We recently looked at several key areas of focus when it comes to effective model risk management in 2012. In Massimo Morini’s recent book, “Understanding and Managing Model Risk: A Practical Guide for Quants, Traders and Validators” (The Wiley Finance Series), he focuses on model risk and validation from a more theoretical approach.
He explores the two different approaches to model validation set forth by the ‘Fathers of Quantitative Risk Management’-- Emanuel Derman, Professor at Columbia University, former Head of Quantitative Risk Management at Goldman Sachs, and author of “Models.Behaving.Badly” and Riccardo Rebonato, Head of Front Office Risk Management and Quantitative Analytics, RBS Global Banking & Markets, Visiting Lecturer, Mathematical Finance, Oxford University, and member of the Board of Directors of ISDA and GARP.
According to Emanuel Derman’s value approach, a model risk manager should consider the following questions:
- Is the payoff accurately described?
- Is the software reliable?
- Has the model been appropriately calibrated to the prices of simpler, liquid constituents that compromise the derivative?
- Does the model provide a realistic (or least plausible) description of the factors that affect the derivative’s value?
Mr. Derman’s value approach can be summarized by the following concept: “Model risk is the risk that the model is not a realistic (or at least plausible) description of the factors that affect the derivative’s value.”
Rebonato’s price approach, on the other hand, can be summarized by the following concept: “Model risk is the risk of a significant difference between the mark-to-model value of an instrument, and the price at which the same instrument is revealed to have traded in the market.”
The contribution Morini makes to the above theories is that he argues that the two approaches are actually the same – or at least have the same practical consequences to practitioners. Certainly, all of these concepts, along with Morini’s new book, provide food for thought when it comes to managing your model risk in 2012. If you have further questions, or would like more information about model risk management solutions, please contact firstname.lastname@example.org.