# Exponential Moving Average

The **Exponential Moving Average**, or exponentially weighted moving average (EWMA), function computes the average of a set of input values over a specified number of periods. In this function, a greater weight is given to more recent data. This function can be used to smooth a data series, which helps to reduce noise and make it easier to spot data trends.

The mathematical formula being calculated is as follows:

EWMA_{t}= λY_{t}+ (1 – λ)EWMA_{t-1}

for t = 1, 2, ..., n.

Where EWMA0 is the mean of historical data, Y is the value, n is the number of periods, and λ is the weight constant, which is set to 2 / (n +1). You can find more information from the National Institute of Standards and Technology.

## 1. Syntax

EXPMOVAVG(d0,s0,Alignment)

## 2. Input

The Exponential Moving Average function requires the following input:

- d0 - The set of data values for which the Exponential Moving Average is calculated.

## 3. Parameters

The Exponential Moving Average function requires the following parameters:

- s0 - The number of periods to use in the calculation. The default value is 10.
- Alignment (Optional) – Hierarchy placeholder to be used as the alignment axis.

## 4. Output

The Exponential Moving Average function generates the following output:

- Exponential Moving Average - The Exponential Moving Average result set.