Goldman Sachs Superday Practice Test 2026 – The Complete All-in-One Guide to Exam Success!

Sensitivity analysis asks what happens to the model’s outputs when you vary a key input. In a financial model, many inputs are uncertain—things like revenue growth, margins, capital expenditures, or the discount rate. By changing one assumption at a time while holding the others steady, you map out a range of possible results (such as NPV or IRR) and see how much those outputs swing.

This approach reveals which inputs really drive value and how robust the results are to uncertainty. It also helps with risk assessment and decision-making by showing both upside and downside scenarios and indicating where it’s worth refining data or adding buffers.

Choosing to ignore uncertain inputs, set all variables to zero, or only test best-case scenarios would give an incomplete or misleading view of risk and potential outcomes, instead of highlighting the true sensitivity of the model.