def alpha_beta_aligned(returns,
                       factor_returns,
                       risk_free=0.0,
                       period=DAILY,
                       annualization=None,
                       out=None):
    """Calculates annualized alpha and beta.

    If they are pd.Series, expects returns and factor_returns have already
    been aligned on their labels.  If np.ndarray, these arguments should have
    the same shape.

    Parameters
    ----------
    returns : pd.Series or np.ndarray
        Daily returns of the strategy, noncumulative.
        - See full explanation in :func:`~empyrical.stats.cum_returns`.
    factor_returns : pd.Series or np.ndarray
         Daily noncumulative returns of the factor to which beta is
         computed. Usually a benchmark such as the market.
         - This is in the same style as returns.
    risk_free : int, float, optional
        Constant risk-free return throughout the period. For example, the
        interest rate on a three month us treasury bill.
    period : str, optional
        Defines the periodicity of the 'returns' data for purposes of
        annualizing. Value ignored if `annualization` parameter is specified.
        Defaults are::

            'monthly':12
            'weekly': 52
            'daily': 252

    annualization : int, optional
        Used to suppress default values available in `period` to convert
        returns into annual returns. Value should be the annual frequency of
        `returns`.
    out : array-like, optional
        Array to use as output buffer.
        If not passed, a new array will be created.

    Returns
    -------
    alpha : float
    beta : float
    """
    if out is None:
        out = np.empty(returns.shape[1:] + (2,), dtype='float64')

    b = beta_aligned(returns, factor_returns, risk_free, out=out[..., 1])
    alpha_aligned(
        returns,
        factor_returns,
        risk_free,
        period,
        annualization,
        out=out[..., 0],
        _beta=b,
    )

    return out
Calculates annualized alpha and beta.

    If they are pd.Series, expects returns and factor_returns have already
    been aligned on their labels.  If np.ndarray, these arguments should have
    the same shape.

    Parameters
    ----------
    returns : pd.Series or np.ndarray
        Daily returns of the strategy, noncumulative.
        - See full explanation in :func:`~empyrical.stats.cum_returns`.
    factor_returns : pd.Series or np.ndarray
         Daily noncumulative returns of the factor to which beta is
         computed. Usually a benchmark such as the market.
         - This is in the same style as returns.
    risk_free : int, float, optional
        Constant risk-free return throughout the period. For example, the
        interest rate on a three month us treasury bill.
    period : str, optional
        Defines the periodicity of the 'returns' data for purposes of
        annualizing. Value ignored if `annualization` parameter is specified.
        Defaults are::

            'monthly':12
            'weekly': 52
            'daily': 252

    annualization : int, optional
        Used to suppress default values available in `period` to convert
        returns into annual returns. Value should be the annual frequency of
        `returns`.
    out : array-like, optional
        Array to use as output buffer.
        If not passed, a new array will be created.

    Returns
    -------
    alpha : float
    beta : float