CandleFocus Glossary Editor
Sensitivity analysis is a forecasting method designed to assess the value of a dependent variable based on different values of an independent variable. It is also known as a what-if or simulation analysis. It is a powerful too that helps to understand the link between cost and output, particularly in terms of identifying cost-effective solutions and optimizing performance. The concept of sensitivity analysis also plays a key role in financial decision-making.
Sensitivity analysis can be used to help make predictions on the basis of historical or true data in different fields such as share prices of publicly traded companies, bond value, financial decision-making, cost and output, etc. It allows us to systematically explore multiple scenarios to determine the effects of a wide range of predictor variables on the performance of a financial model.
It is a fairly simple concept. The analysis computes the correlation between one or more independent variables such as price and demand, and assesses the corresponding effect of each, on a dependent variable such as profits. This correlation is expressed as a coefficient, and the higher that coefficient, the more sensitive the dependent variable is to the independent variable.
As sensitivity analysis enables us to understand the impact of varying an input parameter, it is an essential part of a business’s decision-making process, given the uncertainty that is inherent in all environment. When used, it highlights cost-effective solutions, thus enabling managers to take confident and informed decisions. Also, it plays a vital role in the forecasting process.
While sensitivity analysis can determine how different values of an independent variable affect a particular dependent variable under given set of assumptions, scenario analysis is a more advanced method that is used to assess the outcome of multiple scenarios.
In a nutshell, sensitivity analysis is a powerful tool that helps business to make sound and accurate forecasts by understanding cost and output. In order to gain more information on the full scope of such process and their complexity, most businesses turn to professional accountants and consultants.
Sensitivity analysis can be used to help make predictions on the basis of historical or true data in different fields such as share prices of publicly traded companies, bond value, financial decision-making, cost and output, etc. It allows us to systematically explore multiple scenarios to determine the effects of a wide range of predictor variables on the performance of a financial model.
It is a fairly simple concept. The analysis computes the correlation between one or more independent variables such as price and demand, and assesses the corresponding effect of each, on a dependent variable such as profits. This correlation is expressed as a coefficient, and the higher that coefficient, the more sensitive the dependent variable is to the independent variable.
As sensitivity analysis enables us to understand the impact of varying an input parameter, it is an essential part of a business’s decision-making process, given the uncertainty that is inherent in all environment. When used, it highlights cost-effective solutions, thus enabling managers to take confident and informed decisions. Also, it plays a vital role in the forecasting process.
While sensitivity analysis can determine how different values of an independent variable affect a particular dependent variable under given set of assumptions, scenario analysis is a more advanced method that is used to assess the outcome of multiple scenarios.
In a nutshell, sensitivity analysis is a powerful tool that helps business to make sound and accurate forecasts by understanding cost and output. In order to gain more information on the full scope of such process and their complexity, most businesses turn to professional accountants and consultants.