SWIM 1.0.0 -
current develop version on GitHub
Major changes:
Additional functions and features
Wasserstein distance
stress_wass():
- A wrapper for the stress functions using the 2-Wasserstein
distance
stress_RM_w():
- a stressed model component (random variable) fulfills a constraint
on its risk measure defined by a gamma function.
stress_RM_mean_sd_w():
- a stressed model component (random variable) fulfills a constraint
on its mean, standard deviation, and risk measure defined by a gamma
function.
stress_HARA_RM_w():
- a stressed model component (random variable) fulfills a constraint
on its HARA utility defined by a, b and eta parameter and risk measure
defined by a gamma function.
stress_mean_sd_w():
- a stressed model component (random variable) fulfills a constraint
on its mean and standard deviation.
stress_mean_w():
- a stressed model component (random variable) fulfills a constraint
on its mean.
Functions
mean_stressed():
- sample mean of chosen stressed model components, subject to the
calculated scenario weights.
sd_stressed():
- sample standard deviation of chosen stressed model components,
subject to the calculated scenario weights.
var_stressed():
- sample variance of chosen stressed model components, subject to the
calculated scenario weights.
cor_stressed():
- sample correlation coefficient of chosen stressed model components,
subject to the calculated scenario weights.
cdf_stressed():
- the empirical distribution function of a stressed model component
(random variable) under the scenario weights.
rename_SWIM():
- Get a new SWIM object with desired names.
Features
stress():
- A parameter “names” to all stress functions, which allows to name a
stress differently than just “stress 1”, “stress 2”, etc.
- A parameter “log” that allows users to inspect weights’ statistics,
including minimum, maximum, standard deviation, Gini coefficient, and
entropy.
sensitivity():
- A parameter “p” can be specified for the degree of Wasserstein
distance.
Minor changes
- fix minor bug in
summary().
- add
base argument for quantile_stressed()
and an error message if the input has wCol has dimension
larger than 1.
SWIM 0.2.2 - current
version on CRAN
Major
changes: Additional functions and features
plot_quantile():
- the function plots the empirical quantile of model components,
subject to scenario weights.
plot_weights():
- the function plots the scenario weights of a stressed model against
model components.
stress_moment():
- add parameter “normalise” that allows to linearly normalise the
values called by
nleqslv.
- the function prints a table with the required and achieved moments
and the absolute and relative error.
stress_VaR_ES():
- add parameter “normalise” that allows to linearly normalise the
values before
uniroot is applied.
Minor changes
- fix bug in merging different stress objects.
SWIM 0.2.1
Minor changes
- add vignette
- fix bug in
merge().
- fix bug in
sensitivity().
SWIM 0.2.0
Major changes
Additional functions and
data sets
VaR_stressed():
- the function calculates the VaR of model components, subject to
scenario weights.
ES_stressed():
- the function calculates the ES of model components, subject to
scenario weights.
credit_data:
- a data set containing aggregate losses from a credit portfolio,
generated through a binomial credit model.
Amendments to functions
stress_VaR():
- amendment to the calculation of scenario weights when the specified
VaR cannot be achieved.
- returns a message if the achieved VaR is not equal to the stressed
VaR specified.
- specs of the
SWIM object contains the achieved VaR
- allowing for stressing VaR downwards
stress_VaR_ES():
- amendment analogous to the
stress_VaR().
- returns a message if the achieved VaR is not equal to the stressed
VaR specified.
- specs of the
SWIM object contains the achieved VaR
- allowing for stressing VaR and ES downwards
Minor changes
stress():
- parameter
x can have missing column names.
stress_moment():
- additional parameter
show; if TRUE
(default is FALSE), the result of nleqslv() is
printed.