Sensitivity analysis models a variety of potential outcomes by using numerous what-if scenarios. The method, which makes a variety of assumptions about the variables, is used to assess alternative business options. Finding the variables that can have an abnormally substantial impact on the study’s results is a particularly useful feature of sensitivity analysis. The decision-maker can then assess the likelihood that the variables will change significantly. The result is a greater comprehension of the investment risks involved.
▪ Credibility: – Because the future cannot be anticipated, testing the financial model against a range of potential outcomes gives the results more credibility. Additionally, it boosts users’ confidence in the financial model.
▪ Flexibility: – A financial model’s underlying assumptions are what make it flexible. A sensitivity analysis reveals a variety of outputs that provide the model with more flexibility.
▪ Financial models are dynamic and can never be static: – There must be some degree of dynamism involved. One can gain insights into numerous circumstances by researching the interactions between independent factors and a small number of dependent variables. A financial model enables analysts to examine the situation and increase predictability, not merely to derive an output. Risk evaluation
▪ Risk evaluation
Assessing the underlying risk component also benefits from looking at how one variable depends on another. Various levels of risk are indicated by a material shift in the output’s value or a heightened dependency. The analyst can discover potential risk factors and take action to mitigate them with the aid of a sensitivity analysis.
▪ Making decisions
A sensitivity analysis aids in the process. The model is used by the decision-makers to determine how sensitive the output is to changes in various variables. The analyst may be able to derive useful findings and use this relationship to assist them to make the best judgments.
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