# Keltner Channels

get_keltner(quotes, ema_periods=20, multiplier=2.0, atr_periods=10)

## Parameters

name | type | notes |
---|---|---|

`quotes` | Iterable[Quote] | Iterable of the Quote class or its sub-class. • See here for usage with pandas.DataFrame |

`ema_periods` | int, default 20 | Number of lookback periods (`E` ) for the center line moving average. Must be greater than 1 to calculate. |

`multiplier` | float, default 2.0 | ATR Multiplier. Must be greater than 0. |

`atr_periods` | int, default 10 | Number of lookback periods (`A` ) for the Average True Range. Must be greater than 1 to calculate. |

### Historical quotes requirements

You must have at least `2×N`

or `N+100`

periods of `quotes`

, whichever is more, where `N`

is the greater of `E`

or `A`

periods, 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 an `Iterable[Quote]`

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

## Return

```
KeltnerResults[KeltnerResult]
```

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

provided. `KeltnerResults`

is just a list of`KeltnerResult`

.- 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`None`

values since there’s not enough data to calculate.

⚞

Convergence warning: The first`N+250`

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

### KeltnerResult

name | type | notes |
---|---|---|

`date` | datetime | Date |

`upper_band` | float, Optional | Upper band of Keltner Channel |

`center_line` | float, Optional | EMA of Close price |

`lower_band` | float, Optional | Lower band of Keltner Channel |

`width` | float, Optional | Width as percent of Centerline price. `(upper_band-lower_band)/center_line` |

### Utilities

See Utilities and Helpers for more information.

## Example

```
from stock_indicators import indicators
# This method is NOT a part of the library.
quotes = get_historical_quotes("SPY")
# Calculate Keltner(20)
results = indicators.get_keltner(quotes, 20,2.0,10)
```

## About Keltner Channels

Created by Chester W. Keltner, Keltner Channels are based on an EMA centerline and ATR band widths. See also STARC Bands for an SMA centerline equivalent. [Discuss] 💬