Model Outputs

Definition

Model Outputs denotes the list of numerical or categorical variables that encapsulate the outcome of a model calculation or "run". The significance of such outcomes lies in the manner in which they are subsequently used in internal and/or external processes.

Examples

There is a wide variety of possible model outputs:

• Continuous Numerical values (valuations, hedge sizes, continuous risk scores)
• Discrete Numerical values or Categorical variables (ratings)
• Distributions (rankings of possible scenario losses)
• Discrete indicators (yes / no)
• Tabular Data (risk allocation to positions)

Issues and Challenges

• Model outputs are frequently becoming in turn Risk Data (Risk Parameters) that are used as Model Inputs in further models, creating chains of dependencies and possible Model Risk propagation
• Careful documentation of all model outputs in use is part of good Model Governance

See Also

• Model Inputs