t3MovingAverage.py

def t3MovingAverage(period,data,vfactor=0.7,tcount=3):

    #--- T3 Moving Average 
    # data: array, time series data e.g. daily close prices.
    # period: integer, number of periods form time series array to include in calculation.
    # vfactor: float, number between 1 and 0. 1 = DEMA, 0 = EMA. default 0.7.
    # tcount: integer, number 1 or greater. times the data is smoothed with the generalisedDEMA. default 3 (T3).
    #
    # requires numpy and techind libraries
    #
    # see below link for maintained code
    # https://github.com/codersnotepad/techind/blob/master/techind/t3MovingAverage.py
    
    import numpy as np
    import techind as ti
    
    #---Generalised DEMA (GD)
    def generalisedDEMA(period,data,vfactor):

        ema1 = ti.exponentialMovingAverage(period,data)
        ema2 = ti.exponentialMovingAverage(period,ema1)

        # GD = EMA(period,data) x (1+vfactor) - EMA(periodT3,EMA(period,data)) x vfactor
        return ema1 * (1 + vfactor) - (ema2 * vfactor)
    
    #---Calculate smoothing passed based on tcount
    if not (tcount >= 1):
        raise ValueError('tcount must be 1 or more. Default = 3 to T3 calucation.')
    elif tcount >= 1:
        gd = generalisedDEMA(period,data,vfactor)

        if tcount >1:
            for i in range(tcount-1):
                gd = generalisedDEMA(period,gd,vfactor)
                
    return gd