Point estimate
A single figure offered as the best estimate of an unknown quantity. On its own it says nothing about how uncertain that estimate is, which is what an interval is for.
Where you will meet it
Point estimate appears in 4 learning outcomes on the CFA syllabus. A few of them:
- Set out what the Gordon growth model takes for granted and how sensitive its output is to inputs
“Sensitivity is therefore extreme precisely where the inputs are least certain, which is why the model is used for stable mature payers and why a sensitivity table matters more than a point estimate.”
- Explain Monte Carlo simulation and what it is used for
“Monte Carlo simulation generates many random draws from assumed distributions for the uncertain inputs of a model, computes the outcome for each, and uses the resulting distribution of outcomes to answer questions a single point estimate cannot.”
- Explain how sensitivity analysis is used in FCFF and FCFE valuation
“The trap is presenting a single point estimate as precise when a plausible change in one input shifts value by a large fraction.”
- Apply a regression model to produce a forecast
“The point estimate is only half the answer; a prediction interval around it reflects both the scatter of the data and the uncertainty in the estimated coefficients, and it widens as the chosen x moves away from the mean of the sample.”
Practise it
Practise point estimate until it is automatic: questions that explain every wrong option.
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