What is Sensitivity Analysis?

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Sensitivity Analysis

Sensitivity analysis is a financial tool to analyze the effect of a set of independent variables on a specific dependent variable under some given conditions. It is used in a wide range of applications, such as in biology and finance as well as economics.

The sensitivity analysis studies numerous sources of uncertainty that contribute to the forecast’s uncertainty by using what-if queries altogether. It is used within limited boundaries that rely on one or more inputs.

How Does It Work?

Also known as What-if analysis or simulation analysis, sensitivity analysis helps to ascertain some decisions depending on numerous independent variables.

  • For example, it can be used to derive how interest rates affect the bond prices and in making predictions about the share prices of the publicly traded companies.

  • Sensitivity analysis helps analysts to find which variables are more critical than others in affecting an outcome. Therefore, it can offer investors an insight into how different variables can affect their returns on investment. The analysts usually look at how the variables move as well as how the targets are affected by the input variables due to their movements.

  • Sensitivity analysis helps in forecasting using historical data, helping to make important decisions of business, economics, and finance decisions.

Advantages of Sensitivity Analysis

Sensitivity analysis is a well-established method to forecast a dependable outcome based on independent variables.

  • It can be used to answer a lot of queries that rely on the "what-if" principle. As it is an in-depth study, the predictions made by it are far more reliable than other methods.

  • It helps business owners to check the bottlenecks and improve their business processes by checking the actual point of issues. Therefore, it helps decision-makers to make decisions based on a scientific procedure that is more reliable and theoretically more established.

  • It is also quite simple to check and understand, and usually, the movement of any particular variable does not affect any particular outcome.

Disadvantages of Sensitivity Analysis

As is obvious, like all other forecasting procedures, Sensitivity Analysis is also not free from errors.

  • As forecasts are made within limited boundaries, the room for error in Sensitivity Analysis is magnified than other tools of investment.

  • There is a chance of a human error being included in the process.

Therefore, although a fairly simple and superior process to forecast some event depending on independent variables, Sensitivity Analysis is subject to correctness and human error that may null its advantages.

raja
Updated on 03-Dec-2021 11:32:22

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