CFA Level I · CFA Level I Exam · Applications of Simple Linear Regression in Finance
An analyst fits a log-lin trend model to quarterly sales: ln(Sales) = 4.60 + 0.025 × t, where t = 1 for the first quarter of the sample. Sales in millions are forecast for t = 9. Using exp(4.825) ≈ 124.6, the forecast is closest to:
The predicted log of sales at t = 9 is 4.60 plus 0.025 times 9, or 4.825. Converting back by exponentiating gives about 124.6 million. Reporting 4.8 would leave the forecast in logs, which is not a sales figure.
- A100.0 million.
- B124.6 million.Correct
- C4.8 million.
Explanation
Predicted ln(Sales) = 4.60 + 0.025 × 9 = 4.825. Sales must be converted back from the log scale: exp(4.825) ≈ 124.6 million. The 4.8 option reports the log value without exponentiating. The 100.0 figure is exp(4.60), which is the intercept alone and ignores the trend term.
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