# -*- coding: utf-8 -*-
from pandas import DataFrame
from pandas_ta.overlap import ma
from pandas_ta.utils import get_drift, get_offset, non_zero_range, verify_series
[docs]def accbands(high, low, close, length=None, c=None, drift=None, mamode=None, offset=None, **kwargs):
"""Indicator: Acceleration Bands (ACCBANDS)"""
# Validate arguments
length = int(length) if length and length > 0 else 20
c = float(c) if c and c > 0 else 4
mamode = mamode if isinstance(mamode, str) else "sma"
high = verify_series(high, length)
low = verify_series(low, length)
close = verify_series(close, length)
drift = get_drift(drift)
offset = get_offset(offset)
if high is None or low is None or close is None: return
# Calculate Result
high_low_range = non_zero_range(high, low)
hl_ratio = high_low_range / (high + low)
hl_ratio *= c
_lower = low * (1 - hl_ratio)
_upper = high * (1 + hl_ratio)
lower = ma(mamode, _lower, length=length)
mid = ma(mamode, close, length=length)
upper = ma(mamode, _upper, length=length)
# Offset
if offset != 0:
lower = lower.shift(offset)
mid = mid.shift(offset)
upper = upper.shift(offset)
# Handle fills
if "fillna" in kwargs:
lower.fillna(kwargs["fillna"], inplace=True)
mid.fillna(kwargs["fillna"], inplace=True)
upper.fillna(kwargs["fillna"], inplace=True)
if "fill_method" in kwargs:
lower.fillna(method=kwargs["fill_method"], inplace=True)
mid.fillna(method=kwargs["fill_method"], inplace=True)
upper.fillna(method=kwargs["fill_method"], inplace=True)
# Name and Categorize it
lower.name = f"ACCBL_{length}"
mid.name = f"ACCBM_{length}"
upper.name = f"ACCBU_{length}"
mid.category = upper.category = lower.category = "volatility"
# Prepare DataFrame to return
data = {lower.name: lower, mid.name: mid, upper.name: upper}
accbandsdf = DataFrame(data)
accbandsdf.name = f"ACCBANDS_{length}"
accbandsdf.category = mid.category
return accbandsdf
accbands.__doc__ = \
"""Acceleration Bands (ACCBANDS)
Acceleration Bands created by Price Headley plots upper and lower envelope
bands around a simple moving average.
Sources:
https://www.tradingtechnologies.com/help/x-study/technical-indicator-definitions/acceleration-bands-abands/
Calculation:
Default Inputs:
length=10, c=4
EMA = Exponential Moving Average
SMA = Simple Moving Average
HL_RATIO = c * (high - low) / (high + low)
LOW = low * (1 - HL_RATIO)
HIGH = high * (1 + HL_RATIO)
if 'ema':
LOWER = EMA(LOW, length)
MID = EMA(close, length)
UPPER = EMA(HIGH, length)
else:
LOWER = SMA(LOW, length)
MID = SMA(close, length)
UPPER = SMA(HIGH, length)
Args:
high (pd.Series): Series of 'high's
low (pd.Series): Series of 'low's
close (pd.Series): Series of 'close's
length (int): It's period. Default: 10
c (int): Multiplier. Default: 4
mamode (str): See ```help(ta.ma)```. Default: 'sma'
drift (int): The difference period. Default: 1
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.DataFrame: lower, mid, upper columns.
"""