What distinguishes a weighted moving average from a simple moving average?

A weighted moving average distinguishes itself from a simple moving average primarily by assigning different weights to each period's data point. In a simple moving average, each data point within the selected time frame is treated equally, meaning they are all assigned the same weight when calculating the average.

On the other hand, a weighted moving average allows analysts to emphasize certain data points more than others, typically giving more importance to recent observations. This is particularly useful in scenarios where the most recent data is deemed more relevant for forecasting future trends or performance. By doing so, the weighted moving average can provide a more nuanced perspective on data trends, effectively capturing shifts that may be missed by a simple moving average.