Sensitivity analysis determines how different values of an independent variable affect a particular dependent variable under a given set of assumptions. In other words, sensitivity analyses study how various sources of uncertainty in a mathematical model contribute to the model’s overall uncertainty. This technique is within specific boundaries that depend on one or more input variables.
Sensitivity analysis is in the business world and the field of economics. It is commonly by financial analysts and economists and is also as a what-if analysis.
Sensitivity analysis is a financial model that determines how target variables are affected based on changes in other variables known as input variables. It is a way to predict the outcome of a decision given a certain range of variables. By creating a given set of variables, an analyst can determine how changes in one variable affect the outcome.
Both the target and input—or independent and dependent—variables are fully analyzed when sensitivity analysis is conducted. The person doing the analysis looks at how the variables move. As well as how the target is by the input variable.
Sensitivity analysis can to help make predictions about the share prices of public companies. Some of the variables that also affect stock prices include company earnings. The number of shares outstanding, the debt-to-equity ratios (D/E), and the number of competitors in the industry. The analysis can about future stock prices by making different assumptions or adding different variables. This model can also to determine the effect that changes in interest rates have on bond prices. In this case, the interest rates are the independent variable, while bond prices are the dependent variable.
Sensitivity analysis allows for forecasting using historical, true data. By studying all the variables and also the possible outcomes. Important decisions can about businesses, the economy, and making investments.