def _pair_exp_cov(X, Y, span=<NUM_LIT>):
covariation = (X - X.mean()) * (Y - Y.mean())<EOL>if span < <NUM_LIT:10>:<EOL><INDENT>warnings.warn("<STR_LIT>")<EOL><DEDENT>return covariation.ewm(span=span).mean()[-<NUM_LIT:1>]<EOL>
Calculate the exponential covariance between two timeseries of returns.

:param X: first time series of returns
:type X: pd.Series
:param Y: second time series of returns
:type Y: pd.Series
:param span: the span of the exponential weighting function, defaults to 180
:type span: int, optional
:return: the exponential covariance between X and Y
:rtype: float