STARC Bands

get_starc_bands(quotes, sma_periods=20, multiplier=2.0, atr_periods=10)

Parameters

name	type	notes
`quotes`	Iterable[Quote]	Iterable(such as list or an object having `__iter__()`) of the Quote class or its sub-class. • Need help with pandas.DataFrame?
`sma_periods`	int, default 20	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. Default is 2.
`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`. Default is 10.

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_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]