def var_gaussian(r, level=5, modified=False):
    '\n    Returns the Parametric Gauusian VaR of a Series or DataFrame\n    If "modified" is True, then the modified VaR is returned,\n    using the Cornish-Fisher modification\n    '
    r = r[((r != 0) & r.notnull())]
    z = norm.ppf((level / 100))
    if modified:
        s = skewness(r)
        k = kurtosis(r)
        z = (((z + ((((z ** 2) - 1) * s) / 6)) + ((((z ** 3) - (3 * z)) * (k - 3)) / 24)) - ((((2 * (z ** 3)) - (5 * z)) * (s ** 2)) / 36))
    return (- (r.mean() + (z * r.std(ddof=0))))
Returns the Parametric Gauusian VaR of a Series or DataFrame
If "modified" is True, then the modified VaR is returned,
using the Cornish-Fisher modification
def var_gaussian(r, level=5, modified=False):
    '\n    Returns the Parametric Gauusian VaR of a Series or DataFrame\n    If "modified" is True, then the modified VaR is returned,\n    using the Cornish-Fisher modification\n    '
    r = r[((r != 0) & r.notnull())]
    z = norm.ppf((level / 100))
    if modified:
        s = skewness(r)
        k = kurtosis(r)
        z = (((z + ((((z ** 2) - 1) * s) / 6)) + ((((z ** 3) - (3 * z)) * (k - 3)) / 24)) - ((((2 * (z ** 3)) - (5 * z)) * (s ** 2)) / 36))
    return (- (r.mean() + (z * r.std(ddof=0))))