credit_data

A dataset containing total aggregate losses from three sub-portfolios, generated through a binomial credit model.

datasets

An efficient sensitivity analysis for stochastic models based on
Monte Carlo samples. Provides weights on simulated scenarios from a
stochastic model, such that stressed random variables fulfil given
probabilistic constraints (e.g. specified values for risk measures),
under the new scenario weights. Scenario weights are selected by
constrained minimisation of the relative entropy to the baseline model.
The 'SWIM' package is based on Pesenti S.M., Millossovich P., Tsanakas A. (2019)
"Reverse Sensitivity Testing: What does it take to break the model"
<openaccess.city.ac.uk/id/eprint/18896/> and Pesenti S.M. (2021)
"Reverse Sensitivity Analysis for Risk Modelling" <https://www.ssrn.com/abstract=3878879>.

Silvana M. Pesenti

SWIM

Scenario Weights for Importance Measurement

Alberto Bettini

Pietro Millossovich

Andreas Tsanakas

Zhuomin Mao

Kent Wu

credit_data function

A data frame with 100,000 rows and 7 variables:<dl class="dl-horizontal">
 <dt>L</dt><dd>total aggregate loss of a portfolio consisting
 of three homogeneous sub-portfolios L1, L2 and L3</dd>
 <dt>L1</dt><dd>aggregate loss of sub-portfolio 1</dd>
 <dt>L2</dt><dd>aggregate loss of sub-portfolio 2</dd>
 <dt>L3</dt><dd>aggregate loss of sub-portfolio 3</dd>
 <dt>H1</dt><dd>(conditional) default probability of sub-portfolio 1</dd>
 <dt>H2</dt><dd>(conditional) default probability of sub-portfolio 2</dd>
 <dt>H3</dt><dd>(conditional) default probability of sub-portfolio 3</dd>
</dl>

Format

Credit data set — credit_data

A data frame with 100,000 rows and 7 variables:<dl class='dl-horizontal'>
 <dt>L</dt><dd>total aggregate loss of a portfolio consisting
 of three homogeneous sub-portfolios L1, L2 and L3</dd>
 <dt>L1</dt><dd>aggregate loss of sub-portfolio 1</dd>
 <dt>L2</dt><dd>aggregate loss of sub-portfolio 2</dd>
 <dt>L3</dt><dd>aggregate loss of sub-portfolio 3</dd>
 <dt>H1</dt><dd>(conditional) default probability of sub-portfolio 1</dd>
 <dt>H2</dt><dd>(conditional) default probability of sub-portfolio 2</dd>
 <dt>H3</dt><dd>(conditional) default probability of sub-portfolio 3</dd>
</dl>

credit_data: Credit data set

Description

Usage

Arguments

Format