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Technical Studies Reference

Moving Average - Move-Adjusted

This study calculates and displays a Move-Adjusted Moving Average of the data specified by the Input Data Input. This moving average is taken from an article entitled "Weight + Volume + Move-Adjusted Moving Average: It's WEVOMO!" by Stephan Bisse in the April 2005 issue of Stocks & Commodities.

Let \(X\) be a random variable denoting the Input Data, and let \(X_t\) be the value of the Input Data at Index \(t\). Let the Input Length be denoted as \(n\). Then we denote the Moving Average - Move-Adjusted at Index \(t\) for the given Inputs as \(MOMA_t(X,n)\), and we compute it for \(t \geq n - 1\) as follows.

\(\displaystyle{MOMA_t(X,n) = \left\{ \begin{matrix} \frac{\sum_{i = t - n + 1}^t X_i \cdot \left|X_i - X_{i - 1}\right|}{\sum_{i = t - n + 1}^t \left|X_i - X_{i - 1}\right|} & \sum_{i = t - n + 1}^t \left|X_i - X_{i - 1}\right| \neq 0 \\ X_t & \sum_{i = t - n + 1}^t \left|X_i - X_{i - 1}\right| = 0 \end{matrix}\right .}\)

For an explanation of the Sigma (\(\Sigma\)) notation for summation, refer to our description here.



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*Last modified Tuesday, 27th September, 2022.