pandas.stats.moments.ewmvar

pandas.stats.moments.ewmvar(arg, com=None, span=None, halflife=None, min_periods=0, bias=False, freq=None, time_rule=None)

Exponentially-weighted moving variance

Parameters :

arg : Series, DataFrame

com : float. optional

Center of mass: \alpha = 1 / (1 + com),

span : float, optional

Specify decay in terms of span, \alpha = 2 / (span + 1)

halflife : float, optional

Specify decay in terms of halflife, :math: alpha = 1 - exp(log(0.5) / halflife)

min_periods : int, default 0

Number of observations in sample to require (only affects beginning)

freq : None or string alias / date offset object, default=None

Frequency to conform to before computing statistic time_rule is a legacy alias for freq

adjust : boolean, default True

Divide by decaying adjustment factor in beginning periods to account for imbalance in relative weightings (viewing EWMA as a moving average)

bias : boolean, default False

Use a standard estimation bias correction

Returns :

y : type of input argument

Notes

Either center of mass or span must be specified

EWMA is sometimes specified using a “span” parameter s, we have have that the decay parameter \alpha is related to the span as \alpha = 2 / (s + 1) = 1 / (1 + c)

where c is the center of mass. Given a span, the associated center of mass is c = (s - 1) / 2

So a “20-day EWMA” would have center 9.5.