Forecasting Sales Using Trend Models

A financial analyst is examining quarterly sales data for a tech company over the past five years to forecast future sales. The analyst applies a linear trend model to the historical data, which resulted in the following regression equation:

$Sales_t = 200 + 15(t) + e_t$

where $Sales_t$ represents sales in quarter $t$, $t$ is the time in quarters since the start of the data collection, and $e_t$ is the error term.

Based on this model, the analyst wants to estimate sales for the next three quarters ($t = 21, 22, 23$). Given this information, the analyst considers two possible adjustments to the model:

• An adjustment for seasonality by adding a seasonal component to the forecasted values based on the last year's data, which indicated significant seasonal variations.

• A reduction in the slope coefficient by 20% to account for economic changes affecting growth rates in the tech sector.

What would be the most appropriate course of action for the analyst when making forecasts for the upcoming quarters?