mirror of
https://github.com/wassname/pandas-ta.git
synced 2026-06-27 16:10:07 +08:00
James Sawyer
66 lines
1.7 KiB
Python
66 lines
1.7 KiB
Python
# -*- coding: utf-8 -*-
|
|
from math import sqrt
|
|
from .wma import wma
|
|
from ..utils import get_offset, verify_series
|
|
|
|
|
|
def hma(close, length=None, offset=None, **kwargs):
|
|
"""Indicator: Hull Moving Average (HMA)"""
|
|
# Validate Arguments
|
|
close = verify_series(close)
|
|
length = int(length) if length and length > 0 else 10
|
|
min_periods = (int(kwargs["min_periods"]) if "min_periods" in kwargs and
|
|
kwargs["min_periods"] is not None else length)
|
|
offset = get_offset(offset)
|
|
|
|
# Calculate Result
|
|
half_length = int(length / 2)
|
|
sqrt_length = int(sqrt(length))
|
|
|
|
wmaf = wma(close=close, length=half_length)
|
|
wmas = wma(close=close, length=length)
|
|
hma = wma(close=2 * wmaf - wmas, length=sqrt_length)
|
|
|
|
# Offset
|
|
if offset != 0:
|
|
hma = hma.shift(offset)
|
|
|
|
# Name & Category
|
|
hma.name = f"HMA_{length}"
|
|
hma.category = "overlap"
|
|
|
|
return hma
|
|
|
|
|
|
hma.__doc__ = """Hull Moving Average (HMA)
|
|
|
|
The Hull Exponential Moving Average attempts to reduce or remove lag in moving
|
|
averages.
|
|
|
|
Sources:
|
|
https://alanhull.com/hull-moving-average
|
|
|
|
Calculation:
|
|
Default Inputs:
|
|
length=10
|
|
WMA = Weighted Moving Average
|
|
half_length = int(0.5 * length)
|
|
sqrt_length = int(math.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.
|
|
"""
|