The average valuation error. Analysts calculate an AVM’s mean error by totaling the percentage of variance for each value estimate in the sample and dividing by the number of returned valuations. This metric indicates the extent to which an AVM tends to overvalue or undervalue subject properties. For example, a mean error of 2.5 percent suggests that, on average, the model’s valuations overestimate properties’ market values by 2.5 percent.
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