What is a Sensitivity Analysis in Finance? Check Sensitivity Analysis Statistics

Key Takeaways: 
 

• Sensitivity analysis is one of the most important components to check how one small change in the input can affect the whole result. 
   
• This approach is used in various sectors such as finance, business, and forecasting. 
   
• The sensitivity analysis statistics help us understand the risk and uncertainty before it happens. Many organisations use the sensitivity analysis formula for risk evaluation. 
   
• The sensitivity analysis helps businesses make smarter and more realistic plans. 

Do you remember going to school to pick up your final result after your exams? As soon as you receive your report card, the first thing you notice is the percentage you achieved. But if you have done an average in one subject, the whole percentage can be affected, even if you did well in others. 

Similarly, this approach also works in businesses and the financial market. Even a tiny change in numbers can completely change the overall outcome. You miscalculate one digit and suddenly notice how profit is different, and risk looks much higher. 

We didn’t have the choice of analysing our results during school time, but in the financial market, we do have a choice. What if I tell you that you test different situations before making the decision? I think this will be a better option, instead of randomly guessing outcomes. 

A simple analysis can change your future outcome, which sounds amazingly crazy. It does not predict the future, but it will definitely prepare you for one. If you also want to know how this can be done, scroll down and check the complete process. 

What is a Sensitivity Analysis in Finance? 

Sensitivity analysis statistics show how various values of an independent variable can affect a dependent variable under certain circumstances. This approach is used by different organisations to identify opportunities, mitigate risk, and communicate decisions to upper management. This analysis is performed by well-known financial analysts and economists, and is also known as “What-if” analysis. 

In simple words, the sensitivity analysis is a method used to evaluate how small changes in one variable can affect the whole outcome. 

Here, this means:

1. If the cost increases, the profit will fall
2. If the sales increase, the profit may rise

This is the simplest explanation you will find of sensitivity analysis. This method is often used when businesses sense uncertainty and want to test various possibilities before making any move. 

Bonus Tip: As per the research of Andrea Saltelli, 96% of sensitivity analyses published in scientific journals are wrong. Satelli mentioned that many researchers construct incorrect analysis as they overlook factors that are considered well-known in statistics.

Calculation Using Sensitivity Analysis Formula

Unlike most of the financial tools, the sensitivity analysis formula is not fixed. So, how will it be calculated perfectly? This does not need a perfect calculation. The trick here is to make changes in certain inputs and check how the outcome changes completely. You can also use this formula to do the same. 

New Output = Base Output × ( 1 + Change in Input )

Basically, 

 

1. You pick out one input, it can be anything, such as sales or even costs. 
2. Make changes to the same by a fixed percentage, like +10% or -10%, as per your needs. 
3. Once you do the calculations, you will notice how the final result changes completely. 

Meaning, if the profit is based on the revenue and it increases by 10%, then the new profit will also increase as per the changes. However, sensitivity analysis in business does not only have tests on one case, but they also create various base cases, downside cases, and worst cases for the same numbers. This helps companies check if they can work under extreme pressure and still make safer decisions. 

Methods of Evaluating Global Sensitivity Analysis 

This type of analysis is done when multiple inputs are fluctuating at the same time. The global analysis helps us understand how each one of them affects the final result. Instead of evaluating one factor at a time, it calculates the combined effect of all variables together.  

Meaning: Y = f ( X1, X2,......, Xp) 

The output that appears will depend on various inputs working together. Through this, the analysis will be more realistic for real-life situations. 

The sensitivity analysis for the global approach includes various methods, which are: 

RBD / FAST-RBD

Make the FAST easier, while ensuring accuracy.

Derivative-based

Morris

Test small input changes and identify useful variables. 

Derivative-based

DGSM

Measures input influence using the rate of change.