kc#
API documentation for pandas_ta.volatility.kc Python function.
- kc(high, low, close, length=None, scalar=None, mamode=None, offset=None, **kwargs)[source]#
Keltner Channels (KC)
A popular volatility indicator similar to Bollinger Bands and Donchian Channels.
- Sources:
- Calculation:
- Default Inputs:
length=20, scalar=2, mamode=None, tr=True
TR = True Range SMA = Simple Moving Average EMA = Exponential Moving Average
- if tr:
RANGE = TR(high, low, close)
- else:
RANGE = high - low
- if mamode == “ema”:
BASIS = sma(close, length) BAND = sma(RANGE, length)
- elif mamode == “sma”:
BASIS = sma(close, length) BAND = sma(RANGE, length)
LOWER = BASIS - scalar * BAND UPPER = BASIS + scalar * BAND
- Args:
high (pd.Series): Series of ‘high’s low (pd.Series): Series of ‘low’s close (pd.Series): Series of ‘close’s length (int): The short period. Default: 20 scalar (float): A positive float to scale the bands. Default: 2 mamode (str): See
`help(ta.ma)`. Default: ‘ema’ offset (int): How many periods to offset the result. Default: 0- Kwargs:
- tr (bool): When True, it uses True Range for calculation. When False, use a
high - low as it’s range calculation. Default: True
fillna (value, optional): pd.DataFrame.fillna(value) fill_method (value, optional): Type of fill method
- Returns:
pd.DataFrame: lower, basis, upper columns.