HGROWTH is the name of the function that calculates the average annualized growth rate of a sequence of data. This could be sales per share or earnings per share.

For example, the HGROWTH of the earnings per share figures

1.0, 1.1, 1.2, 1.4, 1.6 is 12.56 percent.

This means that on average the earnings per share are growing by 12.56 percent each year.

In contrast to the conventional method of calculating average growth rate, **all** the numbers in the sequence are included in the calculation. In the conventional method only the first and last numbers are used.

For example, if we drop the second number in the sequence from 1.1 to 0.9 to get the sequence

1.0, 0.9, 1.2, 1.4, 1.6

then the HGROWTH becomes 14.87 percent. The higher figure is because the numbers are growing from a lower base. However, if we use the standard method for calculating growth there would be no difference between the growths for the two sequences.

You can remember the name by thinking __H__istorical __GROWTH__.

**Benefits of HGrowth**

Starting with the fact that it uses all the data points, there a number of benefits of HGrowth

compared to the standard method of using only the first and last points.

- All the data points are used.
- More emphasis is given to more recent data.
- Adjustments are made to allow the incorporation of negative data points.
- Adjustments are made for extreme outliers and data points near 0. Without this, in both cases such points can overly influence the rate of return.