Model Assumptions

From Open Risk Manual

Definition

Model Assumptions denotes the large collection of explicitly stated or implicit premises, conventions, choices and other specifications on which any Risk Model is based. The suitability of those assumptions is a major factor behind the Model Risk associated with a given model.

Context

Inthe context of modelling economic, financial or other complex systems, model assumptions are necessary to simplify Model Development, or even make a model feasible / tractable.

Examples

Assumptions can be conceptual, mathematical or numerical in nature

Conceptual Assumptions

This class concerns idealizations and simplifications of the underlying entity or system that is being modeled

  • Idealizing and simplifying the behavior of complex systems such as markets (e.g. via assumptions on liquidity)
  • Simplifying the model of counterparties to legal contracts
  • Simplifying the model of an economy by assuming away heterogeneity
  • Injecting rational behavior assumptions

Mathematical Assumptions

This class concerns assumptions around the mathematical representation of the modelled system

  • Overall approach: e.g. Bayesian or Frequentist for statistical models
  • Choice of univariate distributions among competing choices
  • Implicity or explicit choices about multi-variate distributions and dependency
  • Choice of parameter fitting / calibration approaches among competing choices

Numerical Assumptions

  • Explicit selection of numerical values

Mitigation

  • Proper Model Documentation is a primary mechanism for recognizing (identifying) and aiming to control the possibly adverse influence of assumptions.
  • Model Validation, an independent review of modelling frameworks offers a second opinion.

Issues and Challenges

  • Undocumented / unrecognised model assumptions

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