Keltner Channels
get_keltner(quotes, ema_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 subclass. • Need help 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 ofKeltnerResult
.  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
N1
periods will haveNone
values since there’s not enough data to calculate.
Convergence warning: The first
N+250
periods will have decreasing magnitude, convergencerelated 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_bandlower_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_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]