Kathrin GlauMatthias SchererRudi Zagst2025-11-132025-11-132013978-3-319-09114-3https://doi.org/10.1007/978-3-319-09114-3https://link.springer.com/openurl?genre=book&isbn=978-3-319-09114-3http://bibliovirtual.umar.mx:4000/handle/123456789/1259Libro electrónico.Quantitative models are omnipresent –but often controversially discussed– in todays risk management practice. New regulations, innovative financial products, and advances in valuation techniques provide a continuous flow of challenging problems for financial engineers and risk managers alike. Designing a sound stochastic model requires finding a careful balance between parsimonious model assumptions, mathematical viability, and interpretability of the output. Moreover, data requirements and the end-user training are to be considered as well.en-USBook