Goldman Sachs Superday Practice Test

Sensitivity analysis in a financial model shows how much outputs change when you vary the inputs. By tweaking key assumptions within realistic ranges, you see how metrics like net present value or internal rate of return move and which inputs drive the outcome. This helps with risk assessment and decision making because you learn which assumptions matter most and where to focus data validation or contingency planning. For example, if NPV changes a lot when revenue growth varies, that input is a critical driver and deserves close scrutiny. If changing the discount rate has little effect, that factor is less influential. This approach reveals potential ranges and the factors shaping them, rather than asserting exact numbers; it’s not about replacing uncertain inputs with single estimates, nor about eliminating risk by assuming no changes.