create_comonotonic_ra

rearrangement_algorithm.create_comonotonic_ra(level: float, quant, num_steps: int = 10)

Creating a matrix with comonotonic random variables

This function creates a rearrangement matrix that represents a joint distribution of comonotonic random variables for a given confidence level. Both upper and lower bound approximations are returned. For mathematical details, see 1

Parameters

  • level (float) – Confidence level between 0 and 1.

  • quant (list) – List of marginal quantile functions

  • num_steps (int) – Number of discretization points

Returns

  • x_ra_low (numpy.array) – Lower bound approximation of the rearrangement matrix.

  • x_ra_up (numpy.array) – Upper bound approximation of the rearrangement matrix.

References

1

P. Embrechts, G. Puccetti, and L. Rüschendorf, “Model uncertainty and VaR aggregation,” Journal of Banking & Finance, vol. 37, no. 8, pp. 2750-2764, Aug. 2013.