Log-linear trend
A trend model of the log of a series, ln y = b0 + b1 × t, implying growth at a constant rate. Forecasts are converted back to the original units by raising e to the fitted value.
Where you will meet it
Log-linear trend appears in 2 learning outcomes on the CFA syllabus. A few of them:
- Work out a trend forecast for a time series, whether fitted as a linear or a log-linear trend, from given trend coefficients, and judge the result
“A log-linear trend regresses the natural log of the series on t instead, so the series grows at a constant rate and the forecast, converted back from logs, is y = e^(b0 + b1 × t).”
- Explain what decides the choice between a linear and a log-linear trend for a given series, and assess where trend models fall short
“If it compounds at a roughly constant rate, its plot curves upward, and a linear trend leaves residuals that are positive at both ends and negative in the middle, so a log-linear trend is better.”
Practise it
Practise log-linear trend until it is automatic: questions that explain every wrong option.
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