Determines the annual volatility of a strategy.

    Parameters
    ----------
    returns : pd.Series or np.ndarray
        Periodic returns of the strategy, noncumulative.
        - See full explanation in :func:`~empyrical.stats.cum_returns`.
    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

    alpha : float, optional
        Scaling relation (Levy stability exponent).
    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
    -------
    annual_volatility : float

def annual_volatility(returns,
                      period=DAILY,
                      alpha=2.0,
                      annualization=None,
                      out=None):
    """
    Determines the annual volatility of a strategy.

    Parameters
    ----------
    returns : pd.Series or np.ndarray
        Periodic returns of the strategy, noncumulative.
        - See full explanation in :func:`~empyrical.stats.cum_returns`.
    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

    alpha : float, optional
        Scaling relation (Levy stability exponent).
    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
    -------
    annual_volatility : float
    """
    allocated_output = out is None
    if allocated_output:
        out = np.empty(returns.shape[1:])

    returns_1d = returns.ndim == 1

    if len(returns) < 2:
        out[()] = np.nan
        if returns_1d:
            out = out.item()
        return out

    ann_factor = annualization_factor(period, annualization)
    nanstd(returns, ddof=1, axis=0, out=out)
    out = np.multiply(out, ann_factor ** (1.0 / alpha), out=out)
    if returns_1d:
        out = out.item()
    return out