Model Risk: A Conceptual Framework for RiskMeasurement and Hedging

The vast majority of approaches to risk management, hedging, or portfolio planningassume that some model is given. However, under model risk, the true data gener-ating process is not known. The focus of this paper is on problems related to thehedging of derivative contracts. We explain the main general concepts, provide eco-nomic interpretations, and illustrate our arguments by simple and straightforwardexamples.Model risk can be dealt with in several ways, e.g. by not taking model risk intoaccount at all (’naive’ approach), by relying on worst case approaches, or by usingBayesian techniques. The integration of market risk and model risk turns out becrucial, since a risk measure that is used to find an optimal, risk-minimizing hedgingstrategy should capture the overall gains and losses of a position, irrespective of theirreason. Since the full problem may be much too complicated to solve in realisticmodel setups, we furthermore discuss robust hedging strategies determined undersimplifying assumptions. Our examples show that model risk is relevant and thatthe choice of risk measure matters, so that it should be based on sound economicarguments.