Presented by Ronald Holanek, founder and president, Financial Risk Group; or Michael Forno, vice president, Financial Risk Group; or Regitze Ladekarl, senior risk consultant, Financial Risk Group
This course introduces the many new features in SAS Risk Dimensions 5.2 and explains how to use them.
Learn how to
- incorporate multiple covariance matrices to create a dynamic covariance simulation
- set options to output Marginal VaR, Component VaR, and VaR Without, as well as how to calculate VaR and ES at multiple confidence levels
- combine two or more simulation methods (for example, historical, Monte Carlo, and covariance) in one analysis to generate the risk factors needed for valuing the portfolio
- utilize normal mixture and t copulas, and define their correlation matrix type (for example, Pearson, Spearman, or Kendall)
- make trades across instruments during simulations to accommodate changes in business strategies
- use the aggregation mapping and correlated aggregation tools to measure portfolio performance
- employ discrete or continuous transition matrices, which can be static or dynamic, in an analysis.
Who should attend
Users of SAS Risk Dimensions 5.2
Before attending this course, you should have experience using SAS Risk Dimensions 4.2 and have working knowledge of risk management.
This course addresses SAS Risk Dimensions.
- dynamic covariance simulation
- Cholesky decomposition
- shrinkage approach
- principal component analysis
VaR Measures and Features
- VaR measures
- multiple thresholds
- mixed simulations
- enhanced copula functionality
- trading methods and reinvestment
- performance management
- aggregation mapping
- correlation and MTM-weighted aggregation
- Brinson's method
- transition matrices
- parameter matrices
- cash flow bucketing
- access to SAS features
- OLAP output