# Exponential Moving Average (EMA)

Exponentially weighted moving average is a rolling moving average that puts more weight on current price. [Discuss] ðŸ’¬

```
// C# usage syntax (with Close price)
IEnumerable<EmaResult> results =
quotes.GetEma(lookbackPeriods);
```

## Parameters

`lookbackPeriods`

* int* - Number of periods (

`N`

) in the moving average. Must be greater than 0.### Historical quotes requirements

You must have at least `2Ã—N`

or `N+100`

periods of `quotes`

, whichever is more, to cover the convergence periods. Since this uses a smoothing technique, we recommend you use at least `N+250`

data points prior to the intended usage date for better precision.

`quotes`

is a collection of generic `TQuote`

historical price quotes. It should have a consistent frequency (day, hour, minute, etc). See the Guide for more information.

## Response

```
IEnumerable<EmaResult>
```

- This method returns a time series of all available indicator values for the
`quotes`

provided. - It always returns the same number of elements as there are in the historical quotes.
- It does not return a single incremental indicator value.
- The first
`N-1`

periods will have`null`

values since thereâ€™s not enough data to calculate.

âšž

Convergence warning: The first`N+100`

periods will have decreasing magnitude, convergence-related precision errors that can be as high as ~5% deviation in indicator values for earlier periods.

### EmaResult

`Date`

* DateTime* - Date from evaluated

`TQuote`

`Ema`

* double* - Exponential moving average

### Utilities

See Utilities and helpers for more information.

## Chaining

This indicator may be generated from any chain-enabled indicator or method.

```
// example
var results = quotes
.Use(CandlePart.HL2)
.GetEma(..);
```

Results can be further processed on `Ema`

with additional chain-enabled indicators.

```
// example
var results = quotes
.GetEma(..)
.GetRsi(..);
```