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get started with risk management toolbox -凯发k8网页登录

develop risk models and perform risk simulation

risk management toolbox™ provides functions and interactive workflows for mathematical modeling and simulation of credit, insurance, and market risk. you can perform lifetime credit modeling of probabilities of default (pd), exposure at default (ead), and loss given default (lgd), as well as expected credit loss (ecl) calculations. you can assess corporate and consumer credit risk, create credit scorecards, estimate probabilities of default, perform credit portfolio analysis, and backtest models to assess potential for financial loss. the toolbox lets you identify important scorecard variables using the predictor screening tools and use the binning explorer app to automatically or manually bin variables for credit scorecards. it also includes mortality and unpaid claims models to quantify and analyze insurance risk. market risk can be assessed with backtesting and simulation tools to evaluate value-at-risk (var) and expected shortfall (es).

tutorials

    overviews

    • risk modeling with risk management toolbox
      learn about the tools for modeling seven areas of risk assessment.

    • when using a creditdefaultcopula object, predicting the credit losses for a counterparty depends on three main elements.

    • use multiple var backtesting tools for assessing var models.

    • use multiple expected shortfall backtesting tools for assessing var models.

    workflows

    • bin data to create credit scorecards using binning explorer
      create a credit scorecard using the binning explorer app.

    • this example shows a common workflow for using a creditdefaultcopula object to measure default risk for a credit portfolio.

    • this example shows a common workflow for using a creditmigrationcopula object to measure credit migration risk for a credit portfolio.

    • this example shows a value-at-risk (var) backtesting workflow and the use of var backtesting tools.
    • expected shortfall (es) backtesting workflow with no model distribution information
      this example shows an expected shortfall (es) backtesting workflow with no model distribution information and the use of esbacktest object.

    • this example shows an expected shortfall (es) backtesting workflow using simulation and the use of esbacktestbysim object.

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