This is the seventh post about the Companion and Self-Testing Question List for my recent book Business Risk and Simulation Modelling in Practice: Using Excel, VBA and @RISK. As mentioned in earlier posts, the complete list of questions posted in this series will also shortly be available for free on the John Wiley web-site.
As a reminder, the full series of posts correspond to the Chapters of the book as follows:
- Post I: Risk Assessment Context and Processes (Chapters 1 and 2 of book)
- Post II: Risk Assessment, Quantification and Modelling: Approaches, Benefits and Challenges (Chapters 3, 4 and 5)
- Post III: Principles of Simulation Methods (Chapter 6)
- Post IV: Core Principles in the Design of Risk Models (Chapter 7)
- Post V: Measuring Risk using Statistics of Distributions (Chapter 8)
- Post VI: The Selection of Distributions for Use in Risk Models (Chapters 9 and 10)
- Post VII: Modelling Dependencies between Sources of Risk (Chapter 11)
- Post VIII: Using Excel/VBA for Simulation Modelling (Chapter 12)
- Post IX: Using @RISK for Simulation Modelling (Chapter 13)
This is Post VII, Modelling Dependencies between Sources of Risk (Chapter 11):
- What is the difference between the modelling of general dependency relationships and the modelling of dependencies between the sampling processes of distributions?
- What are the two main types of dependency relationships, and the key sub-categories with each?
- Provide examples of various types of parameter-type dependency.
- What is meant by common risk drivers, and what are the frequent effects on a model’s output if common risk drivers are overlooked or ignored?
- What is the role of scenario techniques in dependency modelling?
- What are the main types and uses of re-sampling methods?
- To what extent would variables appear correlated even if the relationship between them is one of parameter dependency?
- What are some of the benefits of using correlation approaches?
- What are the potential disadvantages of correlation approaches?
- What is meant by copula functions?
- If parameter dependencies exist between items in a model, to what extent would the model outputs (post simulation) be the same if these dependencies were replaced with correlation or copula approaches?
- Derive the exact formulae for each element of a 3×3 Cholesky decomposition, assuming that each of the three variables is correlated with the same coefficient. (Further exercise: a) Implement these in Excel and b) Build a simulation model (using either VBA, @RISK, or some other tool) to show that the results of using this decomposition does produce the appropriately correlated random numbers).
- Explain what is meant by an inconsistent or invalid correlation matrix. To what extent can such a matrix arise when using actual historic information?
- List some key types of time-series models.
- Explain what is meant by a convexity adjustment, and how it arises in models using geometric Brownian motion?
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