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Innovations in Quantitative Risk Management
Computation is based on models and applies algorithms. Both a model and an algorithm can be sources of risks, which will be discussed in this paper. The risk from the algorithm stems from erroneous results, the topic of the first part of this paper. We attempt to give a definition of computational risk, and propose how to avoid it. Concerning the underlying model, our concern will not be the "model error". Rather, even the reality (or a perfect model) can be subjected to structural changes:doi:10.1007/978-3-319-09114-3_17 fatcat:dmwoheedxvay7pqedu6raowlre