accbands#

API documentation for pandas_ta.volatility.accbands Python function.

accbands(high, low, close, length=None, c=None, drift=None, mamode=None, offset=None, **kwargs)[source]#

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.