What is Sensitivity Analysis?
Sensitivity Analysis is a tool used in financial modelling to analyse how the different values of a set of independent variables affect a specific dependent variable under certain conditions. In general, sensitivity analysis is used in various fields, ranging from biology and geography to economics and engineering.
It is instrumental in studying and analysing a “Black Box Process” where the output is an opaque function of several inputs. An opaque function or process is one that, for some reason, can’t be studied and analysed. For example, climate models in geography are usually very complex. As a result, the exact relationship between the inputs and outputs is not well understood.
A Financial Sensitivity Analysis, also known as a What-If analysis or a What-If simulation exercise, is most commonly used by financial analysts to predict the outcome of a specific action when performed under certain conditions.
Financial Sensitivity Analysis is done within defined boundaries determined by the set of independent (input) variables.
For example, sensitivity analysis can study the effect of a change in interest rates on bond prices if the interest rates increase by 1%. The “What-If” question would be: “What would happen to the price of a bond If interest rates went up by 1%?”. This question can be answered with sensitivity analysis.
The analysis is performed in Excel, under the Data section of the ribbon and the “What-if Analysis” button, which contains both “Goal Seek” and “Data Table”.
Advantages of Financial Sensitivity Analysis
There are many important reasons to perform sensitivity analysis:
- Sensitivity analysis adds credibility to any type of financial model by testing the model across a broad set of possibilities.
- Financial Sensitivity Analysis allows the analyst to be flexible with the boundaries within which to test the sensitivity of the dependent variables to the independent variables. For example, the model to study the effect of a 5-point change in interest rates on bond prices would be different from the financial model used to study the impact of a 20-point shift in interest rates on bond prices.
- Sensitivity analysis helps one make informed choices. Decision-makers use the model to understand how responsive the output is to changes in certain variables. Thus, the analyst can help derive tangible conclusions and be instrumental in making optimal decisions.
Sensitivity Analysis vs Scenario Analysis
It is important not to confuse Financial Sensitivity Analysis with Financial Scenario Analysis. Although similar to some degree, the two have some key differences.
Sensitivity Analysis is used to understand the effect of a set of independent variables on some dependent variable under certain specific conditions. For example, a financial analyst wants to determine the impact of a company’s net working capital on its profit margin. The analysis will involve all the variables that impact the company’s profit margin, such as the cost of goods sold, workers’ wages, managers’ wages, etc. The analysis will isolate these fixed and variable costs and record all the possible outcomes.
Scenario Analysis, on the other hand, requires the financial analyst to examine a specific scenario in detail. Scenario Analysis is usually done to analyse situations involving major economic shocks, such as a global market shift or a significant change in the nature of the business.
After specifying the details of the scenario, the analyst would then have to specify all of the relevant variables so that they align with the scenario. The result is a comprehensive picture of the future (a discrete scenario). The analyst would know the full range of outcomes, given all the extremes, and understand what the various outcomes would be, given a specific set of variables defined by one particular real-life scenario.