# STARC Bands

get_starc_bands(quotes, sma_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 |

`sma_periods` | int | Number of lookback periods (`S` ) for the center line moving average. Must be greater than 1 to calculate and is typically between 5 and 10. |

`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 and is typically the same value as `sma_periods` . |

### Historical quotes requirements

You must have at least `S`

or `A+100`

periods of `quotes`

, whichever is more, to cover the convergence periods. Since this uses a smoothing technique, we recommend you use at least `A+150`

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

```
STARCBandsResults[STARCBandsResult]
```

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

provided. `STARCBandsResults`

is just a list of`STARCBandsResult`

.- 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, where`N`

is the greater of`S`

or`A`

.

⚞

Convergence warning: The first`A+150`

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

### STARCBandsResult

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

`date` | datetime | Date |

`upper_band` | float, Optional | Upper STARC band |

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

`lower_band` | float, Optional | Lower STARC band |

### 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 StarcBands(20)
results = indicators.get_starc_bands(quotes, 20, 2.0, 10)
```

## About STARC Bands

Created by Manning Stoller, the Stoller Average Range Channel (STARC) Bands, are price ranges based on an SMA centerline and ATR band widths. See also Keltner Channels for an EMA centerline equivalent. [Discuss] 💬