

Limitations

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.