Cont and Deguest propose a method for computing model risk exposures in multi-asset equity derivatives and show that options which depend on the worst or best performances in a basket (so called rainbow option) are more exposed to model uncertainty than index options.Gennheimer investigates the model risk present in pricing basket default derivatives.If you are updating from a Class D license to a Class C, then there is no road test requirement unless the endorsement requires one.Passenger, air brake, and school bus endorsements require road tests.He writes "Understanding the robustness of models used for hedging and risk-management purposes with respect to the assumption of perfectly liquid markets is therefore an important issue in the analysis of model risk in general." Convertible bonds, mortgage-backed securities, and high-yield bonds can often be illiquid and difficult to value.Hedge funds that trade these securities can be exposed to model risk when calculating monthly NAV for its investors.
Fender and Kiff (2004) note that holding complex financial instruments, such as CDOs, "translates into heightened dependence on these assumptions and, thus, higher model risk.
Rantala (2006) mentions that "In the face of model risk, rather than to base decisions on a single selected 'best' model, the modeller can base his inference on an entire set of models by using model averaging." In the context of derivative pricing Cont (2006) proposes a quantitative approach to measurement of model risk exposures in derivatives portfolios: first, a set of benchmark models is specified and calibrated to market prices of liquid instruments, then the target portfolio is priced under all benchmark models.
A measure of exposure to model risk is then given by the difference between the current portfolio valuation and the worst-case valuation under the benchmark models.
They write "From a quantitative perspective, in the case of pricing models, we can set up a reserve to allow for the difference in estimations using alternative models.
In the case of risk measurement models, scenario analysis can be undertaken for various fluctuation patterns of risk factors, or position limits can be established based on information obtained from scenario analysis." Taleb wrote when describing why most new models that attempted to correct the inadequacies of the Black–Scholes model failed to become accepted: "Traders are not fooled by the Black–Scholes–Merton model.