t3#

API documentation for pandas_ta.overlap.t3 Python function.

t3(close, length=None, a=None, talib=None, offset=None, **kwargs)[source]#

Tim Tillson’s T3 Moving Average (T3)

Tim Tillson’s T3 Moving Average is considered a smoother and more responsive moving average relative to other moving averages.

Sources:

http://www.binarytribune.com/forex-trading-indicators/t3-moving-average-indicator/

Calculation:
Default Inputs:

length=10, a=0.7

c1 = -a^3 c2 = 3a^2 + 3a^3 = 3a^2 * (1 + a) c3 = -6a^2 - 3a - 3a^3 c4 = a^3 + 3a^2 + 3a + 1

ema1 = EMA(close, length) ema2 = EMA(ema1, length) ema3 = EMA(ema2, length) ema4 = EMA(ema3, length) ema5 = EMA(ema4, length) ema6 = EMA(ema5, length) T3 = c1 * ema6 + c2 * ema5 + c3 * ema4 + c4 * ema3

Args:

close (pd.Series): Series of ‘close’s length (int): It’s period. Default: 10 a (float): 0 < a < 1. Default: 0.7 talib (bool): If TA Lib is installed and talib is True, Returns the TA Lib

version. Default: True

offset (int): How many periods to offset the result. Default: 0

Kwargs:

adjust (bool): Default: True presma (bool, optional): If True, uses SMA for initial value. fillna (value, optional): pd.DataFrame.fillna(value) fill_method (value, optional): Type of fill method

Returns:

pd.Series: New feature generated.