A simple moving average gives more weight to recent periods than older periods.

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BlackTom AI · Accepted Answer

Consider the statement about moving averages and how weighting works in a simple moving average.
Option 1: True. In many moving average methods, weights differ, but for a simple moving average all observations within the window are given equal weight. This means recent periods are not weighted more heavily than older ones; every data point in the defined window contributes equally to the average. Therefore, describing the simple moving average as giving more weight to recent periods is inaccurate.
Option 2: False. By definition, a simple moving average calculates the average of a fixed number of most recent observations with equal weights assigned to each one. While other types like exponential or weighted moving averages assign greater weight to more recent data, the simple variant treats all included observations identically, which contradicts the claim that recent periods are weighted more.
To further clarify, a simple moving average of length n sums the last n values and divides by n, so each of those n values has the same influence on the result. In contrast, an exponential moving average uses a decreasing exponential factor to give newer observations more influence, which is why this statement would be true for an exponential MA but not for the simple MA. In summary, the key distinction is equal weighting in the simple form versus weighted schemes that favor recent data in other MA types.

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A simple moving average gives more weight to recent periods than older periods.

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