cmo#

cmo(close, length=None, scalar=None, talib=None, drift=None, offset=None, **kwargs)[source]#

Chande Momentum Oscillator (CMO)

Attempts to capture the momentum of an asset with overbought at 50 and oversold at -50.

Sources:

https://www.tradingtechnologies.com/help/x-study/technical-indicator-definitions/chande-momentum-oscillator-cmo/ https://www.tradingview.com/script/hdrf0fXV-Variable-Index-Dynamic-Average-VIDYA/

Calculation:

Default Inputs:: drift=1, scalar=100

# Same Calculation as RSI except for this step CMO = scalar * (PSUM - NSUM) / (PSUM + NSUM)

Args:

close (pd.Series): Series of ‘close’s scalar (float): How much to magnify. Default: 100 talib (bool): If TA Lib is installed and talib is True, Returns the TA Lib

version. If TA Lib is not installed but talib is True, it runs the Python version TA Lib. Default: True

drift (int): The short period. Default: 1 offset (int): How many periods to offset the result. Default: 0

Kwargs:

talib (bool): If True, uses TA-Libs implementation. Otherwise uses EMA version. Default: True fillna (value, optional): pd.DataFrame.fillna(value) fill_method (value, optional): Type of fill method

Returns:

pd.Series: New feature generated.