• documentation
main content

exposure at default models -凯发k8网页登录

estimate exposure at default

calculate the exposure at default (ead) using a regression, tobit, or beta model to predict the amount of loss exposure for a bank when a debtor defaults on a loan. calculate the estimated loss reserves using expected credit loss (ecl) calculator.

functions

create specified ead model object type
predict exposure at default
compute auroc and roc data
plot roc curve
compute r-square, rmse, correlation, and sample mean error of predicted and observed eads
scatter plot of predicted and observed eads
compute the lifetime ecl at individual or portfolio level

objects

create regression model object for exposure at default
create tobit model object for exposure at default
create beta model object for exposure at default

topics

  • compare results for regression and tobit ead models

    this example shows how to use fiteadmodel to create a regression model and a tobit model for exposure at default (ead) and then compare the results.


  • this example shows how to perform expected credit loss (ecl) computations with portfolioecl using simulated loan data, macro scenario data, and an existing lifetime probability of default (pd) model.

  • incorporate macroeconomic scenario projections in loan portfolio ecl calculations

    this example shows how to generate macroeconomic scenarios and perform expected credit loss (ecl) calculations for a portfolio of loans.


  • this example shows how to work with consumer (retail) credit panel data to visualize observed probabilities of default (pds) at different levels.


  • exposure at default (ead) is the loss exposure for a bank when a debtor defaults on a loan.

网站地图