code: 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)
docs: 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.