get_keltner(quotes, ema_periods=20, multiplier=2.0, atr_periods=10)
||Iterable[Quote]||Iterable(such as list or an object having
• Need help with pandas.DataFrame?
||int, default 20||Number of lookback periods (
||float, default 2.0||ATR Multiplier. Must be greater than 0.|
||int, default 10||Number of lookback periods (
Historical quotes requirements
You must have at least
N+100 periods of
quotes, whichever is more, where
N is the greater of
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.
- This method returns a time series of all available indicator values for the
KeltnerResultsis 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.
Convergence warning: The first
N+250periods 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 band of Keltner Channel|
||float, Optional||EMA of Close price|
||float, Optional||Lower band of Keltner Channel|
||float, Optional||Width as percent of Centerline price.
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 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]