SENSITIVITY ANALYSIS

All feasibility studies and valuations using the DCF approach to measure the rate of return should be subject to a sensitivity analysis. This will determine the most important variables in the cash flow and show their comparative rate of change. The normal sensitivity analysis adjusts the subject variable by +/- 10%. The resulting NPV or IRR using the equated yield model is recorded in a table or on a graph to show the sensitivity in terms of absolute amounts or slope of line. All other variables are held equal. The most commonly analyzed variables are:

FEASIBILITY STUDIES
• Purchase price or land value
• Cost of construction
• Length of development period
• End market value
EXISTING INVESTMENT PROPERTIES
• Purchase price
• End market value
• Rental income (this can also be use to measure different vacancy rates).
• End market value + rental income.
TABLE SENSITIVITY ANALYSIS FOR AN INVESTMENT REPORT OVER SUBJECT PROPERTY

The equated yield rates of return are used to determine the investment's sensitivity:

 VARIABLE VALUE CHANGE +10% -10% PURCHASE PRICE: 9.08% 14.28% END MARKET VALUE: 13.20% 9.69% RENTAL INCOME ONLY: 12.34% 10.68% RENTAL INCOME + END MARKET VALUE: 14.01% 8.83%

The sensitivity analysis shows that the risk to investment is greatest with a change in rental income which in turn affects the expected end market value. The next most important single variable is the purchase price which is slightly more sensitive than the end market value. Rental income during the 5 year period is not a very sensitive variable at all. The above results are better shown on a graph where the sensitivity of each variable can be observed by it's slope. The steeper the slope, the more sensitive is the variable - see diagram below:

DIAGRAM SLOPES OF VARIABLES - SENSITIVITY ANALYSIS

SCENARIOS

As the sensitivity analysis shows, forecasting error can effect both the feasibility of a project or the value of an existing building. Therefore, in any situation where the result or value will vary greatly due to forecasting error it is better for the valuer not to determine a final answer but instead, provide 3 answers according to the following scenarios:
• Expected (E)
• Optimistic (O)
• Pessimistic (P)
EXPECTED SCENARIO

The expected scenario is the market's forecast that is, the cash flow is constructed using data analysed from comparable sales. Where land values are determined from such a DCF they are market values.

OPTIMISTIC SCENARIO

The optimistic scenario is that cash flow constructed according to a 10% increase in rental income and expected end market value. Therefore, the optimistic scenario in the DCF will determine the highest land value, above market value.

PESSIMISTIC SCENARIO

The pessimistic scenario is that cash flow which incorporates a 10% decrease in rental income and expected end market value. Therefore, the pessimistic scenario will provide the lowest land value, below market value. Some valuers combine a number of variable changes in the scenario for example, purchase price, rental income and end market value. However, this can result in scenarios which are extremely unlikely and will determine extreme values. A single statistic can be calculated for comparison purposes by using the PERT formula:

PERT = (O+4E+P)/4