pandas.stats.moments.ewmvar

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

Exponentially-weighted moving variance

arg : Series, DataFrame com : float. optional

Center of mass: alpha = com / (1 + com),
span : float, optional
Specify decay in terms of span, alpha = 2 / (span + 1)
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

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 = 1 - 2 / (s + 1) = c / (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.

y : type of input argument