portvine_roll-class: S4 output class for the function 'estimate_risk_roll()'

In portvine: Vine Based (Un)Conditional Portfolio Risk Measure Estimation

S4 output class for the function estimate_risk_roll()

Description

The main output class for the function estimate_risk_roll()is portvine_roll but in the conditional case the child class cond_portvine_roll with some extra slots (below visible by the !C!) is returned.

Usage

## S4 method for signature 'portvine_roll'
show(object)

## S4 method for signature 'cond_portvine_roll'
show(object)

## S4 method for signature 'portvine_roll'
summary(object)

## S4 method for signature 'cond_portvine_roll'
summary(object)

Arguments

object

An object of class portvine_roll or cond_portvine_roll

Details

For easy access for the most important slots and some filtering functionality have a look at the accessor methods risk_estimates(), fitted_vines(), fitted_marginals().

Value

object of class portvine_roll

object of class cond_portvine_roll

Slots

risk_estimates

data.table with the columns risk_measure, risk_est, alpha, row_num, vine_window and realized (here all samples also in the conditional case are used)

fitted_marginals

named list with an entry for each asset containing a rugarch::ugarchroll class object that encompasses the marginal model fit.

fitted_vines

list of rvinecopulib::vinecop class objects each entry corresponds to one vine window.

marginal_settings

containing the specification used for the ARMA-GARCH fitting i.e. marginal models. Is of class marginal_settings.

vine_settings

containing the specifications used for the vine fitting. Is of class vine_settings.

risk_measures

a character vector displaying the estimated risk measures.

alpha

numeric vector in (0,1) displaying the confidence levels used when estimating the risk measures.

weights

the numeric positive weights of the assets. (Matrix with each row corresponding to one vine window) The weights of conditional variables are always 0.

cond_estimation

logical value indicating whether the conditional estimation approach for the risk measures was used.

n_samples

positive numeric count displaying how many return samples were used for the risk measure estimation.

time_taken

numeric value displaying how many minutes the whole estimation process took.

cond_risk_estimates

!C! data.table with the same columns as the risk_estimate slot has + the additional conditional columns with the respective conditioning value and the column character cond_u that indicates the used conditional quantile level or the conditional value corresponding to the residual one time unit prior with "prior_resid" or the realized residual with "resid".

cond_vars

!C! character vector with the names of the variables that were used to sample conditionally from.

cond_u

!C! a numeric vector specifying the corresponding quantiles in (0,1) of the conditional variable(s) conditioned on which the conditional risk measures were calculated.

See Also

estimate_risk_roll(), risk_estimates(), fitted_vines(), fitted_marginals()

portvine documentation built on May 29, 2024, 2:27 a.m.