Description

This two-day course aims to provide participants with the tools necessary to conduct robust risk analyses using @RISK5 across a range of applications. The course aims to maximise hands-on experience by building most models from scratch and using this process to facilitate the learning and use of the software in practice.

Day 1 is focussed on the fundamentals of @RISK, including learning to operate the software and to interpret the results of the analysis, including hands-on exercises related to cost budgeting, risk registers, and scenario modelling.

Day 2 is focussed on extending participants’ @RISK modelling techniques, including further topics in the selection and use of distributions and the capturing of dependency relationships, such as correlation. Further features of the software are also explored, and participants’ own modelling situations are discussed. Hands-on exercises include cash flow modelling, time series modelling, and the implementation of correlation. 

Detailed Agenda

Day 1: Fundamentals of @RISK

AM

• Introduction to risk analysis
• Benefits and purpose
• Brief revision of key statistical terms
• Hands-on exercise: cost budgeting
• Introduction to risk modeling using distributions
• Exercise using Triangular distributions
• Viewing an @RISK model
• RiskStatic and @RISK function swap
• Running a simulation, viewing and interpreting results
• Repeating a simulation, random number methods and number of iterations required
• Hands-on exercise: Risk mitigation
• Use of multiple simulations
• Use of @RISK Statistics functions for model outputs and inputs

PM

• Hands-on exercise: scenario modeling
• Use of the Discrete distribution
• Comparison with multiple simulations
• Hands-on exercise: event risks/ risk registers/frequency-severity models
• Use of the Binomial distribution
• Use of the Poisson, and Compound distributions (overview)
• Related applications (oil and gas, sales forecasting)
• Dependency modeling example (incl. multiple simulations)
• Further features
• Excel reports
• Simulation data
• Working with @RISK graphs

Day 2: Building Robust Models with @RISK

AM

• Selection and use of distributions for continuous uncertainty
• The Triangular and PERT distributions
• The Normal and Lognormal distributions
• Alternate parameter methods
• Hands-on exercises: Cash flow, time-series and further modelling applications
• Cash flow and time-series modelling (incl. extensions, such as mean-reverting processes, crash processes, Markov chains, as relevant)
• Valuing flexibility and real options
• Extensions of cost and risk register models
• Working with data
• Distribution fitting with BestFit
• Re-sampling methods
• Hands-on exercise: Modelling time-to-occurrence
• Introduction to other distributions (Geometric, Exponential, Weibull etc.)

PM

• Dependency and correlation modelling
• Comparing parameter dependency with correlated sampling (meaning, advantages and disadvantages)
• Measuring correlation coefficients
• Consistency of correlation matrices
• Hands-on exercise: Implementing correlation
• In cost modeling
• In time series models
• Further aspects of results reporting
• Tornado graphs and scatter plots: Creation and interpretation (incl. common mistakes)
• Model auditing tools
• Further topics and examples (open session) e.g.
• Review of pre-built models (e.g. oil and gas, environmental, pricing, insurance, optimisation etc)
• Use of other sensitivity analysis tools, macros, other functions and features etc

Credits available:
» 16 PDH toward AACEI certification
» 16 CPE

» Palisade Corporation
» Seminar Schedule