get_starc_bands(quotes, sma_periods=20, multiplier=2.0, atr_periods=10)
||Iterable[Quote]||Iterable(such as list or an object having
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||int, default 20||Number of lookback periods (
||float, default 2.0||ATR Multiplier. Must be greater than 0. Default is 2.|
||int, default 10||Number of lookback periods (
Historical quotes requirements
You must have at least
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.
- This method returns a time series of all available indicator values for the
STARCBandsResultsis just a list of
- 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-1periods will have
Nonevalues since there’s not enough data to calculate, where
Nis the greater of
Convergence warning: The first
A+150periods will have decreasing magnitude, convergence-related precision errors that can be as high as ~5% deviation in indicator values for earlier periods.
||float, Optional||Upper STARC band|
||float, Optional||SMA of Close price|
||float, Optional||Lower STARC band|
See Utilities and Helpers for more information.
from stock_indicators import indicators # This method is NOT a part of the library. quotes = get_history_from_feed("SPY") # Calculate StarcBands(20) results = indicators.get_starc_bands(quotes, 20, 2.0, 10)
About STARC Bands
Created by Manning Stoller, Stoller Average Range Channel (STARC) Bands, are based on an SMA centerline and ATR band widths. See also Keltner Channels for an EMA centerline equivalent. [Discuss]