API documentation for pandas_ta.volatility.rvi Python function.
- rvi(close, high=None, low=None, length=None, scalar=None, refined=None, thirds=None, mamode=None, drift=None, offset=None, **kwargs)#
Relative Volatility Index (RVI)
The Relative Volatility Index (RVI) was created in 1993 and revised in 1995. Instead of adding up price changes like RSI based on price direction, the RVI adds up standard deviations based on price direction.
- Default Inputs:
length=14, scalar=100, refined=None, thirds=None
EMA = Exponential Moving Average STDEV = Standard Deviation
UP = STDEV(src, length) IF src.diff() > 0 ELSE 0 DOWN = STDEV(src, length) IF src.diff() <= 0 ELSE 0
UPSUM = EMA(UP, length) DOWNSUM = EMA(DOWN, length
RVI = scalar * (UPSUM / (UPSUM + DOWNSUM))
high (pd.Series): Series of ‘high’s low (pd.Series): Series of ‘low’s close (pd.Series): Series of ‘close’s length (int): The short period. Default: 14 scalar (float): A positive float to scale the bands. Default: 100 refined (bool): Use ‘refined’ calculation which is the average of
RVI(high) and RVI(low) instead of RVI(close). Default: False
thirds (bool): Average of high, low and close. Default: False mamode (str): See
`help(ta.ma)`. Default: ‘ema’ offset (int): How many periods to offset the result. Default: 0
fillna (value, optional): pd.DataFrame.fillna(value) fill_method (value, optional): Type of fill method
pd.DataFrame: lower, basis, upper columns.