We can get a sense of how model output responds to changes in inputs from sensitivity analyses. Some argue that we might draw very different conclusions when using different boundaries, especially when model output is a non-linear function of inputs. For example, we compute the net present value (NPV) of a business with a 10% discount rate. We can choose +/- 1% for our sensitivity analysis, or +/-5% for our analysis. For this reason, some argue that one can manipulate sensitivity analysis to support one’s prior. What do you think of this comment?
We can get a sense of how model output responds to changes in inputs from sensitivity analyses. Some argue that we might draw very different conclusions when using different boundaries, especially when model output is a non-linear function of inputs. For example, we compute the net present value (NPV) of a business with a 10% discount rate. We can choose +/- 1% for our sensitivity analysis, or +/-5% for our analysis. For this reason, some argue that one can manipulate sensitivity analysis to support one’s prior. What do you think of this comment?
Essentials Of Investments
11th Edition
ISBN:9781260013924
Author:Bodie, Zvi, Kane, Alex, MARCUS, Alan J.
Publisher:Bodie, Zvi, Kane, Alex, MARCUS, Alan J.
Chapter1: Investments: Background And Issues
Section: Chapter Questions
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- We can get a sense of how model output responds to changes in inputs from sensitivity analyses. Some argue that we might draw very different conclusions when using different boundaries, especially when model output is a non-linear function of inputs. For example, we compute the
net present value (NPV) of a business with a 10% discount rate. We can choose +/- 1% for our sensitivity analysis, or +/-5% for our analysis. For this reason, some argue that one can manipulate sensitivity analysis to support one’s prior. What do you think of this comment?
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