The mean absolute deviation is a measure of dispersion of a set of data points. It can be used in place of the standard deviation when the weight of outliers shall be reduced.

### Indicator Description

Calculation: The mean absolute deviation of the selected data set is the arithmetic mean of the absolute deviations from the arithmetic mean of the data set.

The mean absolute deviation is calculated from price data over the selected lookback period.

- We start with the calculation of a central tendency, such as the mean, median or mode of the selected input data.
- Next we find out how much the data points deviate from the central tendency and calculate the absolute differences dropping any negative signs.
- We take the absolute values of the differences and calculate the arithmetic mean.

The indicator which can be downloaded here is the mean absolute deviation around the mean, which is often referred to as the “mean absolute deviation”.

The mean absolute deviation is looking at the absolute differences where the standard deviation is calculating the squares of the differences. Hence large outliers will create a higher dispersion, when using the standard deviation instead of the mean absolute deviation.

The mean absolute deviation around the mean is always smaller than the standard deviation. When the data is normally distributed the standard deviation is about 1.2533 times the mean absolute deviation. The exact factor is obtained as the square root of π/2.

The indicator is available for NinjaTrader 8.