pyfolio/timeseries.py
def var_cov_var_normal(P, c, mu=0, sigma=1):
    """
    Variance-covariance calculation of daily Value-at-Risk in a
    portfolio.

    Parameters
    ----------
    P : float
        Portfolio value.
    c : float
        Confidence level.
    mu : float, optional
        Mean.

    Returns
    -------
    float
        Variance-covariance.
    """

    alpha = sp.stats.norm.ppf(1 - c, mu, sigma)
    return P - P * (alpha + 1)
def var_cov_var_normal(P, c, mu=0, sigma=1):
    """
    Variance-covariance calculation of daily Value-at-Risk in a
    portfolio.

    Parameters
    ----------
    P : float
        Portfolio value.
    c : float
        Confidence level.
    mu : float, optional
        Mean.

    Returns
    -------
    float
        Variance-covariance.
    """

    alpha = sp.stats.norm.ppf(1 - c, mu, sigma)
    return P - P * (alpha + 1)
def var_cov_var_normal ( P , c , mu = 0 , sigma = 1 ) : alpha = sp . stats . norm . ppf ( 1 - c , mu , sigma ) return P - P * ( alpha + 1 )
Variance-covariance calculation of daily Value-at-Risk in a
    portfolio.

    Parameters
    ----------
    P : float
        Portfolio value.
    c : float
        Confidence level.
    mu : float, optional
        Mean.

    Returns
    -------
    float
        Variance-covariance.
Variance - covariance calculation of daily Value - at - Risk in a portfolio .