hma#
API documentation for pandas_ta.overlap.hma Python function.
- hma(close, length=None, offset=None, **kwargs)[source]#
Hull Moving Average (HMA)
The Hull Exponential Moving Average attempts to reduce or remove lag in moving averages.
- Sources:
- Calculation:
- Default Inputs:
length=10
WMA = Weighted Moving Average half_length = int(0.5 * length) sqrt_length = int(sqrt(length))
wmaf = WMA(close, half_length) wmas = WMA(close, length) HMA = WMA(2 * wmaf - wmas, sqrt_length)
- Args:
close (pd.Series): Series of ‘close’s length (int): It’s period. Default: 10 offset (int): How many periods to offset the result. Default: 0
- Kwargs:
fillna (value, optional): pd.DataFrame.fillna(value) fill_method (value, optional): Type of fill method
- Returns:
pd.Series: New feature generated.