fixed_point_computation_function: fixed_point_computation_function

In Martin-Summer-1090/syslosseval: Provide data and functions to support the analysis in Systemic Loss Evaluation

Description

This function computes the least and the greatest fire sale equilibrium according to theorem 2 in the paper to a given level of accuracy, which is set by default to 10^-9. In many cases the least and the greatest fire-sale equilibrium will coincide for a given set of data, but this need not generally be the case.

Usage

fixed_point_computation_function(
  mat,
  lb,
  data_idx,
  data_adv,
  base_year,
  constant,
  accuracy = 10^(-9)
)

Arguments

mat	A list of the initial state variable (output of make_state_variables())
lb	The critical leverage threshold called lambda_bar in the paper.
data_idx	The data-frame with the sovereign bond indices.
data_adv	The data-frame with the average daily volume figures.
base_year	The base year for the simulation
constant	The value of the constant kappa in the impact fuction (equation (9)).
accuracy	The accuracy of the fixed point approximation. Set by default to 10^9

Value

A tibble with variables delta_lower (lower fixed point), iterations_lower (iterations to converge to lower fixed point), delta_upper (upper fixed point), iterations_uppper( iterations to converge to the upper fixed point), delta_max (maximum impact), unique (logical variable which is true if fixed point is unique and false if it is not unique)

Examples

stress_data <- make_stress_data(eba_exposures_2016, eba_impairments_2016, 1, 2015)
state_variables <- make_state_variables(stress_data)
fixed_point_computation_function(
  mat = state_variables, lb = 33,
  data_idx = sovereign_bond_indices,
  data_adv = average_daily_volume_sovereign,
  base_year = 2015,
  constant = 1.5
)

Martin-Summer-1090/syslosseval documentation built on Dec. 17, 2021, 3:14 a.m.