One potential problem with sensitivity analysis is that it generally looks at sensitivity "one variable at a time." However, one way to judge the sensitivity of results to simultaneous changes in two variables, at least, is to construct an.
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A. B. C. D.B
Sensitivity analysis is a financial analysis technique used to determine how changes in key variables will impact the outcome of a financial model. It involves adjusting one variable at a time while holding other variables constant to assess the impact on the financial result, such as net present value (NPV), internal rate of return (IRR), or payback period.
However, one potential problem with sensitivity analysis is that it only considers the impact of one variable at a time. In reality, multiple variables are likely to change simultaneously, and the combined effect of these changes can be different from the sum of the individual effects.
To address this issue, one way to judge the sensitivity of results to simultaneous changes in two variables is to construct an NPV sensitivity matrix. An NPV sensitivity matrix is a table that shows how changes in two variables affect NPV. It includes a range of values for each variable and shows the resulting NPV for each combination of values.
By analyzing the NPV sensitivity matrix, a financial analyst can identify the combinations of variables that have the greatest impact on NPV. This analysis can inform decision-making by highlighting the key variables that need to be monitored closely and by indicating which combinations of variables are most likely to result in a favorable or unfavorable outcome.
Therefore, option B, NPV sensitivity matrix, is the correct answer to this question.